Search results for: open mining

Authors: Felix Gbenoba, Opeyemi Dahunsi

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Customised, self-instructional materials are at the heart of instructional delivery in Open and Distance Learning (ODL). The success of any ODL institution depends on the availability of learning materials in quality and quantity. An ODL study material is expected to imitate what the teacher does in the face-to-face learning environment. This paper evaluates these expectation based on existing data and evidence. It concludes that the reality has not matched the expectation so far in terms of pedagogic aspect of instructional delivery especially in West Africa. This does not mean that instructional materials development has not produced any significant positive results in improving the overall learning (and teaching) experience in these institutions; it implies what will help further to identify the new challenges. Obstacles and problems of instructional materials development that could have affected the open educational resource initiatives are well established. The first section of this paper recalls some of the proposed values of instructional materials. The second section compares achievements so far and suggests that instructional materials development should be consider first at an early stage to realise the aspirations of instructional delivery. The third section highlights the challenges of instructional materials development in the future.

Keywords: face-to-face learning, instructional delivery, open and distance education, self-instructional materials

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Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

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

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

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

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

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

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

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Authors: S. M. Rifat, André L. Marchildon, Mark F. Tachie

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The effect of upstream surface roughness over a smooth forward facing step in an open channel was investigated using a particle image velocimetry technique. Three different upstream surface topographies consisting of hydraulically smooth wall, sandpaper 36 grit and sand grains were examined. Besides the wall roughness conditions, all other upstream flow characteristics were kept constant. It was also observed that upstream roughness decreased the approach velocity by 2% and 10% but increased the turbulence intensity by 14% and 35% at the wall-normal distance corresponding to the top plane of the step compared to smooth upstream. The results showed that roughness decreased the reattachment lengths by 14% and 30% compared to smooth upstream. Although the magnitudes of maximum positive and negative Reynolds shear stress in separated and reattached region were 0.02Ue for all the cases, the physical size of both the maximum and minimum contour levels were decreased by increasing upstream roughness.

Keywords: forward facing step, open channel, separated and reattached turbulent flows, wall roughness

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Authors: Haohao Wang

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Technology, multimedia in Open Educational Resources, can contribute positively to student performance in an online instructional environment. Student performance data of past four years were obtained from an online course entitled Applied Calculus (MA139). This paper examined the data to determine whether multimedia (independent variable) had any impact on student performance (dependent variable) in online math learning, and how students felt about the value of the technology. Two groups of student data were analyzed, group 1 (control) from the online applied calculus course that did not use multimedia instructional materials, and group 2 (treatment) of the same online applied calculus course that used multimedia instructional materials. For the MA139 class, results indicate a statistically significant difference (p = .001) between the two groups, where group 1 had a final score mean of 56.36 (out of 100), group 2 of 70.68. Additionally, student testimonials were discussed in which students shared their experience in learning applied calculus online with multimedia instructional materials.

Keywords: online learning, open educational resources, multimedia, technology

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Authors: Sunil Kumar Singal, Manoj Sood, Upendra Bajpai

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Instream technology is the upcoming sustainable approach in the hydro sector for energy harnessing. With well-known cross-sections and regulated supply, open channels are the most prominent locations for the installation of hydrokinetic turbines. The fluctuation in generated torque varies with site condition (flow depth and flow velocity), as well as with the type of turbine. The present experimental study aims to investigate the torque/power fluctuations of crossflow hydrokinetic turbines operating at different flow velocities and water depths. The flow velocity is varied from 1.0 m/s to 2.0 m/s. The complete assembly includes an open channel having dimensions of 0.3 m (depth) x 0.71 m (width) x 4.5 m (length), along with a lifting mechanism for varying the channel slope, a digital transducer for monitoring the torque, power, and rpm, a digital handheld water velocity meter for measuring the flow velocity. Further, a time series of torque, power, and rpm is plotted for a duration of 30 minutes showing the continuous operation of the turbine. A comparison of Savonius, Darrieus, and their improved twisted and helical blades is also presented in the study. A correlation has also been developed for assessing the hydropower generation from the installed turbine. The developed correlations will be very useful in the decision-making process for development at a site.

Keywords: darrieus turbine, flow velocity, open channel, savoinus turbine, water depth, hydropower

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Authors: Gabriel Quintero

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This paper presents the result of the implementation of a series of algorithms intended to be used for representing in most of the 3D geographic software, even Google Earth, the subsurface formations properties combining 2D charts or 3D plots over a 3D background, allowing everyone to use them, no matter the economic size of the company for which they work. Besides the existence of complex and expensive specialized software for modeling subsurface formations based on the same information provided to this one, the use of this open source development shows a higher and easier usability and good results, limiting the rendered properties and polygons to a basic set of charts and tubes.

Keywords: chart, earth, formations, subsurface, visualization

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Authors: E. Keramaris

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In this study, laboratory experiments in open channel flows over a sand bed were conducted. A porous bed (sand bed) with porosity of ε=0.70 and porous thickness of s΄=3 cm was tested. Vertical distributions of velocity were evaluated by using a two-dimensional (2D) Particle Image Velocimetry (PIV). Velocity profiles are measured above the impermeable bed and above the sand bed for the same different total water heights (h= 6, 8, 10 and 12 cm) and for the same slope S=1.5. Measurements of mean velocity indicate the effects of the bed material used (sand bed) on the flow characteristics (Velocity distribution and Reynolds number) in comparison with those above the impermeable bed.

Keywords: particle image velocimetry, sand bed, velocity distribution, Reynolds number

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Authors: Sam Solaimani, Jack A. A. van der Veen, Mehdi Latifi

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Considering the increasingly VUCA (Volatile, Uncertain, Complex, Ambiguous) business market, innovation is the name of the game in contemporary business. Innovation is not solely created within the organization itself; its 'network environment' appears to be equally important for innovation. There are, at least, two streams of literature that emphasize the idea of using the extended organization to foster innovation capability, namely, Supply Chain Collaboration (SCC) (also rooted in the Lean philosophy) and Open Innovation (OI). Remarkably, these two concepts are still considered as being totally different in the sense that these appear in different streams of literature and applying different concepts in pursuing the same purposes. This paper explores the commonalities between the two concepts in order to conceptually further our understanding of how OI can effectively be applied in Supply Chain networks. Drawing on available literature in OI, SCC and Lean, the paper concludes with five principles that help firms to contextualize the implementation of OI to the peculiar setting of SC. Theoretically, the present paper aims at contributing to the relatively under-researched theme of Supply Chain Innovation. More in practical terms, the paper provides OI and SCC communities with a workable know-how to seize on and sustain OI initiatives.

Keywords: lean philosophy, open innovation, supply chain collaboration, supply chain management

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Authors: Naila Naseer

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Emotional Intelligence (EI) concept is not new yet unique and interesting. EI is a person’s ability to be aware of his/her own emotions and to manage, handle and communicate emotions with others effectively. The present study was conducted to assess the relationship between emotional intelligence and age of graduate level students at Allama Iqbal Open University (AIOU). Population consisted of Allama Iqbal Open University students (B.Ed 3rd Semester, Autumn 2007) from Rawalpindi and Islamabad regions. Total number of sample consisted of 469 participants was randomly drawn out by using table of random numbers. Bar-On EQ-i was administered on the participants through personal contact. The instrument was also validated through pilot study on a random sample of 50 participants (B.Ed students Spring 2006), who had completed their B.Ed degree successfully. Data was analyzed and tabulated in percentages, frequencies, mean, standard deviation, correlation, and scatter gram in SPSS (version 16.0 for windows). The results revealed that students with higher age group had scored low on the scale (Bar-On EQ-i). Moreover, the students in low age groups exhibited higher levels of EI as compared with old age students.

Keywords: emotional intelligence, age level, learning, emotion-related feelings

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Authors: Yassine Mehros, Jean-Michel Degeorge, Abdelaziz Elabjani

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Innovation has long been considered the key to the survival, development, and growth of companies. It is a process in which start-ups play a key role, but they suffer from a structural lack of resources, which hinders the development of new innovations and their commercialization. The use of alternative channels to access resources is therefore becoming a necessity to overcome this constraint and identify opportunities. This is why they can be part of large communities of interdependent actors, namely innovation ecosystems that are part of a logic of sharing and open innovation. This research aims to explore and better understand OI in start-ups within an innovation ecosystem. We offer an exploratory qualitative study with start-ups and other actors in the Saint-Étienne innovation ecosystem. Our paper explored the characteristics and main actors of the Saint-Etienne innovation ecosystem, focusing on start-ups. We have identified the motivations of start-up’s adopting OI, its difficulties, its risks, and its impact on their growth. Also, our results show the existence of strong links between the different actors in the ecosystem. In addition, a strong trust has been established between these actors thanks to the geographical proximity; the start-ups manage to get in touch with the different actors of their innovation ecosystem by practicing OI. The actors collaborate on projects involving companies and, in particular, start-ups.

Keywords: open innovation, start-ups, Innovation ecosystem, actors

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Authors: Kyung Bae Park, Sung Ho Ha

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

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

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Authors: Sokkhey Phauk, Takeo Okazaki

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

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

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Authors: Polina Pekker

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This work analyzes the role of lecturers in e-learning in Russia. It is based on qualitative research of lecturers who conduct courses on Russian national platforms of open education. The platform is based on edx software (provider of massive open online courses). The interviews with e-learning lecturers were conducted: from December 2015 till January 2016 and from April 2016 till May 2016. The results of interviews (face-to-face, telephone, skype) show, firstly, the difference between the role of lecturers in e-learning and in traditional education and, secondly, that the competition between lecturers is high in Russia. The results of interviews in Russia show that e-learning lecturer should have several special professional competences: the ability to keep attention of audiences without real contact, the ability to work on camera and competences related with e-learning course support (test, forum, communication on forum and etc.) It is concluded that lecturers need special course on acting and speech skills and on conducting and organizing of e-learning course in Russia. It is planned to conduct French study. When results from French research will be totally ready, they will be compared to Russian. As well French platform, France Universite Numerique, was launched earlier, in January 2014, so Russian lecturers should get best practice from the French colleagues.

Keywords: e-courses lecturer, e-learning, professional competences of lecturers, national Russian and French platforms of open education

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

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

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

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Rakibul Islam Sagor, Sadia Ibnat Raisa

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Many nations across the globe, including Dhaka, are facing challenges in meeting the needs for a satisfactory quality of life due to the combination of a growing population and limited land resources. As a result, maximum spaces in modern cities are engulfed by concrete infrastructure, and there are hardly any open spaces in the urban neighborhoods. Although vertical movement has predominantly been employed for residential and commercial applications, the notion of vertical recreational and sports facilities remains unsettled. The primary objective of this study is to explore the feasibility of implementing vertical adaptations in urban recreational spaces, drawing upon the principles of high-rise theory. This article presents an analysis of the open spaces in Gulshan, Dhaka, focusing on the evaluation of the demand for open recreational and sports facilities that adequately cater to the existing population of the region. Initially, the study tried to identify and examine all potential open spaces within the designated area. Following that, an acceptable place is selected utilizing space syntax analysis, which takes into account the most conveniently accessible space for social interactions in the neighborhood. In addition, socioeconomic conditions of the area have been studied in order to determine the feasibility of the area. Finally, the study presented viable options for vertical urban sports facilities in the context of Dhaka, Bangladesh. Additionally, it seeks to develop strategies for maximizing the use of vertical expansions, thereby promoting a healthier and more active lifestyle among the city's residents. This approach aims to effectively handle the issue of limited land availability and enhance the efficiency of recreational areas around the globe.

Keywords: vertical sports, urban open spaces, social interaction, recreational activities

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

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

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

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Authors: Minami Ito, Akihiro Iijima

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

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

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Authors: Yusri Yusof, Kamran Latif

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Computer Numeric Control (CNC) machine has been widely used in the industries since its inception. Currently, in CNC technology has been used for various operations like milling, drilling, packing and welding etc. with the rapid growth in the manufacturing world the demand of flexibility in the CNC machines has rapidly increased. Previously, the commercial CNC failed to provide flexibility because its structure was of closed nature that does not provide access to the inner features of CNC. Also CNC’s operating ISO data interface model was found to be limited. Therefore, to overcome that problem, Open Architecture Control (OAC) technology and STEP-NC data interface model are introduced. At present the Personal Computer (PC) has been the best platform for the development of open-CNC systems. In this paper, both ISO data interface model interpretation, its verification and execution has been highlighted with the introduction of the new techniques. The proposed is composed of ISO data interpretation, 3D simulation and machine motion control modules. The system is tested on an old 3 axis CNC milling machine. The results are found to be satisfactory in performance. This implementation has successfully enabled sustainable manufacturing environment.

Keywords: CNC, ISO 6983, ISO 14649, LabVIEW, open architecture control, reconfigurable manufacturing systems, sustainable manufacturing, Soft-CNC

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

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

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

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Authors: Anshar Ajatasatru

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

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

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Authors: Nuzhat Sharmin

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Human being is the most integral part of the nature and responsible for maintaining ecological balance both in rural and urban areas. But unfortunately, we are not doing our job with a holistic approach. The rapid growth of urbanization is making human life more isolated from greenery. Nowadays modern urban living involves sensory deprivation and overloaded stress. In many cities and towns of the world are expanding unabated in the name of urbanization and industrialization and in fact becoming jungles of concrete. Dhaka is one of the examples of such cities where open and green spaces are decreasing because of accommodating the overflow of population. This review paper has been prepared based on interviewing 30 teenagers, both male and female in Dhaka city. There were 12 open-ended questions in the questionnaire. For the literature review information had been gathered from scholarly papers published in various peer-reviewed journals. Some information was collected from the newspapers and some from fellow colleagues working around the world. Ideally about 25% of an urban area should be kept open or with parks, fields and/or plants and vegetation. But currently Dhaka has only about 10-12% open space and these also are being filled up rapidly. Old Dhaka has only about 5% open space while the new Dhaka has about 12%. Dhaka is now one of the most populated cities in the world. Accommodating this huge influx of people Dhaka is continuously losing its open space. As a result, children and teenagers are losing their interest in playing games and making friends, rather they are mostly occupied by television, gadgets and social media. It has been known from the interview that only 28% of teenagers regularly play. But the majority of them have to play on the street and rooftop for the lack of open space. On an average they are occupied with electronic devices for 8.3 hours/day. 64% of them has chronic diseases and often visit doctors. Most shockingly 35% of them claimed for not having any friends. Green space offers relief from stress. Areas of natural environment in towns and cities are theoretically seen providing setting for recovery and recuperation from anxiety and strains of the urban environment. Good quality green spaces encourage people to walk, run, cycle and play. Green spaces improve air quality and reduce noise, while trees and shrubbery help to filter out dust and pollutants. Relaxation, contemplation and passive recreation are essential to stress management. All city governments that are losing its open spaces should immediately pay attention to this aesthetic issue for the benefit of urban people. All kinds of development must be sustainable both for human being and nature.

Keywords: greenery, health, human, urban

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

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

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

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Authors: Maja Jokić, Andrea Mervar, Stjepan Mateljan

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Peer review journals, as the main communication channel among researchers, fully achieve their objective if they are available to the global research community, which is accomplished through open access. In the EU countries, the idea of open access has spread over the years through various projects, initiatives, and strategic documents. Consequently, in this paper we want to analyze, using various bibliometric indicators, visibility, and significance of open access peer review journals compared to the conventional (non-open access) ones. We examine the sample of open access (OA) journals in 28 EU countries in addition to open access journals in three EU candidate countries (Bosnia and Herzegovina, FYR Macedonia and Serbia), all indexed by Scopus (N=1,522). These journals comprise 42% of the total number of OA journals indexed by Scopus. The distribution of OA journals in our sample according to the subject fields indicates that the largest share has OA journals in Health Sciences, 29% followed by Social Sciences and Physical Sciences with 25%, and 21% in Life Sciences. At the same time, the distribution according to countries (N=31) shows the dominance of EU15 countries with the share of 68.3% (N=1041) while post-socialist European countries (EU11 plus three candidate EU countries) have the share of 31.6% (N=481). Bibliometric indicators are derived from the SCImago Journal Ranking database. The analysis of OA journals according to their quartile scores (that reflect the relation between number of articles and their citations) shows that the largest number of OA journals from our sample was in the third quartile in 2015. For comparison, the majority of all academic journals indexed in Scopus from the countries in our sample were in the same year in the first quartile. The median of SJR indicator (SCImago Journal Rankings) for 2015 that measures the journal's prestige, amounted 0.297 for OA journals from the sample, while it was modestly lower for all OA journals, 0.284. The value of the same indicator for all journals indexed by Scopus (N=11,086) from our group of countries was 0.358, which is significantly different from the one for OA journals. Apart from the number of OA journals we also confirm significant differences between EU15 and post-socialist countries in bibliometric status of OA journals. The median SJR indicator for 2015 for EU15 countries was 0.394, while for post-socialist countries it amounted to 0.226. The changes in bibliometric indicators: quartile score, SJR (SCImago Journal Rankings), SNIP (Sources Normalised Impact by Paper) and IPP (Impact per Publication) of OA journals during 2012-2015 period, as well as H-index for the main four subject fields (Life Sciences, Physical Sciences, Social Sciences and Health Sciences) in the whole sample as well as in two main groups of European countries, show increasing trend of acceptance and visibility of OA journals within the academic community. More comprehensive insights into the visibility of OA journals could be reached by using additional qualitative research methods such as for example, interviews with researchers.

Keywords: bibliometric analysis, European countries, journal evaluation, open access journals

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

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

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

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Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

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Authors: Dasom Kim, William Xiu Shun Wong, Yoonjin Hyun, Donghoon Lee, Minji Paek, Sungho Byun, Namgyu Kim

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There have been many researches on document classification for classifying voluminous documents automatically. Through document classification, we can assign a specific category to each unlabeled document on the basis of various machine learning algorithms. However, providing labeled documents manually requires considerable time and effort. To overcome the limitations, the semi-supervised learning which uses unlabeled document as well as labeled documents has been invented. However, traditional document classifiers, regardless of supervised or semi-supervised ones, cannot sufficiently explain the reason or the process of the classification. Thus, in this paper, we proposed a methodology to visualize major topics and class components of each document. We believe that our methodology for visualizing topics and classes of each document can enhance the reliability and explanatory power of document classifiers.

Keywords: data mining, document classifier, text mining, topic modeling

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Authors: Faiza Hussain, Usman Qamar

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Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

Procedia PDF Downloads 306