Search results for: association rule mining

Authors: Ghirmay Teklemicheal, Samsom Mehari, Sara Tesfay

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Objectives: A total of 1074 suspected chikungunya cases were reported in Tesseney Province, Gash Barka region, Eritrea, during an outbreak. This study was aimed to assess the possible association of chikungunya severity among ABO blood groups and other potential determinants. Methods: A sex-matched and age-matched case-control study was conducted during the outbreak. For each case, one control subject had been selected from the mild Chikungunya cases. Along the same line of argument, a second control subject had also been designated through which neighborhood of cases were analyzed, scrutinized, and appeared to the scheme of comparison. Time is always the most sacrosanct element in pursuance of any study. According to the temporal calculation, this study was pursued from October 15, 2018, to November 15, 2018. Coming to the methodological dependability, calculating odds ratios (ORs) and conditional (fixed-effect) logistic regression methods were being applied. As a consequence of this, the data was analyzed and construed on the basis of the aforementioned methodological systems. Results: In this outbreak, 137 severe suspected chikungunya cases and 137 mild chikungunya suspected patients, and 137 controls free of chikungunya from the neighborhood of cases were analyzed. Non-O individuals compared to those with O blood group indicated as significant with a p-value of 0.002. Separate blood group comparison among A and O blood groups reflected as significant with a p-value of 0.002. However, there was no significant difference in the severity of chikungunya among B, AB, and O blood groups with a p-value of 0.113 and 0.708, respectively, and a strong association of chikungunya severity was found with hypertension and diabetes (p-value of < 0.0001); whereas, there was no association between chikungunya severity and asthma with a p-value of 0.695 and also no association with pregnancy (p-value =0.881), ventilator (p-value =0.181), air conditioner (p-value = 0.247), and didn’t use latrine and pit latrine (p-value = 0.318), among individuals using septic and pit latrine (p-value = 0.567) and also among individuals using flush and pit latrine (p-value = 0.194). Conclusions: Non- O blood groups were found to be at risk more than their counterpart O blood group individuals with severe form of chikungunya disease. By the same token, individuals with chronic disease were more prone to severe forms of the disease in comparison with individuals without chronic disease. Prioritization is recommended for patients with chronic diseases and non-O blood group since they are found to be susceptible to severe chikungunya disease. Identification of human cell surface receptor(s) for CHIKV is quite necessary for further understanding of its pathophysiology in humans. Therefore, molecular and functional studies will necessarily be helpful in disclosing the association of blood group antigens and CHIKV infections.

Keywords: Chikungunya, Chikungunya virus, disease outbreaks, case-control studies, Eritrea

Procedia PDF Downloads 159

Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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Authors: L. Chevez, A. Apaza, J. Rodriguez, R. Puga, H. Loro, Juan Z. Davalos

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Virtual Dimension (VD) procedure is used to analyze Hyperspectral Image (HIS) treatment-data in order to estimate the abundance of mineral components of a mining sample. Hyperspectral images coming from reflectance spectra (NIR region) are pre-treated using Standard Normal Variance (SNV) and Minimum Noise Fraction (MNF) methodologies. The endmember components are identified by the Simplex Growing Algorithm (SVG) and after adjusted to the reflectance spectra of reference-databases using Simulated Annealing (SA) methodology. The obtained abundance of minerals of the sample studied is very near to the ones obtained using XRD with a total relative error of 2%.

Keywords: hyperspectral imaging, minimum noise fraction, MNF, simplex growing algorithm, SGA, standard normal variance, SNV, virtual dimension, XRD

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Authors: Joshua N. Edokpayi, John O. Odiyo, Patience P. Shikwambana

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Water is a very rare natural resource in South Africa. Ga-Selati River is used for both domestic and industrial purposes. This study was carried out in order to assess the quality of Ga-Selati River in a mining area of Limpopo Province-Phalaborwa. The pH, Electrical Conductivity (EC) and Total Dissolved Solids (TDS) were determined using a Crinson multimeter while turbidity was measured using a Labcon Turbidimeter. The concentrations of Al, Ca, Cd, Cr, Fe, K, Mg, Mn, Na and Pb were analysed in triplicate using a Varian 520 flame atomic absorption spectrometer (AAS) supplied by PerkinElmer, after acid digestion with nitric acid in a fume cupboard. The average pH of the river from eight different sampling sites was 8.00 and 9.38 in wet and dry season respectively. Higher EC values were determined in the dry season (138.7 mS/m) than in the wet season (96.93 mS/m). Similarly, TDS values were higher in dry (929.29 mg/L) than in the wet season (640.72 mg/L) season. These values exceeded the recommended guideline of South Africa Department of Water Affairs and Forestry (DWAF) for domestic water use (70 mS/m) and that of the World Health Organization (WHO) (600 mS/m), respectively. Turbidity varied between 1.78-5.20 and 0.95-2.37 NTU in both wet and dry seasons. Total hardness of 312.50 mg/L and 297.75 mg/L as the concentration of CaCO3 was computed for the river in both the wet and the dry seasons and the river water was categorised as very hard. Mean concentration of the metals studied in both the wet and the dry seasons are: Na (94.06 mg/L and 196.3 mg/L), K (11.79 mg/L and 13.62 mg/L), Ca (45.60 mg/L and 41.30 mg/L), Mg (48.41 mg/L and 44.71 mg/L), Al (0.31 mg/L and 0.38 mg/L), Cd (0.01 mg/L and 0.01 mg/L), Cr (0.02 mg/L and 0.09 mg/L), Pb (0.05 mg/L and 0.06 mg/L), Mn (0.31 mg/L and 0.11 mg/L) and Fe (0.76 mg/L and 0.69 mg/L). Results from this study reveal that most of the metals were present in concentrations higher than the recommended guidelines of DWAF and WHO for domestic use and the protection of aquatic life.

Keywords: contamination, mining activities, surface water, trace metals

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Authors: Anida Causevic-Ramosevac, Sabina Semiz

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The aim of this study was to investigate the association of four single nucleotide polymorphisms (SNPs) - rs673548, rs693 in ApoB gene, rs1800775 in CETP gene and rs4846914 in GALNT2 gene with parameters of type 2 diabetes (T2D) and diabetic dyslipidemia in the population of Bosnia and Herzegovina (BH). Materials and methods: Our study involved 352 patients with T2D and 156 healthy subjects. Biochemical and anthropometric parameters were measured in all participants. DNA was extracted from the peripheral blood for the purpose of genetic testing. Polymorphisms in ApoB (rs673548, rs693), CETP (rs1800775) and GALNT2 (rs4846914) genes were analyzed by using Sequenom IPLEX platform. Results: Our results demonstrated significant associations for rs180075 polymorphism in CETP gene with levels of fasting insulin (p = 0.020; p = 0.027; p = 0.044), triglycerides (p = 0.046) and ALT (p = 0.031) activity in control group. In group of diabetic patients, results showed a significant association of rs673548 in ApoB gene with levels of fasting insulin (p = 0.008), HOMA-IR (p = 0.013), VLDL-C (p = 0.037) and CRP (p = 0.029) and rs693 in ApoB gene with BMI (p = 0.025), systolic blood pressure (p = 0.027), fasting insulin (p = 0.037) and HOMA-IR (p = 0.023) levels. Significant associations were also observed for rs1800775 in CETP gene with triglyceride (p = 0.023) levels and rs4846914 in GALNT2 gene with HbA1C (p = 0.013) and triglyceride (p = 0.043) levels. Conclusion: In conclusion, this is the first study that examined the impact of variations of candidate genes on a wide range of metabolic parameters in BH population. Our results suggest an association of variations of ApoB, CETP and GALNT2 genes with specific markers of T2D and dyslipidemia. Further studies would be needed in order to confirm these genetic effects in other ethnic groups as well.

Keywords: ApoB, CETP, dyslipidemia, GALNT2, type 2 diabetes

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Authors: Rabia Faridi, Rizwana Maqbool, Umara Sahar Rana, Zaheer Ahmad

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Climate change impacts agriculture, notably in Germany, where spring faba beans predominate. However, improved winter hardiness aligns with milder winters, enabling autumn-sown varieties. Genetic resistance to Ascochyta blight is vital for crop integration. Traditional breeding faces challenges due to complex inheritance. This study assessed 224 homozygous faba bean lines for Ascochyta resistance traits. To achieve h²>70%, 12 replicates were required (realized h²=87%). Genetic variation and strong trait correlations were observed. Five lines outperformed 29H, while three were highly susceptible. A genome-wide association study (GWAS) with 188 inbred lines and 2058 markers, including 17 guide SNP markers, identified 12 markers associated with resistance traits, potentially indicating new resistance genes. One guide marker (Vf-Mt1g014230-001) on chromosome III validated a known QTL. The guided marker approach complemented GWAS, facilitating marker-assisted selection for Ascochyta resistance. The Göttingen Winter Bean Population offers promise for resistance breeding.

Keywords: genome wide association studies, marker assisted breeding, faba bean, ascochyta blight

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Chayaporn Kaensar

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Recently, Job Recommender Systems have gained much attention in industries since they solve the problem of information overload on the recruiting website. Therefore, we proposed Extended Personalized Job System that has the capability of providing the appropriate jobs for job seeker and recommending some suitable information for them using Data Mining Techniques and Dynamic User Profile. On the other hands, company can also interact to the system for publishing and updating job information. This system have emerged and supported various platforms such as web application and android mobile application. In this paper, User profiles, Implicit User Action, User Feedback, and Clustering Techniques in WEKA libraries have gained attention and implemented for this application. In additions, open source tools like Yii Web Application Framework, Bootstrap Front End Framework and Android Mobile Technology were also applied.

Keywords: recommendation, user profile, data mining, web and mobile technology

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Authors: T. Nguyen, H. Rennie, S. Vallance, M. Mackay

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Municipal Associations, also called Unions, Leagues or Federations of municipalities have been established worldwide to represent the interests and needs of urban governments in the face of increasing urban issues. In 2008, the Association of Cities of Vietnam (ACVN) joined the Asian Coalition of Community Action Program (ACCA program) and introduced the community-based upgrading approach to help Vietnamese cities to address urban upgrading issues. While this community-based upgrading approach has only been implemented in a small number of Vietnamese cities and its replication has faced certain challenges, it is worthy to explore insights on how the Association of cities of Vietnam played its role in implementing some reportedly successful projects. This paper responds to this inquiry and presents results extracted from the author’s PhD study that sets out with a general objective to critically examine how social capital dimensions (i.e., bonding, bridging and linking) were formed, mobilized and maintained in a local collective and community-based upgrading process. Methodologically, the study utilized the given general categorization of bonding, bridging and linking capitals to explore and confirm how social capital operated in the real context of a community-based upgrading process, particularly in the context of Vietnam. To do this, the study conducted two exploratory and qualitative case studies of housing projects in Friendship neighbourhood (Vinh city) and Binh Dong neighbourhood (Tan An city). This paper presents the findings of the Friendship neighbourhood case study, focusing on the role of the Vietnamese municipal association in forming, mobilizing and maintaining bonding, bridging and linking capital for a community-based upgrading process. The findings highlight the essential but uncertain role of ACVN - the organization that has a hybrid legitimacy status - in such a process. The results improve our understanding both practically and theoretically. Practically, the results offer insights into the performance of a municipal association operating in a transitioning socio-political context of Vietnam. Theoretically, the paper questions the necessity of categorizing social capital dimensions (i.e., bonding, bridging and linking) by suggesting a holistic approach of looking at social capital for urban governance issues within the Vietnamese context and perhaps elsewhere.

Keywords: bonding capital, bridging capital, municipal association, linking capital, social capital, housing upgrading

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Authors: Marieta Safta

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The separation and balance of state powers constitute the basis of the rule of law. Observance of this principle requires framing of public authorities within the limits of competence established by the Constitution and the law, as well as loyal cooperation between them. From this perspective, the attribution of the constitutional courts for settling legal conflicts of a constitutional nature is an important tool for correcting the tendencies of violation of these limits, as well as for identifying solutions for situations that do not find an explicit regulation in the constitutional texts. The present study analyzes the jurisprudence of the Constitutional Court of Romania in the field of legal conflicts of a constitutional nature, revealing, together with the presentation of conflict situations, the vulnerabilities of the constitutional reference texts. It is also highlighted the role of the constitutional courts in the evolution of constitutional law institutions, even in terms of defining and redefining the regime of the forms of government. The conclusion of the study, beyond the subject of legal conflicts of a constitutional nature, bears on the necessity, even more so in this matter, of the certainty of jurisdictional interpretation. This certainty cannot be achieved as long as the interpretation is not authoritative; consequently, the assurance of the effectiveness of constitutional justice constitute a key issue of the rule of law.

Keywords: legal conflicts of constitutional nature, the Constitutional Court of Romania, the separation and balance of powers in the state, the effectiveness of constitutional justice

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Authors: Kyung Bae Park, Sung Ho Ha

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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

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Authors: Gebeyaw Molla Wondim, Damen Haile Mariam, Wubegzier Mekonnen, Catherine Arsenault

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Introduction: Maternal depression is a common psychological disorder that mostly occurs during pregnancy and after childbirth. It affects approximately one in four women worldwide. There is inconsistent evidence regarding the association between anemia and maternal depression. The objective of this systematic review was to examine the association between anemia and depression during pregnancy. Method: A comprehensive search of articles published before March 8, 2024, was conducted in seven databases such as PubMed, Scopus, Web of Science, PsycINFO, CINAHL, Cochrane Library, and Google Scholar. The Boolean operators “AND” or “OR” and “NOT” were used to connect the MeSH terms and keywords. Rayyan software was used to screen articles for final retrieval, and the PRISMA diagram was used to show the article selection process. Data extraction and risk bias assessment were done by two reviewers independently. JBI critical appraisal tool was used to assess the methodological quality of the retrieved articles. Heterogenicity was assessed through visual inspection of the extracted result, and narrative analysis was used to synthesize the result. Result: A total of 2,413 articles were obtained from seven electronic databases. Among these articles, a total of 2,398 were removed due to duplication (702 articles), by title and abstract selection criteria (1,678 articles), and by full-text review (18 articles). Finally, in this systematic review, 15 articles with a total of 628,781 pregnant women were included: seven articles were cohort studies, two were case-control, and six studies were cross-sectional. All included studies were published between 2013 and 2022. Studies conducted in the United States, South Korea, Finland, and one in South India found no significant association between anemia and maternal depression during pregnancy. On the other hand, studies conducted in Australia, Canada, Finland, Israel, Turkey, Vietnam, Ethiopia, and South India showed a significant association between anemia and depression during pregnancy. Conclusion: The overall finding of the systematic review shows the burden of anemia and antenatal depression is much higher among pregnant women in developing countries. Around three-fourths of the studies show that anemia is positively associated with antenatal depression. Almost all studies conducted in LMICs show anemia positively associated with antenatal depression.

Keywords: pregnant, women, anemia, depression

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

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Authors: J. Vinay , Kusumbati Besra, Niharika Pattnaik, Shivaram Prasad Singh, Manjusha Dixit

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Gallbladder cancer (GBC) is rare but highly malignant cancer; its prevalence is more in certain geographical regions and ethnic groups, which include the Northern and Eastern states of India. Previous studies in India have reported genetic predisposition as one of the risk factors in GBC pathogenesis. Although the matrix metalloproteinase-14 (MMP14) is a well-known modulator of the tumor microenvironment and tumorigenesis and TCGA data also suggests its upregulation yet, its role in the genetic predisposition for GBC is completely unknown. We elucidated the role of MMP14 promoter variants as genetic risk factors and their implications in expression modulation. We screened MMP14 promoter variants association with GBC using Sanger’s sequencing in approximately 300 GBC and 300 control subjects and 26 GBC tissue samples of Indian ethnicity. The immunohistochemistry was used to check the MMP14 protein expression in GBC tissue samples. The role of promoter variants on expression levels was elucidated using a luciferase reporter assay. The variants rs1004030 (p-value = 0.0001) and rs1003349 (p-value = 0.0008) were significantly associated with gallbladder cancer. The luciferase assay in two different cell lines, HEK-293 (p = 0.0006) and TGBC1TKB (p = 0.0036) showed a significant increase in relative luciferase activity in the presence of risk alleles for both the single nucleotide polymorphisms (SNPs). Similarly, genotype-phenotype correlation in patients samples confirmed that the presence of risk alleles at rs1004030 and rs1003349 increased MMP14 expression. Overall, this study unravels the genetic association of MMP14 promoter variants with gallbladder cancer, which may contribute to pathogenesis by increasing its expression.

Keywords: gallbladder cancer, matrix metalloproteinase-14, single nucleotide polymorphism, case control study, genetic association study

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

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Many global firms and corporations derive new technology and opportunity by identifying vacant technology from patent analysis. However, previous studies failed to focus on technologies that promised continuous growth in industrial fields. Most studies that derive new technology opportunities do not test practical effectiveness. Since previous studies depended on expert judgment, it became costly and time-consuming to evaluate new technologies based on patent analysis. Therefore, research suggests a quantitative and systematic approach to technology evaluation indicators by using patent data to and from customer communities. The first step involves collecting two types of data. The data is used to construct evaluation indicators and apply these indicators to the evaluation of new technologies. This type of data mining allows a new method of technology evaluation and better predictor of how new technologies are adopted.

Keywords: data mining, evaluating new technology, technology opportunity, patent analysis

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Authors: Esther Yin-Nei Cho

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There is inconsistency among studies about whether there is an association between poverty and the subjective wellbeing of children. Some have found a positive association, though its magnitude could be limited, others have shown no association. One possible explanation for this inconsistency is that household income, an often-adopted measure of child poverty, may not accurately and stably reflect the actual life experience of children. Some studies have suggested, however, that material deprivation covering various dimensions of children’s lives could be a better measure of child poverty. Another possible explanation for the inconsistency is that the link between poverty and subjective wellbeing of children may not be that straightforward, as there could be underlying mechanisms, such as mediation and moderation, influencing its direction or strength. While a mediator refers to the mechanism through which an independent variable affects a dependent variable, a moderator changes the direction or strength of the relationship between an independent variable and a dependent variable. As suggested by empirical evidence, family relationships and friendships could be potential mediators or moderators of the link between poverty and subjective well-being: poverty affects relationships; relationships are an important element in children’s subjective well-being; and economic status affects child outcomes, though not necessarily subjective wellbeing, through relationships. Since the potential links have not been adequately understood, this study fills this gap by examining the possible role of family relationships and friendships as mediators or moderators between poverty (using child-derived material deprivation as measure) and the subjective wellbeing of children. Improving subjective wellbeing is increasingly considered as a policy goal. The finding of no or a limited association between poverty and subjective wellbeing of children could be a justification for less effort to improve poverty in this regard. But if the observed magnitude of that association is due to some underlying mechanisms at work, the effect of poverty may be underestimated and the potentially useful strategies that take into account both poverty and other mediators or moderators for improving children’s subjective well-being may be overlooked. Multiple mediation, and multiple moderation models, based on regression analyses, are performed to a sample of approximately 1,600 children, who are aged 10 to 15, from the wellbeing survey conducted by The Children’s Society in England from 2010 to 2011. Results show that the effect of children’s material deprivation on their subjective well-being is mediated by their family relationships and friendships. Moreover, family relationships are a significant moderator. It is found that the negative impact of child deprivation on subjective wellbeing could be exacerbated if family relationships are not going well, while good family relationships may prevent the further decline in subjective well-being. Policy implications of the findings are discussed. In particular, policy measures that focus on strengthening the family relationships or nurturing home environment through supporting household’s economic security and parental time with children could promote the subjective wellbeing of children.

Keywords: child poverty, mediation, moderation, subjective well-being of children

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Authors: Syed M. Shahid, Rozeena Shaikh, Syeda N. Nawab, Abid Azhar

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Diabetes mellitus (DM) is a prevalent non-communicable disease worldwide. DM may lead to many vascular complications like hypertension, nephropathy, retinopathy, neuropathy and foot infections. Pathogenesis of diabetic nephropathy (DN) is implicated by the polymorphisms in genes encoding the specific components of renin angiotensin aldosterone system (RAAS) which include angiotensinogen (AGT), angiotensin-II receptor and angiotensin converting enzyme (ACE) genes. This study was designed to explore the possible association of AG (M268T) polymorphism in the patients of diabetes and nephropathy in Pakistan. Study subjects included 100 controls, 260 diabetic patients without renal insufficiency and 190 diabetic nephropathy patients with persistent albuminuria. Fasting blood samples were collected from all the subjects after getting institutional ethical approval and informed consent. The biochemical estimations, PCR amplification and direct sequencing for the specific region of AGT gene was carried out. A significantly high frequency of TT genotype and T allele of AGT (M268T) was observed in the patients of diabetes with nephropathy as compared to controls and diabetic patients without any known renal impairment. The TT genotype and T allele of AGT (M268T) polymorphism may be considered as a genetic risk factor for the development and progression of nephropathy in diabetes. Further cross sectional population studies would be of help to establish and confirm the observed possible association of AGT gene variations with development of nephropathy in diabetes.

Keywords: RAAS, AGT (M268T), diabetes, nephropathy

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Authors: Nor Hafizah Anuar, M. Gul Akdeniz

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This paper attempted on emphasize on the station buildings façade elements. Station buildings were essential part of the transportation that reflected the technology. Comparative analysis on architectural styles will also be made between the railway station buildings of Malaysia and any railway station buildings which have similarities. The Malay Peninsula which is strategically situated between the Straits of Malacca and the South China Sea makes it an ideal location for trade. Malacca became an important trading port whereby merchants from around the world stopover to exchange various products. The Portuguese ruled Malacca for 130 years (1511–1641) and for the next century and a half (1641–1824), the Dutch endeavoured to maintain an economic monopoly along the coasts of Malaya. Malacca came permanently under British rule under the Anglo-Dutch Treaty, 1824. Up to Malaysian independence in 1957, Malaya saw a great influx of Chinese and Indian migrants as workers to support its growing industrial needs facilitated by the British. The growing tin ore mining and rubber industry resulted as the reason of the development of the railways as urgency to transport it from one place to another. The existence of railway transportation becomes more significant when the city started to bloom and the British started to build grandeur buildings that have different functions; administrative buildings, town and city halls, railway stations, public works department, courts, and post offices.

Keywords: Malaysia, station building, architectural styles, facade elements

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Atje Setiawan Abdullah, Budi Nurani Ruchjana, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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Ethnoscience is used to see the culture with a scientific perspective, which may help to understand how people develop various forms of knowledge and belief, initially focusing on the ecology and history of the contributions that have been there. One of the areas studied in ethnoscience is etno-informatics, is the application of informatics in the culture. In this study the science of informatics used is data mining, a process to automatically extract knowledge from large databases, to obtain interesting patterns in order to obtain a knowledge. While the application of culture described by naming database village on the island of Java were obtained from Geographic Indonesia Information Agency (BIG), 2014. The purpose of this study is; first, to classify the naming of the village on the island of Java based on the structure of the word naming the village, including the prefix of the word, syllable contained, and complete word. Second to classify the meaning of naming the village based on specific categories, as well as its role in the community behavioral characteristics. Third, how to visualize the naming of the village to a map location, to see the similarity of naming villages in each province. In this research we have developed two theorems, i.e theorems area as a result of research studies have collected intersection naming villages in each province on the island of Java, and the composition of the wedge theorem sets the provinces in Java is used to view the peculiarities of a location study. The methodology in this study base on the method of Knowledge Discovery in Database (KDD) on data mining, the process includes preprocessing, data mining and post processing. The results showed that the Java community prioritizes merit in running his life, always working hard to achieve a more prosperous life, and love as well as water and environmental sustainment. Naming villages in each location adjacent province has a high degree of similarity, and influence each other. Cultural similarities in the province of Central Java, East Java and West Java-Banten have a high similarity, whereas in Jakarta-Yogyakarta has a low similarity. This research resulted in the cultural character of communities within the meaning of the naming of the village on the island of Java, this character is expected to serve as a guide in the behavior of people's daily life on the island of Java.

Keywords: ethnoscience, ethno-informatics, data mining, clustering, Java island culture

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Authors: S. I. Enem, S. I. Oboegbulem

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Objective: The most frequently implicated E. coli serotype causing haemorrhagic colitis and haemorrhagic uraemic syndrome (HUS) is VTEC 0157. However, non-O157 VTEC is now known to be as prevalent as VETC O157 infection (or even more) in most parts of the world. The objective of the study was to establish the occurrence of non-O157 VTEC serotypes in cattle in the Federal Capital Territory (FCT) Abuja, Nigeria. The level of significance of the infection with sex, age and season were also tested. Methods: The study was carried out in the FCT, Abuja, Nigeria which is located between latitude 8o and 90 25` North of the equator and longitude 60 45` and 7045` East of the Greenwich meridian. The cross sectional epidemiological method and multi-staged sampling technique were used in this study. Samples were collected from the freshly voided faeces of both apparently healthy and diarrhoeic cattle in selected abattoirs and cattle herds. Enriched samples were analyzed bacteriologically and biochemically after which they were characterised using commercially prepared latex agglutination test kits. Results: A total of 718 faecal samples from cattle were analyzed for the presence of VTEC non-O157. Thirty eight (5.23%) were positive for non-O157. There was no significant association (p > 0.05) between sex and infection with non-O157 VTEC in cattle. There was a significant association (P < 0.05) between age and infection with non-O157 VTEC in cattle. Calves were more associated than the adults. There was also a significant association (P < 0.05) between season and infection with non-O157 VTEC in cattle. The dry season was more associated than the wet season. Conclusion: The study established the occurrence and prevalence of non-O157 VTEC in cattle in FCT, Abuja, Nigeria. As a major food animal in Nigeria, infection in cattle provides an epidemiological causal association to the infection in humans. The result showed that warmer seasons (dry season) stimulate the presence of VTEC infection in animals and thus, as a consequence, increases the number of human cases. The prevalence was also higher in younger calves (< 6 months) probably as a result of undeveloped immune system.

Keywords: prevalence, distribution, Verocytotoxigenic escherichia coli (VTEC), non-O157 serotypes, cattle

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Authors: Minami Ito, Akihiro Iijima

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On March 11, 2011, the Great East Japan Earthquake occurred off the coast of Sanriku, Japan. It is important to build a sustainable society through the reconstruction process rather than simply restoring the infrastructure. To compare the goals of reconstruction plans of quake-stricken municipalities, Japanese language morphological analysis was performed by using text mining techniques. Frequently-used nouns were sorted into four main categories of “life”, “disaster prevention”, “economy”, and “harmony with environment”. Because Soma City is affected by nuclear accident, sentences tagged to “harmony with environment” tended to be frequent compared to the other municipalities. Results from cluster analysis and principle component analysis clearly indicated that the local government reinforces the efforts to reduce risks from radiation exposure as a top priority.

Keywords: eco-friendly reconstruction, harmony with environment, decontamination, nuclear disaster

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Anshar Ajatasatru

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The decline of coal prices over past years have been significantly increasing the awareness of effective mining operation. A viable step must be undertaken in becoming more cost competitive while striving for best mining practice especially at Melak Coal Mine in East Kalimantan, Indonesia. This paper aims to show how effective dozer push measurement method can be implemented as it is controlled by contract rate on the unit basis of USD ($) per bcm. The method emerges from an idea of daily dozer push activity that continually shifts the overburden until final target design by mine planning. Volume calculation is then performed by calculating volume of each time overburden is removed within determined distance using cut and fill method from a high precision GNSS system which is applied into dozer as a guidance to ensure the optimum result of overburden removal. Accumulation of daily to weekly dozer push volume is found 95 bcm which is multiplied by average sell rate of $ 0,95, thus the amount monthly revenue is $ 90,25. Furthermore, the payment mechanism is then based on push distance and push grade. The push distance interval will determine the rates that vary from $ 0,9 - $ 2,69 per bcm and are influenced by certain push slope grade from -25% until +25%. The amount payable rates for dozer push operation shall be specifically following currency adjustment and is to be added to the monthly overburden volume claim, therefore, the sell rate of overburden volume per bcm may fluctuate depends on the real time exchange rate of Jakarta Interbank Spot Dollar Rate (JISDOR). The result indicates that dozer push measurement can be one of the surface mining alternative since it has enabled to refine method of work, operating cost and productivity improvement apart from exposing risk of low rented equipment performance. In addition, payment mechanism of contract rate by dozer push operation scheduling will ultimately deliver clients by almost 45% cost reduction in the form of low and consistent cost.

Keywords: contract rate, cut-fill method, dozer push, overburden volume

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Authors: Xiaohua Jing

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Efficient extraction for separation of V and Cr in the leaching/aqueous solution is essential to the reuse of V and Cr in the V-Cr slag. Trioctylamine, a common tertiary amine extractant, with some good characters (e.g., weak base, insoluble in water and good stability) different from N1923, was investigated in this paper. The separation factor of Cr and V can be reached to 230.71 when initial pH of the aqueous solution is 0.5, so trioctylamine can be used for extracting Cr from the leaching/aqueous solution contained V and Cr. The highest extraction percentages of Cr and V were 98.73% and 90.22% when the initial pH values were 0.5 and 1.5, respectively. Via FT-IR spectra of loaded organic phase and trioctylamine, the hydrogen bond association mechanism of extracting V and Cr was investigated, which was the same with the way of extracting the two metals with primary amine N1923.

Keywords: selective extraction, trioctylamine, V and Cr, separation factor, hydrogen bond association

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Authors: Hanan Azzam1, Nashwa Abousamra1, Amany Mansour1, Yaser Abd El-dayem2, , Solafa Elsharawy1

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Background: Inherited thrombophilias are a heterogenous group of conditions which have been implicated in a variety of pregnancy complications. More recently, deficiency of protein Z (PZ) has been liked to pregnancy complications, including preterm delivery. Aim: We designed this study to evaluate the association of inherited thrombophilias including [Protein C (PC), Protein S (PS), Anti thrombin III (ATIII) deficiency and activated protein C (APC) resistance] and protein Z deficiency with a variety of pregnancy complications. Patients and Methods: 60 women with different pregnancy complications, including 20 patients with preeclampsia, 20 patients with intrauterine growth resistance (IUGR), and 20 patients with intrauterine fetal death (IUFD), in addition to 30 healthy pregnant women were recruited for the present study. PC and free PS antigen, ATIII activity, modified functional APC-resistance, and PZ levels were determined. Results: There was no significant association between inherited thrombophilias and complicated pregnancies as regards PC deficiency (p=1.0), AT III and PS deficiency (p=0.312), and APC-resistance (P=0.083). PZ was significantly associated with complicated pregnancies (p=0.012). Patients with protein Z levels below 1.5 µg/ml were considered deficient. Accordingly, we demonstrated protein Z deficiency in 30% of complicated pregnancies (RR 6.0, 95% CI 1.29-27.90;p=0.022), 20% of preeclampsia (RR 3.5, 95% CI 0.57 – 21.28; P = 0.174), 40% of IUGR (RR 9.3 95% CI 1.72-50.61; P = 0.010) and 30% of IUFD (RR 6, 95% CI 1.07 – 33.64; P = 0.042). Conclusions: These findings indicate the absence of association of inherited thrombophilias, including PC, PS, AT III deficiency, and APC resistance with pregnancy complications. However, PZ deficiency is associated with increased risk of pregnancy complications, especially intrauterine growth restriction and intrauterine fetal death.

Keywords: protein C, protein S, thrombophelia, pregnancy, protein Z

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Giovana Longo-Silva, Risia Cristina Egito de Menezes, Renan Serenini, Márcia de Oliveira Lima, Júlia Souza de Melo, Larissa de Lima Soares

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Introduction: Sleep duration and quality have been increasingly recognized as important factors affecting overall health and well-being, including their potential impact on body weight and composition. Previous research has shown inconsistent results regarding the association between sleep patterns and body mass index (BMI), particularly among diverse populations such as Brazilian adults. Understanding these relationships is crucial for developing targeted interventions to address obesity and related health issues. Objective: This study aimed to investigate the association between sleep duration, insomnia, and BMI among Brazilian adults using data from a large national survey focused on chronic nutrition and sleep habits. Materials and Methods: The study included 2050 participants from a population-based virtual survey. BMI was calculated using self-reported weight and height measurements. Participants also reported usual bedtime and wake time on weekdays and weekends and whether they experienced symptoms of insomnia. The average sleep duration across the entire week was calculated as follows: [(5×sleep duration on weekdays) + (2×sleep duration on weekends)]/7. Linear regression analyses were conducted to assess the association between sleep duration, insomnia, and BMI, adjusting for potential confounding factors, including age, sex, marital status, physical exercise duration, and diet quality. Results: After adjusting for confounding variables, the study found that BMI decreased by 0.19 kg/m² for each additional hour of sleep duration (95% CI = -0.37, -0.02; P = 0.03). Conversely, individuals with insomnia had a higher BMI, with an increase of 0.75 kg/m² (95% CI = 0.28, 1.22; P = 0.002) compared to those without insomnia. Conclusions: The findings suggest a significant association between sleep duration, insomnia, and BMI among Brazilian adults. Longer sleep duration was associated with lower BMI, while insomnia was associated with higher BMI. These results underscore the importance of considering sleep patterns in strategies aimed at preventing and managing obesity in this population. Further research is needed to explore the underlying mechanisms and potential interventions targeting sleep-related factors to promote healthier body weight outcomes.

Keywords: sleep, obesity, chronobiology, nutrition

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Authors: Chong Zhang, Guoming Tang, Bin Ge, Jiuyang Tang

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With the fast growing road traffic and increasingly severe traffic congestion, more and more citizens choose to use the public transportation for daily travelling. Meanwhile, the shared bike provides a convenient option for the first and last mile to the public transit. As of 2016, over one thousand cities around the world have deployed the bike-sharing system. The combination of these two transportations have stimulated the development of each other and made significant contribution to the reduction of carbon footprint. A lot of work has been done on mining the riding behaviors in various bike-sharing systems. Most of them, however, treated the bike-sharing system as an isolated system and thus their results provide little reference for the public transit construction and optimization. In this work, we treat the bike-sharing and public transit as a whole and investigate the customers’ bike-and-ride behaviors. Specifically, we develop a spatio-temporal traffic delivery model to study the riding patterns between the two transportation systems and explore the traffic characteristics (e.g., distributions of customer arrival/departure and traffic peak hours) from the time and space dimensions. During the model construction and evaluation, we make use of large open datasets from real-world bike-sharing systems (the CitiBike in New York, GoBike in San Francisco and BIXI in Montreal) along with corresponding public transit information. The developed two-dimension traffic model, as well as the mined bike-and-ride behaviors, can provide great help to the deployment of next-generation intelligent transportation systems.

Keywords: riding pattern mining, bike-sharing system, public transportation, bike-and-ride behavior

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Authors: Reiner-Ace P. Mateo, Vince Paolo F. Obille

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The traditional method of classifying the potential mineral resources requires a significant amount of time and money. In this paper, an alternative way to classify potential mineral resources with GIS application in Surigao del Sur. The three (3) analog map data inputs integrated to GIS are geologic map, topographic map, and land cover/vegetation map. The indicators used in the classification of potential nickel laterite integrated from the analog map data inputs are a geologic indicator, which is the presence of ultramafic rock from the geologic map; slope indicator and the presence of plateau edges from the topographic map; areas of forest land, grassland, and shrublands from the land cover/vegetation map. The potential mineral of the area was classified from low up to very high potential. The produced mineral potential classification map of Surigao del Sur has an estimated 4.63% low nickel laterite potential, 42.15% medium nickel laterite potential, 43.34% high nickel laterite potential, and 9.88% very high nickel laterite from its ultramafic terrains. For the validation of the produced map, it was compared with known occurrences of nickel laterite in the area using a nickel mining tenement map from the area with the application of remote sensing. Three (3) prominent nickel mining companies were delineated in the study area. The generated potential classification map of nickel-laterite in Surigao Del Sur may be of aid to the mining companies which are currently in the exploration phase in the study area. Also, the currently operating nickel mines in the study area can help to validate the reliability of the mineral classification map produced.

Keywords: mineral potential classification, nickel laterites, GIS, remote sensing, Surigao del Sur

Procedia PDF Downloads 116