Search results for: sequential pattern mining

Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

Procedia PDF Downloads 120

Authors: Ming Su, Ziqiang Mu

Abstract:

This paper proposes a synthesis method for nonuniform linear antenna arrays that combine Gaussian process regression (GPR) and genetic algorithm (GA). In this method, the GPR model can be used to calculate the array radiation pattern in the presence of mutual coupling effects, and then the GA is used to optimize the excitations and locations of the elements so as to generate the desired radiation pattern. In this paper, taking a 9-element nonuniform linear array as an example and the desired radiation pattern corresponding to a Chebyshev distribution as the optimization objective, optimize the excitations and locations of the elements. Finally, the optimization results are verified by electromagnetic simulation software CST, which shows that the method is effective.

Keywords: nonuniform linear antenna arrays, GPR, GA, mutual coupling effects, active element pattern

Procedia PDF Downloads 82

Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

Abstract:

Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

Procedia PDF Downloads 631

Authors: Paul Idoko Ukanu, Sunday Abba, Balogun Sadiya

Abstract:

The study of the finger prints patterns among the Igala ethnic groups was done in order to see their association gender. A cross sectional study was conducted and a total of 602 subjects participated in this study, 322 females and 280 males, which were mainly secondary school students between the age ranges of 13-19 years. The subjects fingerprint pattern was obtained by allowing them place the tip of each finger on the stamp pad, which is then imprinted on the questionnaire, this was done for both the left and right hand. Female had higher arch, whorl and loop finger print pattern in most of the right fingers than the males, the differences were statistically significant for the right index, right ring finger and right little finger, but were statistically insignificant for right thumb and right middle finger as p = 0.207 and 0.726, respectively. The result also revealed that males had higher arch finger print pattern in the right index and right little finger than the females, which was statistically significant (p = 0.001), and also a high whorl finger print pattern than the females in the right middle and ring finger.

Keywords: arch, loop, whorl, fingers

Procedia PDF Downloads 112

Authors: Taechit Cheuypoung

Abstract:

The research will focus on creating pattern designs that are inspired by the pagodas, Phra Maha Chedi of King Rama I-IV, that are located in the temple, Wat Phra Chetuphon Vimolmangklararm Rajwaramahaviharn. Different aspects of the temple were studied, including the history, architecture, significance of the temple, and techniques used to decorate the pagodas, Phra Maha Chedi of King Rama I-IV. Moreover, composition of arts and the form of pattern designs which all led to the outcome of four Thai application pattern. The four patterns combine Thai traditional design with international scheme, however, maintaining the distinctiveness of the glaze mosaic tiles of each Phra Maha Chedi. The patterns consist of rounded and notched petal flowers, leaves and vine, and various square shapes, and original colors which are updated for modernity. These elements are then grouped and combined with new techniques, resulting in pattern designs with modern aspects and simultaneously reflecting the charm and the aesthetic of Thai craftsmanship which are eternally embedded in the designs.

Keywords: Chedi, Pagoda, pattern, Wat

Procedia PDF Downloads 351

Authors: Tatjana Stefanovic Stanojevic, Milica Tosic Radev, Aleksandra Bogdanovic

Abstract:

Depression is considered to be a leading cause of death and disability in the female population, and that is the reason why understanding the dynamics of the onset of depressive symptomatology is important. A review of the literature indicates the relationship between depressive symptoms and insecure attachment patterns, but very few studies have examined the mechanism underlying this relation. The aim of the study was to examine the pathway from the preoccupied attachment pattern to depressive symptomatology, as well as to test the mediation effect of mentalization, social anxiety and rumination in this relationship using a serial mediation model. The research was carried out on a geographical cluster sample from the general population of Serbia included within the project ‘Indicators and models of family and work roles harmonization’ funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia. This research was carried out on a subsample of 791 working-age female adults from 37 urban and rural locations distributed through 20 administrative districts of Serbia. The respondents filled in a battery of instruments, including Relationship Questionnaire - Clinical Version (RQ - CV), The Mentalization Scale (MentS), Scale of Social Anxiety (SA), Patient Ruminative Thought Style Questionnaire (RTSQ), Health Questionnaire (PHQ-9). The results confirm our assumption that the total indirect effect of the preoccupied attachment pattern to depressive symptoms is significant across all mediators separately. More importantly, this effect is still present in a model with a sequential mediator relationship, where social anxiety, rumination, and mentalization were perceived as serial mediators of a relationship between preoccupied attachment and depressive symptoms (estimated indirect effect=0.004, boot-strapped 95% CI=0.002 to 0.007). Our findings suggest that there is a significant specific indirect effect of the preoccupied attachment pattern to depressive symptoms, occurring through mentalization, social anxiety and rumination, indicating that preoccupied attachment cause decrease of a self related mentalization, which in turn causes increasing of social anxiety and rumination, concluding in depressive symptoms as a final consequence. The finding that the path from the preoccupied attachment pattern to depressive symptoms is typical in women is understandable from the perspective of both evolutionary and culturally conditioned gender differences. The practical implications of the study are reflected in the recommendations for the prevention and forehand psychotherapy response among preoccupied women with depressive symptomatology. Treatment of this specific group of depressed patients should be focused on strengthening mentalization, learning to accept and to understand herself better, reducing anxiety in situations where mistakes are visible to others, and replacing the rumination strategy with more constructive coping strategies.

Keywords: preoccupied attachment, depression, serial mediation model, mentalization, rumination

Procedia PDF Downloads 115

Authors: O. R. Obalowu, F. B. Akande, T. P Abegunrin

Abstract:

Maize (Zea may) is mostly grown and consumed by Nigeria farmers using different tillage practices which have a great effect on its growth and yield. In order to maximize output, there is need to recommend a suitable tillage practice for crop production which will increase the growth and yield of maize. This study investigated the effect of tillage practices and planting pattern on the growth and yield of maize. The experiment was arranged in a 4x3x3 Randomized Complete Block Design (RCBD) layout, with four tillage practices consisting of no-tillage (NT), disc ploughing only (Ponly), disc ploughing followed by harrowing (PH), and disc ploughing, harrowing then ridging (PHR). Three planting patterns which include; 65 x 75, 75 x 75 and 85 x 75 cm spacing within and between the rows respectively, were randomly applied on the plots. All treatments were replicated three times. Data which consist of plant height, stem girth, leaf area and weight of maize per plots were taken and recorded. Data gathered were analyzed using Analysis of Variance (ANOVA) in the Minitab Software Package. The result shows that PHR under the third planting pattern has the highest growth rate (216.50 cm) while NT under the first planting pattern has the lowest mean value of growth rate (115.60 cm). Also, Ponly under the first planting pattern gives a better maize yield (19.45 kg) when compared with other tillage practices while NT under first planting pattern recorded the least yield of maize (9.40 kg). In conclusion, considering soil and weather conditions of the research area, plough only under the first planting pattern (65 x 75 cm) is the best alternative for the production of the Swan maize variety.

Keywords: tillage practice, planting pattern, disc ploughing, harrowing, ridging

Procedia PDF Downloads 454

Authors: Mai Anh Pham Ho

Abstract:

Ao Dai is the traditional dress of Vietnamese women that consists of a long tunic with slits on either side and wide trousers. This is the Vietnamese national costume which most common worn by women in daily life. The Vietnamese men may wear Ao Dai on special occasions like New Year Eve or Wedding Ceremony. Ao Dai is one of the few Vietnamese words that appear in English language dictionaries. Nowadays, there are variations in modern Ao Dai that consist of a short tunic on knee and slim trousers with the other materials like kaki or jeans. This paper aims to apply Pop art pattern on modern Ao Dai through the image of Vietnamese women by modifying the creation process of fashion design. It reflects on how modern culture is involved in Ao Dai and how it affects on fashion design. The research method of this paper is done through surveying the various examples of technological applications to fashion design, then the pop art pattern with the image of Vietnamese women is applied on modern Ao Dai. The results of this paper have shown through the collection of modern Ao Dai with three artworks applied the pop art pattern. In conclusion, the role of fashion technology supports and evolves the traditional value in order to establish the Vietnamese national personality as well as distinguish to other cultural values in the world.

Keywords: pop art pattern, Vietnamese national costume, modern ao dai, fashion design

Procedia PDF Downloads 252

Authors: Kateryna Zharan, Jan C. Bongaerts

Abstract:

In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.

Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy

Procedia PDF Downloads 316

Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

Abstract:

The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

Procedia PDF Downloads 56

Authors: Nakache Radouane, M. Boukelloul, M. Fredj

Abstract:

Method room and pillar sizes are key factors for safe mining and their recovery in open-stop mining. This method is advantageous due to its simplicity and requirement of little information to be used. It is probably the most representative method among the total load approach methods although it also remains a safe design method. Using a finite element software (PLAXIS 3D), analyses were carried out with an elasto-plastic model and comparisons were made with methods based on the total load approach. The results were presented as the optimization for improving the ore recovery rate while maintaining a safe working environment.

Keywords: room and pillar, mining, total load approach, elasto-plastic

Procedia PDF Downloads 310

Authors: Seyed Mohsen Samaei, Shirley Gato-Trinidad

Abstract:

A pre-treatment stage prior to reverse osmosis (RO) is very important to ensure the long-term performance of the RO membranes in any wastewater treatment using RO. This study aims to evaluate the application of the Actiflo^® clarifier as part of a pre-treatment unit in mining operations. It involves performing analytical testing on RO feed water before and after installation of Actiflo^® unit. Water samples prior to RO plant stage were obtained on different dates from Costerfield mining operations in Victoria, Australia. Tests were conducted in an independent laboratory to determine the concentration of various compounds in RO feed water before and after installation of Actiflo^® unit during the entire evaluated period from December 2015 to June 2018. Water quality analysis shows that the quality of RO feed water has remarkably improved since installation of Actiflo^® clarifier. Suspended solids (SS) and turbidity removal efficiencies has been improved by 91 and 85 percent respectively in pre-treatment system since the installation of Actiflo^®. The Actiflo^® clarifier proved to be a valuable part of pre-treatment system prior to RO. It has the potential to conveniently condition the mining wastewater prior to RO unit, and reduce the risk of RO physical failure and irreversible fouling. Consequently, reliable and durable operation of RO unit with minimum requirement for RO membrane replacement is expected with Actiflo^® in use.

Keywords: ACTIFLO ® clarifier, mining wastewater, reverse osmosis, water treatment

Procedia PDF Downloads 173

Authors: İbrahi̇m Kara, Seher Arslankaya

Abstract:

Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

Procedia PDF Downloads 330

Authors: Salamatu Shaibu, Jan Hernning Sommer

Abstract:

Integrating biodiversity conservation practices in mining landscapes ensures the continual provision of various ecosystem services to the dependent communities whilst serving as ecological insurance for corporate mining when purchasing reclamation security bonds. Climate hazards such as long dry seasons, erratic rainfall patterns, and extreme weather events contribute to biodiversity loss in addition to the impact due to mining. Both corporate mining and mine-fringe communities perceive the effect of climate on biodiversity from the context of the benefits they accrue, which motivate their conservation practices. In this study, pragmatic approaches including semi-structured interviews, field visual observation, and review were used to collect data on corporate mining employees and households of fringing communities in the southwestern mining hub. The perceived changes in the local climatic conditions and the consequences on environmental management practices that promote biodiversity conservation were examined. Using a thematic content analysis tool, the result shows that best practices such as concurrent land rehabilitation, reclamation ponds, artificial wetlands, land clearance, and topsoil management are directly affected by prolonging long dry seasons and erratic rainfall patterns. Excessive dust and noise generation directly affect both floral and faunal diversity coupled with excessive fire outbreaks in rehabilitated lands and nearby forest reserves. Proposed adaptive measures include engaging national conservation authorities to promote reforestation projects around forest reserves. National government to desist from using permit for mining concessions in forest reserves, engaging local communities through educational campaigns to control forest encroachment and burning, promoting community-based resource management to promote community ownership, and provision of stricter environmental legislation to compel corporate, artisanal, and small scale mining companies to promote biodiversity conservation.

Keywords: biodiversity conservation, climate hazards, corporate mining, mining landscapes

Procedia PDF Downloads 182

Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

Abstract:

In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

Procedia PDF Downloads 131

Authors: Yunus Doğan, Ahmet Durap

Abstract:

Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

Procedia PDF Downloads 337

Authors: S. Abera, T. Gidey, W. Terefe

Abstract:

Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

Procedia PDF Downloads 465

Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

Abstract:

This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

Procedia PDF Downloads 377

Authors: Shahin Shabani, Pouya Pourmadadi

Abstract:

Tunnel boring machines (TBMs) have been used for the construction of various tunnels for mining projects for the purpose of access, conveyance of ore and waste, drainage, exploration, water supply and water diversion. Several mining projects have seen the successful and economic beneficial use of TBMs, and there is an increasing awareness of the benefits of TBMs for mining projects. Key technical considerations for the use of TBMs for the construction of tunnels for mining projects include geological issues (rock type, rock alteration, rock strength, rock abrasivity, durability, ground water inflows), depth of cover and the potential for overstressing/rockbursts, site access and terrain, portal locations, TBM constraints, minimum tunnel size, tunnel support requirements, contractor and labor experience, and project schedule demands. This study focuses on tunnelling mining, with the goal to develop methods and tools to be used to gain understanding of these processes, and to analyze metro of Tehran. The Metro Line 7 of Tehran is one of the Longest (26 Km) and deepest (27m) of projects that’s under implementation. Because of major differences like passing under all geotechnical layers of the town and encountering part of it with underground water table and also using mechanized excavation system, is one of special metro projects.

Keywords: TBM, tunnel boring machines economic, metro, line 7

Procedia PDF Downloads 353

Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

Abstract:

It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

Procedia PDF Downloads 268

Authors: Mohamed Hendawy Mousa, Warda Youssef Mohamed Morsy

Abstract:

Background: Sepsis is a major cause of mortality and morbidity in trauma patients. Body mass index as an indicator of nutritional status was reported as a predictor of injury pattern and complications among critically ill injured patients. Aim: The aim of this study is to investigate the relationship between body mass index and the development of sepsis, systemic inflammatory response syndrome among adult trauma patients at emergency hospital - Cairo University. Research design: Descriptive correlational research design was utilized in the current study. Research questions: Q1. What is the body mass index profile of adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, Q2. What is the frequency of systemic inflammatory response syndrome and sepsis among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, and Q3. What is the relationship between the development of sepsis, systemic inflammatory response syndrome and body mass index among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?. Sample: A purposive sample of 52 adult male and female trauma patients with revised trauma score 10 to 12. Setting: The Emergency Hospital affiliated to Cairo University. Tools: Four tools were utilized to collect data pertinent to the study: Socio demographic and medical data tool, Systemic inflammatory response syndrome assessment tool, Revised Trauma Score tool, and Sequential organ failure assessment tool. Results: The current study revealed that, (61.5 %) of the studied subjects had normal body mass index, (25 %) were overweight, and (13.5 %) were underweight. 84.6% of the studied subjects had systemic inflammatory response syndrome and 92.3% were suffering from mild sepsis. No significant statistical relationship was found between body mass index and occurrence of Systemic inflammatory response syndrome (2= 2.89 & P = 0.23). However, Sequential organ failure assessment scores were affected significantly by body mass index was found mean of initial and last Sequential organ failure assessment score for underweight, normal and obese where t= 7.24 at p = 0.000, t= 16.49 at p = 0.000 and t= 9.80 at p = 0.000 respectively. Conclusion: Underweight trauma patients showed significantly higher rate of developing sepsis as compared to patients with normal body weight and obese. Recommendations: based on finding of this study the following are recommended: replication of the study on a larger probability sample from different geographical locations in Egypt; Carrying out of further studies in order to assess the other risk factors influencing trauma outcome and incidence of its complications; Establishment of standardized guidelines for managing underweight traumatized patients with sepsis.

Keywords: body mass index, sepsis, systemic inflammatory response syndrome, adult trauma

Procedia PDF Downloads 225

Authors: Arun Kumar Yadav

Abstract:

Coal contributes a significant role in India’s developmental mission. But, ironically, on the other side it causes large scale population displacement and significant changes in indigenous people’s livelihood mechanism. Dhanbad which is regarded as one of the oldest and large mining area, as well as a “Coal Capital of India”. Here, mining exploration work started nearly a century ago. But with the passage of time, mining brings a lot of changes in the life of local people. In this context, study tries to do comparative situational analysis of the changes in the living condition of dwellers living in mines affected and non-mines affected villages based on livelihood approach. Since, this place has long history of mining so it is very difficult to conduct before and after comparison between mines and non-mines affected areas. Consequently, the present study is based on relative comparison approach to elucidate the actual scenario. By using primary survey data which was collected by the author during the month of September 2014 to March 2015 at Dhanbad, Jharkhand. The data were collected from eight villages, these were categorised broadly into mines and non-mines affected villages. Further at micro level, mines affected villages has been categorised into open cast and underground mines. This categorization will help us to capture the deeper understanding about the issues of mine affected villages group. Total of 400 household were surveyed. Result depicts that in every sphere mining affected villages are more vulnerable. Regarding financial capital, although mine affected villages are engaged in mining work and get higher mean income. But in contrast, non-mine affected villages are more occupationally diversified. They have an opportunity to earn money from diversified extents like agricultural land, working in mining area, selling coal informally as well as receiving remittances. Non-mines affected villages are in better physical capital which comprises of basic infrastructure to support livelihood. They have an access to secured shelter, adequate water supply & sanitation, and affordable information and transport. Mining affected villages are more prone to health risks. Regarding social capital, it shows that in comparison to last five years, law and order has been improved in mine affected villages.

Keywords: displacement, indigenous, livelihood, mining

Procedia PDF Downloads 282

Authors: Mavis Yaa Konadu Agyemang

Abstract:

Despite provisions to uphold and safeguard the rights of persons with disability in Ghana, there is evidence that they still encounter several challenges which limit their full and effective involvement in mainstream society, including the gold mining sector. The study sought to explore how persons with physical disability (PWPDs) experience gold mining in the Obuasi Municipal Area. A qualitative research design was used to discover and understand the experiences of PWPDs regarding mining. The purposive sampling technique was used to select five key informants for the study with the age range of (24-52 years) while snowball sampling aided the selection of 16 persons with various forms of physical disability with the age range of (24-60 years). In-depth interviews were used to gather data. The interviews lasted from forty-five minutes to an hour. In relation to the setting, the interviews of thirteen (13) of the participants with disability were done in their houses, two (2) were done on the phone, and one (1) was done in the office. Whereas the interviews of the five (5) key informants were all done in their offices. Data were analyzed using Creswell’s (2009) concept of thematic analysis. The findings suggest that even though land degradation affected everyone in the area, persons with mobility and visual impairment experienced many difficulties trekking the undulating land for long distances in search of arable land. Also, although mining activities are mostly labour-intensive, PWPDs were not employed even in areas where they could work. Further, the cost of items, in general, was high, affecting PWPDs more due to their economic immobility and paying for other sources of water due to land degradation and water pollution. The study also discovered that the peculiar conditions of PWPDs were not factored into compensation payments, and neither were females with physical disability engaged in compensation negotiations. Also, although some of the infrastructure provided by the gold mining companies in the area was physically accessible to some extent, it was not accessible in terms of information delivery. There is a need to educate the public on the effects of mining on PWPDs, their needs as well as disability issues in general. The Minerals and Mining Act (703) should be amended to include provisions that would consider the peculiar needs of PWPDs in compensation payment.

Keywords: mining, resettlement, compensation, environmental, social, disability

Procedia PDF Downloads 25

Authors: Artur Cichowicz

Abstract:

The last active mine in the Central Rand Goldfields area (50 km x 15 km) ceased operations in 2008. This resulted in the closure of the pumping stations, which previously maintained the underground water level in the mining voids. As a direct consequence of the water being allowed to flood the mine voids, seismic activity has increased directly beneath the populated area of Johannesburg. Monitoring of seismicity in the area has been on-going for over five years using the network of 17 strong ground motion sensors. The objective of the project is to improve strategies for mine closure. The evolution of the seismicity pattern was investigated in detail. Special attention was given to seismic source parameters such as magnitude, scalar seismic moment and static stress drop. Most events are located within historical mine boundaries. The seismicity pattern shows a strong relationship between the presence of the mining void and high levels of seismicity; no seismicity migration patterns were observed outside the areas of old mining. Seven years after the pumping stopped, the evolution of the seismicity has indicated that the area is not yet in equilibrium. The level of seismicity in the area appears to not be decreasing over time since the number of strong events, with Mw magnitudes above 2, is still as high as it was when monitoring began over five years ago. The average rate of seismic deformation is 1.6x1013 Nm/year. Constant seismic deformation was not observed over the last 5 years. The deviation from the average is in the order of 6x10^13 Nm/year, which is a significant deviation. The variation of cumulative seismic moment indicates that a constant deformation rate model is not suitable. Over the most recent five year period, the total cumulative seismic moment released in the Central Rand Basin was 9.0x10^14 Nm. This is equivalent to one earthquake of magnitude 3.9. This is significantly less than what was experienced during the mining operation. Characterization of seismicity triggered by a rising water level in the area can be achieved through the estimation of source parameters. Static stress drop heavily influences ground motion amplitude, which plays an important role in risk assessments of potential seismic hazards in inhabited areas. The observed static stress drop in this study varied from 0.05 MPa to 10 MPa. It was found that large static stress drops could be associated with both small and large events. The temporal evolution of the inter-event time provides an understanding of the physical mechanisms of earthquake interaction. Changes in the characteristics of the inter-event time are produced when a stress change is applied to a group of faults in the region. Results from this study indicate that the fluid-induced source has a shorter inter-event time in comparison to a random distribution. This behaviour corresponds to a clustering of events, in which short recurrence times tend to be close to each other, forming clusters of events.

Keywords: inter-event time, fluid induced seismicity, mine closure, spectral parameters of seismic source

Procedia PDF Downloads 259

Authors: Elham Fathi, Seyed Mohammad Kalantarkousheh, Abolfazl Hatami Varzane

Abstract:

The present study aimed to determine predict capacity of the relationship among attachment styles, humor styles and communication patterns in female married students. Statistical population consisted of female married students from Allameh Tabataba’i University. The research sample consisted of 104 married students selected through convenience sampling. They responded to study instruments that consisted of attachment styles, humor styles and Communication patterns questionnaires. Data was analyzed by means of correlation method. The results indicated significant positive relationship between secure attachment styles with adaptive humor styles, and anxious attachment styles with maladaptive humor styles. Also a negative relationship between avoidant attachment with affiliative humor, and anxious attachment with self-enhancing humor was found. Furthermore, a negative relationship between self- enhancing humor styles with demand – withdraw communication pattern, and between affiliative humor with mutual avoidant communication pattern and a positive relationship between affiliative humor with mutual constructive communication pattern was observed. The relationship between secure attachment with mutual constructive communication pattern was positive, while relationship between avoidant attachment to mutual constructive communication pattern was negative and significant and its relation with mutual avoidant communication pattern was significantly positive. The result of regression analysis indicated that affliative humor style and secure attachment style, positively predicted mutual constructive communication pattern. Avoidant attachment style positively and affliative humor style negatively predicted the mutual avoidant communication pattern. And self-enhancing humor style negatively predicted the demand – withdraw communication pattern style.

Keywords: attachment styles, communication patterns, humor styles, female married students

Procedia PDF Downloads 349

Authors: Jawharah Alasmari

Abstract:

In verb inflection, tense marks past/present/future action, and aspect marks progressive/continues perfect/completed actions. This usage and meaning of tense and aspect differ in Arabic and English. In this research, we applied data mining methods to test the predictive function of candidate features by using our dataset of Arabic verbs in-context, and their 7 translations. Weka machine learning classifiers is used in this experiment in order to examine the key features that can be used to provide guidance to enable a translator’s appropriate English translation of the Arabic verb tense and aspect.

Keywords: Arabic verb, English translations, mining methods, Weka software

Procedia PDF Downloads 247

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well.

Keywords: data mining technique, the decision support system, knowledge and decision rules, education

Procedia PDF Downloads 397

Authors: Tolga Aydin, M. Fatih Alaeddinoğlu

Abstract:

People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatio-temporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newly-formed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: apriori algorithm, association rules, data mining, spatio-temporal data

Procedia PDF Downloads 344

Authors: Saroj Bijarnia, Preety Singh

Abstract:

We propose a simple and effective biometrics system based on face verification across aging using a new variant of texture feature, Pyramid Binary Pattern. This employs Local Binary Pattern along with its hierarchical information. Dimension reduction of generated texture feature vector is done using Principal Component Analysis. Support Vector Machine is used for classification. Our proposed method achieves an accuracy of 92:24% and can be used in an automated age-invariant face verification system.

Keywords: biometrics, age invariant, verification, support vector machine

Procedia PDF Downloads 316

Authors: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

Abstract:

Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining

Procedia PDF Downloads 280