Search results for: frequent item sets mining
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3698

Search results for: frequent item sets mining

3158 Use of Quasi-3D Inversion of VES Data Based on Lateral Constraints to Characterize the Aquifer and Mining Sites of an Area Located in the North-East of Figuil, North Cameroon

Authors: Fofie Kokea Ariane Darolle, Gouet Daniel Hervé, Koumetio Fidèle, Yemele David

Abstract:

The electrical resistivity method is successfully used in this paper in order to have a clearer picture of the subsurface of the North-East ofFiguil in northern Cameroon. It is worth noting that this method is most often used when the objective of the study is to image the shallow subsoils by considering them as a set of stratified ground layers. The problem to be solved is very often environmental, and in this case, it is necessary to perform an inversion of the data in order to have a complete and accurate picture of the parameters of the said layers. In the case of this work, thirty-three (33) Schlumberger VES have been carried out on an irregular grid to investigate the subsurface of the study area. The 1D inversion applied as a preliminary modeling tool and in correlation with the mechanical drillings results indicates a complex subsurface lithology distribution mainly consisting of marbles and schists. Moreover, the quasi-3D inversion with lateral constraint shows that the misfit between the observed field data and the model response is quite good and acceptable with a value low than 10%. The method also reveals existence of two water bearing in the considered area. The first is the schist or weathering aquifer (unsuitable), and the other is the marble or the fracturing aquifer (suitable). The final quasi 3D inversion results and geological models indicate proper sites for groundwaters prospecting and for mining exploitation, thus allowing the economic development of the study area.

Keywords: electrical resistivity method, 1D inversion, quasi 3D inversion, groundwaters, mining

Procedia PDF Downloads 157
3157 Development and Evaluation of a Psychological Adjustment and Adaptation Status Scale for Breast Cancer Survivors

Authors: Jing Chen, Jun-E Liu, Peng Yue

Abstract:

Objective: The objective of this study was to develop a psychological adjustment and adaptation status scale for breast cancer survivors, and to examine the reliability and validity of the scale. Method: 37 breast cancer survivors were recruited in qualitative research; a five-subject theoretical framework and an item pool of 150 items of the scale were derived from the interview data. In order to evaluate and select items and reach a preliminary validity and reliability for the original scale, the suggestions of study group members, experts and breast cancer survivors were taken, and statistical methods were used step by step in a sample of 457 breast cancer survivors. Results: An original 24-item scale was developed. The five dimensions “domestic affections”, “interpersonal relationship”, “attitude of life”, “health awareness”, “self-control/self-efficacy” explained 58.053% of the total variance. The content validity was assessed by experts, the CVI was 0.92. The construct validity was examined in a sample of 264 breast cancer survivors. The fitting indexes of confirmatory factor analysis (CFA) showed good fitting of the five dimensions model. The criterion-related validity of the total scale with PTGI was satisfactory (r=0.564, p<0.001). The internal consistency reliability and test-retest reliability were tested. Cronbach’s alpha value (0.911) showed a good internal consistency reliability, and the intraclass correlation coefficient (ICC=0.925, p<0.001) showed a satisfactory test-retest reliability. Conclusions: The scale was brief and easy to understand, was suitable for breast cancer patients whose physical strength and energy were limited.

Keywords: breast cancer survivors, rehabilitation, psychological adaption and adjustment, development of scale

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3156 Identifying Concerned Citizen Communication Style During the State Parliamentary Elections in Bavaria

Authors: Volker Mittendorf, Andre Schmale

Abstract:

In this case study, we want to explore the Twitter-use of candidates during the state parliamentary elections-year 2018 in Bavaria, Germany. This paper focusses on the seven parties that probably entered the parliament. Against this background, the paper classifies the use of language as populism which itself is considered as a political communication style. First, we determine the election campaigns which started in the years 2017 on Twitter, after that we categorize the posting times of the different direct candidates in order to derive ideal types from our empirical data. Second, we have done the exploration based on the dictionary of concerned citizens which contains German political language of the right and the far right. According to that, we are analyzing the corpus with methods of text mining and social network analysis, and afterwards we display the results in a network of words of concerned citizen communication style (CCCS).

Keywords: populism, communication style, election, text mining, social media

Procedia PDF Downloads 149
3155 Sexting Phenomenon in Educational Settings: A Data Mining Approach

Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

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Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

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3154 Heart Failure Identification and Progression by Classifying Cardiac Patients

Authors: Muhammad Saqlain, Nazar Abbas Saqib, Muazzam A. Khan

Abstract:

Heart Failure (HF) has become the major health problem in our society. The prevalence of HF has increased as the patient’s ages and it is the major cause of the high mortality rate in adults. A successful identification and progression of HF can be helpful to reduce the individual and social burden from this syndrome. In this study, we use a real data set of cardiac patients to propose a classification model for the identification and progression of HF. The data set has divided into three age groups, namely young, adult, and old and then each age group have further classified into four classes according to patient’s current physical condition. Contemporary Data Mining classification algorithms have been applied to each individual class of every age group to identify the HF. Decision Tree (DT) gives the highest accuracy of 90% and outperform all other algorithms. Our model accurately diagnoses different stages of HF for each age group and it can be very useful for the early prediction of HF.

Keywords: decision tree, heart failure, data mining, classification model

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3153 Disaster Risk Reduction (DRR) through Harvesting Encosternum delegorguei Insect (Harurwa) in Nerumedzo, Bikita District, Zimbabwe

Authors: Mkhokheli Sithole, Brenda N. Muchapondwa

Abstract:

Food security is becoming a critical issue for people residing mainly in the rural areas where frequent droughts interrupt food production, reduce income, compromise the ability to save and erode livelihoods. This tends to increase the vulnerability of poor households to food and income insecurity, hence, malnutrition. There is an emerging need for DRR strategies to complement the existing rain fed crop production based livelihoods. One of such strategies employed by the community of Nerumedzo in Bikita district is the harvesting of Encosternum delegorguei insect. This article analyses the livelihood impacts of Encosternum delegorguei insect as a DRR strategy. The research used a combination of qualitative and quantitative approaches. The insect samples were tested in the laboratory for their nutritional composition while surveys were done on a sample of 40 community members. Participatory observations and 5 focus group discussions were also done. The results revealed that harvesting the Encosternum delegorguei insects provides a livelihood for the locals by complementing crop production thereby mitigating potential negative effects of frequent droughts. The insects are now a significant source of income to poor households in the community.

Keywords: disaster risk reduction, livelihoods, human, social sciences

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3152 Turbulent Flow Characteristics and Bed Morphology around Circular Bridge Pier

Authors: Pratik Acharya

Abstract:

Scour is the natural phenomenon brought about by erosive action of the flowing stream in alluvial channels. Frequent scouring around bridge piers may cause damage to the structures. In alluvial channels, a complex interaction between the streamflow and the bed particles results in scouring around piers. Thus, the study of characteristics of flow around piers can give sound knowledge about the scouring process. The present research has been done to investigate the turbulent flow characteristics around bridge piers and corresponding changes in bed morphology. Laboratory experiments were carried out in a tilting flume with a sand bed. The velocities around the pier are measured by Acoustic Doppler Velocimeter. Measurements show that at upstream of the pier velocity and Reynolds stresses are negative near the bed and near the free surface at downstream of the pier. At the downstream of the pier, Reynolds stresses changes rapidly due to the formation of wake vortices. Experimental results show that secondary currents are more predominant at the downstream of the pier. As the flowing stream hits the pier, the flow gets separated in the form of downflow along the face of the pier due to a strong pressure gradient and along the sides of the piers. Separation of flow around the pier leads to scour the bed material and develop the vortex. The downflow hits the bed and removes the bed material, which can be carried forward by the flow circulations along sides of the piers. Eroded bed material is deposited along the centerline at the rear side of the pier and produces hump in the downstream region. Initially, the rate of scouring is high and reduces gradually with increasing time. After a certain limit, equilibrium sets between the erosive capacity of the flowing stream and resistance to the motion by bed particles.

Keywords: acoustic doppler velocimeter, pier, Reynolds stress, scour depth, velocity

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3151 A Less Complexity Deep Learning Method for Drones Detection

Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

Abstract:

Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

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3150 Development and Testing of Health Literacy Scales for Chinese Primary and Secondary School Students

Authors: Jiayue Guo, Lili You

Abstract:

Background: Children and adolescent health are crucial for both personal well-being and the nation's future health landscape. Health Literacy (HL) is important in enabling adolescents to self-manage their health, a fundamental step towards health empowerment. However, there are limited tools for assessing HL among elementary and junior high school students. This study aims to construct and validate a test-based HL scale for Chinese students, offering a scientific reference for cross-cultural HL tool development. Methods: We conducted a cross-sectional online survey. Participants were recruited from a stratified cluster random sampling method, a total of 4189 Chinese in-school primary and secondary students. The development of the scale was completed by defining the concept of HL, establishing the item indicator system, screening items (7 health content dimensions), and evaluating reliability and validity. Delphi method expert consultation was used to screen items, the Rasch model was conducted for quality analysis, and Cronbach’s alpha coefficient was used to examine the internal consistency. Results: We developed four versions of the HL scale, each with a total score of 100, encompassing seven key health areas: hygiene, nutrition, physical activity, mental health, disease prevention, safety awareness, and digital health literacy. Each version measures four dimensions of health competencies: knowledge, skills, motivation, and behavior. After the second round of expert consultation, the average importance score of each item by experts is 4.5–5.0, and the coefficient of variation is 0.000–0.174. The knowledge and skills dimensions are judgment-based and multiple-choice questions, with the Rasch model confirming unidimensionality at a 5.7% residual variance. The behavioral and motivational dimensions, measured with scale-type items, demonstrated internal consistency via Cronbach's alpha and strong inter-item correlation with KMO values of 0.924 and 0.787, respectively. Bartlett's test of sphericity, with p-values <0.001, further substantiates the scale's reliability. Conclusions: The new test-based scale, designed to evaluate competencies within a multifaceted framework, aligns with current international adolescent literacy theories and China's health education policies, focusing not only on knowledge acquisition but also on the application of health-related thinking and behaviors. The scale can be used as a comprehensive tool for HL evaluation and a reference for other countries.

Keywords: adolescent health, Chinese, health literacy, rasch model, scale development

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3149 Sino-Africa Trade Ties: The Curse of African Minerals: Tweaking the Corporate Scorecard to Benefit the Mining Village Communities

Authors: Donald Ouko

Abstract:

For decades, Africa has been home to several foreign companies doing business in various sectors. In recent years, China has consistently positioned itself as a development partner powerhouse among African nations. However, this has not been felt as equally beneficial to the local communities where the partnerships bloom in extractives trading. This paper explores the impact of Chinese involvement in mining on the local communities in three African countries, the factors that enable the sector to thrive amid the impacts, and what could be done differently for the local communities to experience a different outcome. It suggests alternative terms of engagement that aim at transparency, accountability, and anti-corruption to ensure inclusive social and economic development, and sound governance both at state and corporate levels.

Keywords: law and society, social development, corporate governance, China-Africa ties, human rights, socio-economic development, accountability, transparency

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3148 Asia Pacific University of Technology and Innovation

Authors: Esther O. Adebitan, Florence Oyelade

Abstract:

The Millennium Development Goals (MDGs) was initiated by the UN member nations’ aspiration for the betterment of human life. It is expressed in a set of numerical ‎and time-bound targets. In more recent time, the aspiration is shifting away from just the achievement to the sustainability of achieved MDGs beyond the 2015 target. The main objective of this study was assessing how much the hotel industry within the Nigerian Federal Capital Territory (FCT) as a member of the global community is involved in the achievement of sustainable MDGs within the FCT. The study had two population groups consisting of 160 hotels and the communities where these are located. Stratified random sampling technique was adopted in selecting 60 hotels based on large, medium ‎and small hotels categorisation, while simple random sampling technique was used to elicit information from 30 residents of three of the hotels host communities. The study was guided by tree research questions and two hypotheses aimed to ascertain if hotels see the need to be involved in, and have policies in pursuit of achieving sustained MDGs, and to determine public opinion regarding hotels contribution towards the achievement of the MDGs in their communities. A 22 item questionnaire was designed ‎and administered to hotel managers while 11 item questionnaire was designed ‎and administered to hotels’ host communities. Frequency distribution and percentage as well as Chi-square were used to analyse data. Results showed no significant involvement of the hotel industry in achieving sustained MDGs in the FCT and that there was disconnect between the hotels and their immediate communities. The study recommended that hotels should, as part of their Corporate Social Responsibility pick at least one of the goals to work on in order to be involved in the attainment of enduring Millennium Development Goals.

Keywords: MDGs, hotels, FCT, host communities, corporate social responsibility

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3147 Successful Management of a Boy with Mild Persistent Asthma: A Longitudinal Case

Authors: A. Lubis, L. Setiawati, A. R. Setyoningrum, A. Suryawan, Irwanto

Abstract:

Asthma is a condition that causing chronic health problems in children. In addition to basic therapy against disease, we must try to reduce the impact of chronic health problems and also optimize their medical aspect of growth and development. A boy with mild asthma attack frequent episode did not showed any improvement with medical treatment and his asthma control test was 11. From radiologic examination he got hyperaerated lung and billateral sinusitis maxillaris; skin test results were house dust, food and pet allergy; an overweight body; bad school grades; psychological and environmental problem. We followed and evaluated this boy in 6 months, treated holistically. Even we could not do much on environmental but no more psychological and school problems, his on a good bodyweight and his asthma control test was 22. A case of a child with mild asthma attack frequent episode was reported. Asthma clinical course show no significant improvement when other predisposing factor is not well-controlled and a child’s growth and development may be affected. Improving condition of the patient can be created with the help of loving and caring way of nurturing from the parents and supportive peer group. Therefore, continuous and consistent monitoring is required because prognosis of asthma is generally good when regularly and properly controlled.

Keywords: asthma, chronic health problems, growth, development

Procedia PDF Downloads 229
3146 Neural Networks Models for Measuring Hotel Users Satisfaction

Authors: Asma Ameur, Dhafer Malouche

Abstract:

Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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3145 A Methodology for Automatic Diversification of Document Categories

Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

Abstract:

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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3144 A Hybrid Approach for Thread Recommendation in MOOC Forums

Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

Abstract:

Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

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3143 Q-Map: Clinical Concept Mining from Clinical Documents

Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

Abstract:

Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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3142 Features of Calculating Structures for Frequent Weak Earthquakes

Authors: M. S. Belashov, A. V. Benin, Lin Hong, Sh. Sh. Nazarova, O. B. Sabirova, A. M. Uzdin, Lin Hong

Abstract:

The features of calculating structures for the action of weak earthquakes are analyzed. Earthquakes with a recurrence of 30 years and 50 years are considered. In the first case, the structure is to operate normally without damage after the earthquake. In the second case, damages are allowed that do not affect the possibility of the structure operation. Three issues are emphasized: setting elastic and damping characteristics of reinforced concrete, formalization of limit states, and combinations of loads. The dependence of damping on the reinforcement coefficient is estimated. When evaluating limit states, in addition to calculations for crack resistance and strength, a human factor, i.e., the possibility of panic among people, was considered. To avoid it, it is proposed to limit a floor-by-floor speed level in certain octave ranges. Proposals have been developed for estimating the coefficients of the combination of various loads with the seismic one. As an example, coefficients of combinations of seismic and ice loads are estimated. It is shown that for strong actions, the combination coefficients for different regions turn out to be close, while for weak actions, they may differ.

Keywords: weak earthquake, frequent earthquake, damage, limit state, reinforcement, crack resistance, strength resistance, a floor-by-floor velocity, combination coefficients

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3141 Heavy Metal Contamination of Mining-Impacted Mangrove Sediments and Its Correlation with Vegetation and Sediment Attributes

Authors: Jumel Christian P. Nicha, Severino G. Salmo III

Abstract:

This study investigated the concentration of heavy metals (HM) in mangrove sediments of Lake Uacon, Zambales, Philippines. The relationship among the studied HM (Cr, Ni, Pb, Cu, Cd, Fe) and the mangrove vegetation and sediment characteristics were assessed. Fourteen sampling plots were designated across the lake (10 vegetated and 4 un-vegetated) based on distance from the mining effluents. In each plot, three sediment cores were collected at 20 cm depth. Among the dominant mangrove species recorded were (in order of dominance): Sonneratia alba, Rhizophora stylosa, Avicennia marina, Excoecaria agallocha and Bruguiera gymnorrhiza. Sediment samples were digested with aqua regia, and the HM concentrations were quantified using Atomic Absorption Spectroscopy (AAS). Results showed that HM concentrations were higher in the vegetated plots as compared to the un-vegetated sites. Vegetated sites had high Ni (mean: 881.71 mg/kg) and Cr (mean: 776.36 mg/kg) that exceeded the threshold values (cf. by the United States Environmental Protection Agency; USEPA). Fe, Pb, Cu and Cd had a mean concentration of 2597.92 mg/kg, 40.94 mg/kg, 36.81 mg/kg and 2.22 mg/kg respectively. Vegetation variables were not significantly correlated with HM concentration. However, the HM concentration was significantly correlated with sediment variables particularly pH, redox, particle size, nitrogen, phosphorus, moisture and organic matter contents. The Pollution Load Index (PLI) indicated moderate to high pollution in the lake. Risk assessment and management should be designed in order to mitigate the ecological risk posed by HM. The need of a regular monitoring scheme for lake and mangrove rehabilitation programs and management should be designed.

Keywords: heavy metals, mangrove vegetation, mining, Philippines, sediment

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3140 Avifaunal Diversity in the Mallathahalli Lake of Bangalore Urban District, Karnataka, India

Authors: Vidya Padmakumar, N. C. Tharavathy

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The study was conducted from July 2015 to July 2017 to determine and understand the occurrence, frequency and diversity of avifauna in the Mallathahalli Lake of Bangalore Urban district. During the study period, 46 species of both terrestrial, as well as, aquatic birds belonging to 30 families were identified out of which 9 families were aquatic birds and 21 families were terrestrial birds. There were 4 species of migratory birds out of 46, showing diurnal migration. There was a significant reduce in the number of bird species both terrestrial and aquatic during the summer season and also varied greatly during winters and monsoon. Of the total 24 species of aquatic birds, Fulica atra and Tachybaptus ruficolis were the most common with 100% frequency and the least frequent species with 3.02% frequency was identified as Threskiornis melanocephalus. Among the 22 species of terrestrial birds, Acridotheres tristis had a frequency of 89% and the least frequent was Pycnonotus cafer (4.45%). The most commonly encountered bird species were from the families- Anatidae, Podicipedidae, Ardeidae, Phalacrocoracidae, Rallidae, Accipitridae, Scolopacidae, Charadridae, Laridae, Meropidae, Hirudinidae. All the birds surviving around the area are dependent on the wetland and crop vegetation surrounding the lake, which are deteriorating due to anthropogenic interventions and urbanization which are rising to its peak gradually causing the decline in the avifaunal diversity.

Keywords: Avifaunal diversity, Mallathahalli lake, seasonal migration, urbanization

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3139 Constructing a Semi-Supervised Model for Network Intrusion Detection

Authors: Tigabu Dagne Akal

Abstract:

While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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3138 Hydrogeological Appraisal of Karacahisar Coal Field (Western Turkey): Impacts of Mining on Groundwater Resources Utilized for Water Supply

Authors: Sukran Acikel, Mehmet Ekmekci, Otgonbayar Namkhai

Abstract:

Lignite coal fields in western Turkey generally occurs in tensional Neogene basins bordered by major faults. Karacahisar coal field in Mugla province of western Turkey is a large Neogene basin filled with alternation of silisic and calcerous layers. The basement of the basin is composed of mainly karstified carbonate rocks of Mesozoic and schists of Paleozoic age. The basement rocks are exposed at highlands surrounding the basin. The basin fill deposits forms shallow, low yield and local aquifers whereas karstic carbonate rock masses forms the major aquifer in the region. The karstic aquifer discharges through a spring zone issuing at intersection of two major faults. Municipal water demand in Bodrum city, a touristic attraction area is almost totally supplied by boreholes tapping the karstic aquifer. A well field has been constructed on the eastern edge of the coal basin, which forms a ridge separating two Neogene basins. A major concern was raised about the plausible impact of mining activities on groundwater system in general and on water supply well field in particular. The hydrogeological studies carried out in the area revealed that the coal seam is located below the groundwater level. Mining operations will be affected by groundwater inflow to the pits, which will require dewatering measures. Dewatering activities in mine sites have two-sided effects: a) lowers the groundwater level at and around the pit for a safe and effective mining operation, b) continuous dewatering causes expansion of cone of depression to reach a spring, stream and/or well being utilized by local people, capturing their water. Plausible effect of mining operations on the flow of the spring zone was another issue of concern. Therefore, a detailed representative hydrogeological conceptual model of the site was developed on the basis of available data and field work. According to the hydrogeological conceptual model, dewatering of Neogene layers will not hydraulically affect the water supply wells, however, the ultimate perimeter of the open pit will expand to intersect the well field. According to the conceptual model, the coal seam is separated from the bottom by a thick impervious clay layer sitting on the carbonate basement. Therefore, the hydrostratigraphy does not allow a hydraulic interaction between the mine pit and the karstic carbonate rock aquifer. However, the structural setting in the basin suggests that deep faults intersecting the basement and the Neogene sequence will most probably carry the deep groundwater up to a level above the bottom of the pit. This will require taking necessary measure to lower the piezometric level of the carbonate rock aquifer along the faults. Dewatering the carbonate rock aquifer will reduce the flow to the spring zone. All findings were put together to recommend a strategy for safe and effective mining operation.

Keywords: conceptual model, dewatering, groundwater, mining operation

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3137 Research on the Correlation between College Students' Physical Fitness and Running Habits: Data Mining of Smart Phone Sports App

Authors: Mingming Guo, Xiaozan Wang

Abstract:

Introduction: The purpose of this study is to examine the correlation between the physical fitness of Chinese college students and their daily running habits (RH). Methods: A total of 718 college students from East China Normal University participated in this study (385 boys and 333 girls). Each participant participated in the Chinese Students’ Physical Fitness Test during the 2018-2019 school year. In addition, each student is also required to use the app to record all their running results during each run during the 2018-2019 school year. Researchers can query and export all running records through the app's management platform. Results: (1) The total number of kilometers run by the students showed a significant negative correlation with their vital capacity (VC), sitting body flexion (SBF), and long jump (LJ) (rᵥ

Keywords: college students, physical fitness, running habits, data mining

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3136 Generation of Knowlege with Self-Learning Methods for Ophthalmic Data

Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

Abstract:

Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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3135 From Ritual to Entertainment: Echoes of Realism and Creativity in Costumes of Masquerades in New Nigerian Festivals

Authors: Bernard Eze Orji

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The masquerade, which is the most popular indigenous art form in Africa, is obviously identified by its elaborate, weird, and opulent costumes. The costume is the major essential accouterments in the art of the masquerade. From time past, masquerades have performed and enjoyed the freedom associated with its inscrutability and mystification solely because of its costumes. Noninitiates and women watched masquerades from a distance due to the reverence attached to its costumes and performances. In fact, whether in performance or as an item of art, the masquerade costume was seen as an embodiment of a tradition of liveliness, showiness, secrecy, and sacredness. This liveliness and showiness transformed masked characters who are believed to be possessed by spirits of ancestors and animals that inhabited the costumes. However, with the translocation of masquerade in new festivals such as carnival and state-sponsored cultural days, its costumes have been reduced to a mere item of entertainment and aesthetic values. The sacredness and reverence which hitherto elevated masquerade art to the point of wonderment have given way to an aesthetic appreciation of ingenious and individual creativity deployed in these festivals. This is as a result of the realistic and artistic creations that pervade masquerade costumes and masks in these festivals. It is a common sight to see such masquerades of animal and human genera like a lion, elephant, hippopotamus, and antelope; Agbogho Mmuo, Adamma, and Nchiekwa, respectively. This creative flair has emerged to expunge the ritual narratives associated with masquerades in the past. The study utilized performance analysis and aesthetic theory to establish that the creative ingenuity deployed by fine artists and mask designers who combine traditional artifacts to achieve modern masterpieces for the masquerades of the new festivals have reduced the ritual trappings and hype ascribed to masquerades in indigenous societies.

Keywords: costume and mask designs, entertainment, masquerade, ritual

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3134 Determination of the Bank's Customer Risk Profile: Data Mining Applications

Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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3133 Parallel Genetic Algorithms Clustering for Handling Recruitment Problem

Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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3132 Isotype and Logical Positivism: A Critical Understanding through Intersemiotic Translation

Authors: Satya Girish Goparaju, Sushmita Pareek

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This paper examines two sets of pictograms published in Neurath’s books Basic by Isotype and International Pictorial Language in order to investigate the reasons for pictorial language having become an end in itself despite its potential to be relevant, especially in the 21st century digital age of heightened interlingual engagement. ISOTYPE was developed by Otto Neurath to be an ‘international language’ (pictorial) in the late 1920s. It was derived from the philosophy of logical positivism (of the Vienna Circle), which believed that language can be reduced to sets of direct experiences as bare symbols, devoid of the emotive and expressive functions. In his book International Picture Language, Neurath noted that any language is less clear-cut in one or the other way, and hence the pictorial language was justified. However, Isotype, as an ambitious version of logical positivism in practice distanced itself from the semiotic theories of language, and therefore his pictograms were defined as an independent set of signs rather than signs as a part of the language. This paper attempts to investigate intersemiotic translation in the form of Isotypes and trace the effects of logical positivism on Neurath’s concept of isotypes; the ‘international language’.

Keywords: intersemiotic translation, isotype, logical positivism, Otto Neurath, translation studies

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3131 Gravity and Magnetic Survey, Modeling and Interpretation in the Blötberget Iron-Oxide Mining Area of Central Sweden

Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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3130 Environmental Monitoring by Using Unmanned Aerial Vehicle (UAV) Images and Spatial Data: A Case Study of Mineral Exploitation in Brazilian Federal District, Brazil

Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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3129 Lowering Error Floors by Concatenation of Low-Density Parity-Check and Array Code

Authors: Cinna Soltanpur, Mohammad Ghamari, Behzad Momahed Heravi, Fatemeh Zare

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Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.

Keywords: concatenated coding, low–density parity–check codes, array code, error floors

Procedia PDF Downloads 357