Search results for: mining software repositories

Authors: G. Gevorgyan, S. Khudaverdyan, A. Vaseashta

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The Lake Sevan basin is situated in the eastern part of the Republic of Armenia (Gegharquniq marz/district). The heavy metal pollution of the some tributaries of Lake Sevan was investigated. Water sampling was performed in August and December, 2014 from the 4 observation sites: 1) Sotq river upstream (about 600 meters upstream from the Sotq gold mine); 2) Sotq river mouth; 3) Masrik river mouth; 4) Dzknaget river mouth. Heavy metal (V, Fe, Ni, Cu, As, Mo, Pb) concentrations in the water samples were determined by the standard methods using an atomic absorption spectrophotometer. The results of the study showed that heavy metal content mainly increased from the upstream of the Sotq river to the mouth of the Masrik river which may have been conditioned by the influence of gold mining activity as the Masrik and its tributary-Sotq rivers passing through the gold mining area were exposed to heavy metal pollution. The observation sites can be ranked by pollution degree as follows: №3> №2> №1> №4. The highest heavy metal pollution degree was observed in the Masrik river mouth which may have been conditioned by the direct impact of gold mining activity and the pressure of its tributary–the Sotq river which flows through the gold mining area. The lowest heavy metal pollution degree was registered in the Dzknaget river mouth which flowing through rural areas wasn’t subject to significant heavy metal pollution. According to the observation sites of the Sotq and Masrik rivers, high positive correlation was mainly observed between the concentrations of the investigated heavy metals (except nickel) which indicated that all the heavy metals except the nickel had the same anthropogenic pollution source which was the activity of the Sotq gold mine. In general, it is possible to state that the activity of the Sotq gold mine in the Lake Sevan basin caused the heavy metal pollution of the Sotq and Masrik rivers which may have posed environmental hazards. Heavy metals are nondegradable substances, and heavy metal pollution of freshwater systems may pose risks to the environment and human health through accumulation in the tissues of aquatic organisms, water-food chain as well as oral ingestion and dermal contact.

Keywords: Armenia, Lake Sevan basin, gold mining activity, river ecosystems, heavy metal pollution

Procedia PDF Downloads 565

Authors: Manel Brichni, Abdelhak-Djamel Seriai

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Systems are increasingly complex. To reduce their complexity, an abstract view of the system can simplify its development. To overcome this problem, we propose a method to decompose systems into subsystems while reducing their coupling. These subsystems represent components. Consisting of an existing object-oriented systems, the main idea of our approach is based on modelling as graphs all entities of an oriented object source code. Such modelling is easy to handle, so we can apply restructuring algorithms based on graph metrics. The particularity of our approach consists in integrating in addition to standard metrics, such as coupling and cohesion, some graph metrics giving more precision during the components identication. To treat this problem, we relied on the ROMANTIC approach that proposed a component-based software architecture recovery from an object oriented system.

Keywords: software reengineering, software component and interfaces, metrics, graphs

Procedia PDF Downloads 479

Authors: Huynh Tan Hoi

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Considered as one of the hardest languages in the world, Japanese is still the language that many young people choose to learn. Today, with the development of technology, learning foreign languages in general and Japanese language, in particular, is not an impossible barrier. Learning materials are not only from paper books, songs but also through software programs of smartphones or computers. Especially, students who begin to explore effective skills to study this language need to access modern technologies to improve their learning much better. When using the software, some students may feel embarrassed and challenged, but everything would go smoothly after a few days. After completing the course, students will get more knowledge, achieve a higher knowledge such as N2 or N1 Japanese Language Proficiency Test Certificate. In this research paper, 35 students who are studying at Ho Chi Minh City FPT University were asked to complete the questionnaire at the beginning of July up to August of 2018. Through this research, we realize that with the guidance of lecturers, the necessity of using modern software and some effective methods are indispensable in term of improving quality of teaching and learning process.

Keywords: higher knowledge, Japanese, methods, software, students

Procedia PDF Downloads 196

Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

Procedia PDF Downloads 387

Authors: Nermin Sökmen

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An effort estimation model is needed for software-intensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

Keywords: functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis

Procedia PDF Downloads 264

Authors: Ivan Stanev, Maria Koleva

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Automated software development issues are addressed in this paper. Layers and packages of a Common Platform for Automated Programming (CPAP) are defined based on Service Oriented Architecture, Cloud computing, Knowledge based automated software engineering (KBASE) and Method of automated programming. Tools of seven leading companies (AWS of Amazon, Azure of Microsoft, App Engine of Google, vCloud of VMWare, Bluemix of IBM, Helion of HP, OCPaaS of Oracle) are analyzed in the context of CPAP. Based on the results of the analysis CPAP requirements are formulated

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

Procedia PDF Downloads 275

Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Mahdi Hamzehei, Homan Alimoradzadeh, Mahdi Shahriyari

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In this paper, vibration of the industrial centrifugal pumps studied by measuring analysis and computational simulation. Effects of different parameters on pump vibration were investigated. Also, simulation of cavitation in the centrifugal pump was down. First, via CF-TURBO software, the pump impeller and the fluid passing through the pump is modelled and finally, the phenomenon of cavitation in the impeller has been modelled by Ansys software. Also, the effects of changes in the amount of NPSH and bubbles generation in the pump impeller were investigated. By simulation of piping with pipe flow software, effect of fluid velocity and pressure on hydraulics and vibration were studied computationally by applying Computational Fluid Dynamic (CFD) techniques, fluent software and experimentally. Furthermore, this comparison showed that the model can predict hydraulics and vibration behaviour.

Keywords: cavitation, vibration, centrifugal pumps, performance curves, NPSH

Procedia PDF Downloads 523

Authors: Theertha Chandroth

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This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

Procedia PDF Downloads 104

Authors: Soumyadip Banerjee, Tanmoy Maity

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The recovery of power from waste air generated by mine ventilation fans presents a promising avenue for enhancing energy efficiency in mining operations. This abstract explores the feasibility and benefits of utilizing turbine generators to capture the kinetic energy present in waste air and convert it into electrical power. By integrating turbine generator systems into mine ventilation infrastructures, the potential to harness and utilize the previously untapped energy within the waste air stream is realized. This study examines the principles underlying turbine generator technology and its application within the context of mine ventilation systems. The process involves directing waste air from ventilation fans through specially designed turbines, where the kinetic energy of the moving air is converted into rotational motion. This mechanical energy is then transferred to connected generators, which convert it into electrical power. The recovered electricity can be employed for various on-site applications, including powering mining equipment, lighting, and control systems. The benefits of power recovery from waste air using turbine generators are manifold. Improved energy efficiency within the mining environment results in reduced dependence on external power sources and associated cost savings. Additionally, this approach contributes to environmental sustainability by utilizing a previously wasted resource for power generation. Resource conservation is further enhanced, aligning with modern principles of sustainable mining practices. However, successful implementation requires careful consideration of factors such as waste air characteristics, turbine design, generator efficiency, and integration into existing mine infrastructure. Maintenance and monitoring protocols are necessary to ensure consistent performance and longevity of the turbine generator systems. While there is an initial investment associated with equipment procurement, installation, and integration, the long-term benefits of reduced energy costs and environmental impact make this approach economically viable. In conclusion, the recovery of power from waste air from mine ventilation fans using turbine generators offers a tangible solution to enhance energy efficiency and sustainability within mining operations. By capturing and converting the kinetic energy of waste air into usable electrical power, mines can optimize resource utilization, reduce operational costs, and contribute to a greener future for the mining industry.

Keywords: waste to energy, wind power generation, exhaust air, power recovery

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Authors: Farzan Farhangian, Behnam Shakibafar, Bobda Cedric, Rene Jr. Landry

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Among the air navigation technologies, many of them are capable of increasing aviation sustainability as well as accuracy improvement in Alternative Positioning, Navigation, and Timing (APNT), especially avionics Distance Measuring Equipment (DME), Very high-frequency Omni-directional Range (VOR), etc. The integration of these air navigation solutions could make a robust and efficient accuracy in air mobility, air traffic management and autonomous operations. Designing a proper RF front-end, power amplifier and software-defined transponder could pave the way for reaching an optimized avionics navigation solution. In this article, the possibility of reaching an optimum front-end to be used with single low-cost Software-Defined Radio (SDR) has been investigated in order to reach a software-defined DME architecture. Our software-defined approach uses the firmware possibilities to design a real-time software architecture compatible with a Multi Input Multi Output (MIMO) BladeRF to estimate an accurate time delay between a Transmission (Tx) and the reception (Rx) channels using the synchronous scheduled communication. We could design a novel power amplifier for the transmission channel of the DME to pass the minimum transmission power. This article also investigates designing proper pair pulses based on the DO-178B avionics standard. Various guidelines have been tested, and the possibility of passing the certification process for each standard term has been analyzed. Finally, the performance of the DME was tested in the laboratory environment using an IFR6000, which showed that the proposed architecture reached an accuracy of less than 0.23 Nautical mile (Nmi) with 98% probability.

Keywords: avionics, DME, software defined radio, navigation

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Bitopi Dutta

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Development Induced Displacement (DID) of subaltern groups has been an issue of intense debate in India. This research will do a gender analysis of displacement induced by the mining projects in tribal indigenous societies of North East India, centering on the primary research question which is 'How does DID reorder gendered relationship in tribal matrilineal societies?' This paper will not focus primarily on the impacts of the displacement induced by coal mining on indigenous tribal women in the North East India; it will rather study 'what' are the processes that lead to these transformations and 'how' do they operate. In doing so, the paper will locate the cracks in traditional social systems that the discourse of displacement manipulates for its own benefit. DID in this sense will not only be understood as only physical displacement, but also as social and cultural displacement. The study will cover one matrilineal tribe in the state of Meghalaya in the North East India affected by several coal mining projects in the last 30 years. In-depth unstructured interviews used to collect life narratives will be the primary mode of data collection because the indigenous culture of the tribes in Meghalaya, including the matrilineal tribes, is based on oral history where knowledge and experiences produced under a tradition of oral history exist in a continuum. This is unlike modern societies which produce knowledge in a compartmentalized system. An interview guide designed around specific themes will be used rather than specific questions to ensure the flow of narratives from the interviewee. In addition to this, a number of focus groups will be held. The data collected through the life narrative will be supplemented and contextualized through documentary research using government data, and local media sources of the region.

Keywords: displacement, gender-relations, matriliny, mining

Procedia PDF Downloads 168

Authors: K. Vrinda

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Coastal ecosystems across the world are facing a lot of challenges due to natural phenomena as well as from uncontrolled human interventions. Here, Alappad, a coastal island situated in Kerala, India is undergoing significant damage and is gradually losing its environmental and social sustainability. The area is blessed with very rare and precious black mineral sand deposits. Sand mining for these minerals started in 1911 and is still continuing. But, unfortunately all the problems that Alappad faces now, have its root on mining of this mineral sand. The land area is continuously diminishing due to sea erosion. The mining has also caused displacement of people and environmental degradation. Marine life also is getting affected by mining on beach and pollution. The inhabitants are fishermen who are largely dependent on the eco-system for a living. So loss of environmental sustainability subsequently affects social sustainability too. Now the damage has reached a point beyond which our actions may not be able to make any impact. This was one of the most affected areas of the 2004 tsunami and the environmental degradation has further increased the vulnerability. So this study focuses on understanding the concerns related to the resource utilization, environment and the indigenous community staying there, and on formulating suitable strategies to restore the sustainability of the area. An extensive study was conducted on site, to find out the physical, social, and economical characteristics of the area. A focus group discussion with the inhabitants shed light on different issues they face in their day-to-day life. The analysis of all these data, led to the formation of a new development vision for the area which focuses on environmental restoration and socio-economic development while allowing controlled exploitation of resources. A participatory approach is formulated which enables these three aspects through community based programs.

Keywords: Community development, Disaster resilience, Ecological restoration, Environmental sustainability, Social-environmental planning, Social Sustainability

Procedia PDF Downloads 88

Authors: Habila Nuhu

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Natural radionuclides in the environment can significantly contribute to human exposure to ionizing radiation. The knowledge of their levels in an environment can help the radiological protection agencies in policymaking. Measurement of natural radioactivity in major soils in the tin mining state of Perak Malaysia has been conducted using an HPGe detector. Seventy (70) soil samples were collected at widely distributed locations in the state. Six major soil types were sampled, and thirteen districts around the state were covered. The following were the results of the 226Ra (238U), 228Ra (232Th), and 40K activity in the soil samples: 226Ra (238U) has a mean activity concentration of 191.83 Bq kg⁻¹, more than five times the UNSCEAR reference limits of 35 Bq kg⁻¹. The mean activity concentration of 228Ra (232Th) with a value of 232.41 Bq kg⁻¹ is over seven times the UNSCEAR reference values of 30 Bq kg⁻¹. The average concentration of 40K activity was 275.24 Bq kg⁻¹, which was less than the UNSCEAR reference limit of 400 Bq Kg⁻¹. The range of external hazards index (Hₑₓ) values was from 1.03 to 2.05, while the internal hazards index (Hin) was from 1.48 to 3.08. The Hex and Hin should be less than one for minimal external and internal radiation threats as well as secure use of soil material for building construction. The Hₑₓ and Hin results generally indicate that while using the soil types and their derivatives as building materials in the study area, care must be taken.

Keywords: activity concentration, hazard index, soil samples, tin mining

Procedia PDF Downloads 90

Authors: Nizar Tayem, AbuMuhammad Moinuddeen, Ahmed A. Hussain, Redha M. Radaydeh

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This research paper introduces an approach for estimating the direction of arrival (DOA) of multiple RF noncoherent sources in a uniform linear array (ULA). The proposed method utilizes a Capon-like estimation algorithm and incorporates LU decomposition to enhance the accuracy of DOA estimation while significantly reducing computational complexity compared to existing methods like the Capon method. Notably, the proposed method does not require prior knowledge of the number of sources. To validate its effectiveness, the proposed method undergoes validation through both software simulations and practical experimentation on a prototype testbed constructed using a software-defined radio (SDR) platform and GNU Radio software. The results obtained from MATLAB simulations and real-time experiments provide compelling evidence of the proposed method's efficacy.

Keywords: DOA estimation, real-time validation, software defined radio, computational complexity, Capon's method, GNU radio

Procedia PDF Downloads 47

Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

Procedia PDF Downloads 41

Authors: Timothy J. Grebec

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This study investigated whether using a voice dictation software program (i.e., Google Voice Typing) has an impact on student writing quality. The research took place in a third-grade general education classroom in a suburban school setting. Because the study involved minors, all data was encrypted and deidentified before analysis. The students completed a series of writings prior to the beginning of the intervention to determine their thoughts and skill level with writing. During the intervention phase, the students were introduced to the voice dictation software, given an opportunity to practice using it, and then assigned writing prompts to be completed using the software. The prompts written by nineteen student participants and surveys of student opinions on writing established a baseline for the study. The data showed that using the dictation software resulted in a 34% increase in the response quality (compared to the Pennsylvania State Standardized Assessment [PSSA] writing guidelines). Of particular interest was the increase in students' proficiency in demonstrating mastery of the English language and conventions and elaborating on the content. Although this type of research is relatively no, it has the potential to reshape the strategies educators have at their disposal when instructing students on written language.

Keywords: educational technology, accommodations, students with disabilities, writing instruction, 21st century education

Procedia PDF Downloads 54

Authors: Kobamelo Mashaba

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The molten slag has a high substantial temperatures range between 1723-1923, carrying a huge amount of useful energy for reducing energy consumption and CO₂ emissions under the heat recovery process. Therefore in this study, we investigated the performance of the modified crank Nicolson method for a delayed partial differential equation on the heat recovery of molten slag in the metallurgical mining environment. It was proved that the proposed method converges quickly compared to the classic method with the existence of a unique solution. It was inferred from numerical result that the proposed methodology is more viable and profitable for the mining industry.

Keywords: delayed partial differential equation, modified Crank-Nicolson Method, molten slag, heat recovery, parabolic equation

Procedia PDF Downloads 82

Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

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True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

Procedia PDF Downloads 417

Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model

Procedia PDF Downloads 403

Authors: Aitana Alonso-Nogueira, Helia Estévez-Fernández, Isaías García

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This paper presents an approach to reduce some of its current flaws in the requirements phase inside the software development process. It takes the software requirements of an application, makes a conceptual modeling about it and formalizes it within JSON documents. This formal model is lodged in a NoSQL database which is document-oriented, that is, MongoDB, because of its advantages in flexibility and efficiency. In addition, this paper underlines the contributions of the detailed approach and shows some applications and benefits for the future work in the field of automatic code generation using model-driven engineering tools.

Keywords: conceptual modelling, JSON, NoSQL databases, requirements engineering, software development

Procedia PDF Downloads 357

Authors: Maphuti Georgina Kwata

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Coal mining in Mpumalanga Province is known of contributing to the atmospheric pollution from various activities. Gold mining in North-West Province is known of also contributing to the atmospheric pollution especially with the production of radon gas. In this research directional dust deposition gauge was used to measure source of direction and meteorological data was used to determine the wind rose blowing and the influence of the seasonal changes. Fourteen months of dust collection was undertaken in Witbank Area and Carletonville Area. The results shows that the sources of direction for Ericson Dam its East in February 2010 and Tip Area shows that the source of direction its West in October 2010. In the East direction there were mining operations, power stations which contributed to the East to be the sources of direction. In the West direction there were smelters, power stations and agricultural activities which contributed for the source of direction to be the West direction for Driefontein Mine: East Recreational Village Club. The East of Leslie Williams hospital is the source of direction which also indicated that there dust generating activities such as mining operation, agricultural activities. The meteorological results for Emalahleni Area in summer and winter the wind rose blow with wind speed of 5-10 ms-1 from the East sector. Annual average for the wind rose blow its East South eastern sector with 20 ms-1 and day time the wind rose from northwestern sector with excess of 20 ms-1. The night time wind direction East-eastern direction with a maximum wind speed of 20 ms-1. The meteorogical results for Driefontein Mine show that North-western sector and north-eastern sector wind rose is blowing with 5-10 ms-1 win speed. Day time wind blows from the West sector and night time wind blows from the north sector. In summer the wind blows North-east sector with 5-10 ms-1 and winter wind blows from North-west and it’s also predominant. In spring wind blows from north-east. The conclusion is that not only mining operation where the directional dust deposit gauge were installed contributed to the source of direction also the power stations, smelters, and other activities nearby the mining operation contributed. The recommendations are the dust suppressant for unpaved roads should be used on a regular basis and there should be monitoring of the weather conditions (the wind speed and direction prior to blasting to ensure minimal emissions).

Keywords: directional dust deposition gauge, BS part 5 1747 dust deposit gauge, wind rose, wind blowing

Procedia PDF Downloads 485

Authors: Khaled Soliman, Abdullah Alrushoud, Abdulrahman Alkhalifah, Raed Albathi, Salman Altymiat

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Radiation dose received by patients undergoing Computed Tomography (CT) examination of the cervical spine was evaluated using Gafchromic XR-QA2 films and CT-EXPO software (ver. 2.3), in order to document our clinical dose values and to compare our results with other benchmarks reported in the current literature. Radiochromic films were recently used as practical dosimetry tool that provides dose profile information not available using the standard ionisation chamber routinely used in CT dosimetry. We have developed an in-house program to use the films in order to calculate the Entrance Dose Length Product (EDLP) in (mGy.cm) and to relate the EDLP to various organ doses calculated using the CT-EXPO software. We also calculated conversion factor in (mSv/mGy.cm) relating the EDLP to the effective dose (ED) from the examination using CT-EXPO software. Variability among different types of CT scanners and dose modulation methods are reported from at least three major CT brands available at our medical institution. Our work describes the dosimetry method and results are reported. The method can be used as in-vivo dosimetry method. But this work only reports results obtained from adult female anthropomorphic Phantom studies.

Keywords: CT dosimetry, gafchromic films, XR-QA2, CT-Expo software

Procedia PDF Downloads 447

Authors: Monica Hoeldtke Pietruchinski, Andrey Ricardo Pimentel

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The teaching of computer programming for beginners has been presented to the community as a not simple or trivial task. Several methodologies and research tools have been developed; however, the problem still remains. This paper aims to present multi-agent system architecture to be incorporated to the educational collaborative game software for teaching programming that monitors, evaluates and encourages collaboration by the participants. A literature review has been made on the concepts of Collaborative Learning, Multi-agents systems, collaborative games and techniques to teach programming using these concepts simultaneously.

Keywords: architecture of multi-agent systems, collaborative evaluation, collaboration assessment, gamifying educational software

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Authors: Shreya Bokare, Sanjay Pawar, Shika Nema

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Growth in cloud applications is generating the tremendous amount of data, building load on traditional storage management systems. Software Defined Storage (SDS) is a new storage management concept becoming popular to handle this large amount of data. CoprHD is one of the open source SDS controller, available for experimentation and development in the storage industry. In this paper, the storage management techniques provided by CoprHD to manage heterogeneous storage platforms are experimented and analyzed. Various storage management parameters such as time to provision, storage capacity measurement, and heterogeneity are experimentally evaluated along with the theoretical expression to prove the completeness of CoprHD controller for storage management.

Keywords: software defined storage, SDS, CoprHD, open source, SMI-S simulator, clarion, Symmetrix

Procedia PDF Downloads 282

Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

Procedia PDF Downloads 141

Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

Abstract:

Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

Procedia PDF Downloads 347

Authors: Cherry Oo, Hnin Min Oo

Abstract:

Software bug localization is one of the most costly tasks in program repair technique. Therefore, there is a high claim for automated bug localization techniques that can monitor programmers to the locations of bugs, with slight human arbitration. Spectrum-based bug localization aims to help software developers to discover bugs rapidly by investigating abstractions of the program traces to make a ranking list of most possible buggy modules. Using the Apache Commons Math library project, we study the diagnostic accuracy using our spectrum-based bug localization metric. Our outcomes show that the greater performance of a specific similarity coefficient, used to inspect the program spectra, is mostly effective on localizing of single line bugs.

Keywords: software testing, bug localization, program spectra, bug

Procedia PDF Downloads 122

Authors: Yayun Hsu, Henry Horng-Shing Lu

Abstract:

In this paper, a new method is proposed to extending the method of connected component labeling from processing binary images to multi-scale modeling of images. By using the adaptive threshold of multi-scale attributes, this approach minimizes the possibility of missing those important components with weak intensities. In addition, the computational cost of this approach remains similar to that of the typical approach of component labeling. Then, this methodology is applied to grain boundary detection and Drosophila Brain-bow neuron segmentation. These demonstrate the feasibility of the proposed approach in the analysis of challenging microscopy images for scientific discovery.

Keywords: microscopic image processing, scientific data mining, multi-scale modeling, data mining

Procedia PDF Downloads 415