Search results for: graph mining
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1482

Search results for: graph mining

312 Recommender Systems Using Ensemble Techniques

Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

Abstract:

This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

Procedia PDF Downloads 276
311 Structuring Paraphrases: The Impact Sentence Complexity Has on Key Leader Engagements

Authors: Meaghan Bowman

Abstract:

Soldiers are taught about the importance of effective communication with repetition of the phrase, “Communication is key.” They receive training in preparing for, and carrying out, interactions between foreign and domestic leaders to gain crucial information about a mission. These interactions are known as Key Leader Engagements (KLEs). For the training of KLEs, doctrine mandates the skills needed to conduct these “engagements” such as how to: behave appropriately, identify key leaders, and employ effective strategies. Army officers in training learn how to confront leaders, what information to gain, and how to ask questions respectfully. Unfortunately, soldiers rarely learn how to formulate questions optimally. Since less complex questions are easier to understand, we hypothesize that semantic complexity affects content understanding, and that age and education levels may have an effect on one’s ability to form paraphrases and judge their quality. In this study, we looked at paraphrases of queries as well as judgments of both the paraphrases’ naturalness and their semantic similarity to the query. Queries were divided into three complexity categories based on the number of relations (the first number) and the number of knowledge graph edges (the second number). Two crowd-sourced tasks were completed by Amazon volunteer participants, also known as turkers, to answer the research questions: (i) Are more complex queries harder to paraphrase and judge and (ii) Do age and education level affect the ability to understand complex queries. We ran statistical tests as follows: MANOVA for query understanding and two-way ANOVA to understand the relationship between query complexity and education and age. A probe of the number of given-level queries selected for paraphrasing by crowd-sourced workers in seven age ranges yielded promising results. We found significant evidence that age plays a role and marginally significant evidence that education level plays a role. These preliminary tests, with output p-values of 0.0002 and 0.068, respectively, suggest the importance of content understanding in a communication skill set. This basic ability to communicate, which may differ by age and education, permits reproduction and quality assessment and is crucial in training soldiers for effective participation in KLEs.

Keywords: engagement, key leader, paraphrasing, query complexity, understanding

Procedia PDF Downloads 145
310 An Assessment of the Impacts of Agro-Ecological Practices towards the Improvement of Crop Health and Yield Capacity: A Case of Mopani District, Limpopo, South Africa

Authors: Tshilidzi C. Manyanya, Nthaduleni S. Nethengwe, Edmore Kori

Abstract:

The UNFCCC, FAO, GCF, IPCC and other global structures advocate for agro-ecology do address food security and sovereignty. However, most of the expected outcomes concerning agro-ecological were not empirically tested for universal application. Agro-ecology is theorised to increase crop health over ago-ecological farms and decrease over conventional farms. Increased crop health means increased carbon sequestration and thus less CO2 in the atmosphere. This is in line with the view that global warming is anthropogenically enhanced through GHG emissions. Agro-ecology mainly affects crop health, soil carbon content and yield on the cultivated land. Economic sustainability is directly related to yield capacity, which is theorized to increase by 3-10% in a space of 3 - 10 years as a result of agro-ecological implementation. This study aimed to empirically assess the practicality and validity of these assumptions. The study utilized mainly GIS and RS techniques to assess the effectiveness of agro-ecology in crop health improvement from satellite images. The assessment involved a longitudinal study (2013 – 2015) assessing the changes that occur after a farm retrofits from conventional agriculture to agro-ecology. The assumptions guided the objectives of the study. For each objective, an agro-ecological farm was compared with a conventional farm in the same climatic conditional occupying the same general location. Crop health was assessed using satellite images analysed through ArcGIS and Erdas. This entailed the production of NDVI and Re-classified outputs of the farm area. The NDVI ranges of the entire period of study were thus compared in a stacked histogram for each farm to assess for trends. Yield capacity was calculated based on the production records acquired from the farmers and plotted in a stacked bar graph as percentages of a total for each farm. The results of the study showed decreasing crop health trends over 80% of the conventional farms and an increase over 80% of the organic farms. Yield capacity showed similar patterns to those of crop health. The study thus showed that agro-ecology is an effective strategy for crop-health improvement and yield increase.

Keywords: agro-ecosystem, conventional farm, dialectical, sustainability

Procedia PDF Downloads 196
309 Evaluation of Drilling Performance through Bit-Rock Interaction Using Passive Vibration Assisted Rotation Drilling (PVARD) Tool

Authors: Md. Shaheen Shah, Abdelsalam Abugharara, Dipesh Maharjan, Syed Imtiaz, Stephen Butt

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Drilling performance is an essential goal in petroleum and mining industry. Drilling rate of penetration (ROP), which is inversely proportional to the mechanical specific energy (MSE) is influenced by numerous factors among which are the applied parameter: torque (T), weight on bit (WOB), fluid flow rate, revolution per minute (rpm), rock related parameters: rock type, rock homogeneousness, rock anisotropy orientation, and mechanical parameters: bit type, configuration of the bottom hole assembly (BHA). This paper is focused on studying the drilling performance by implementing a passive vibration assisted rotary drilling tool (pVARD) as part of the BHA through using different bit types: coring bit, roller cone bit, and PDC bit and various rock types: rock-like material, granite, sandstone, etc. The results of this study aim to produce a pVARD index for optimal drilling performance considering the recommendations of the pVARD’s spring compression tests and stress-strain analysis of rock samples conducted prior to drilling experiments, analyzing the cutting size distribution, and evaluating the applied drilling parameters as a function of WOB. These results are compared with those obtained from drilling without pVARD, which represents the typical rigid BHA of the conventional drilling.

Keywords: BHA, drilling performance, MSE, pVARD, rate of penetration, ROP, tensile and shear fractures, unconfined compressive strength

Procedia PDF Downloads 130
308 Mathematical modeling of the calculation of the absorbed dose in uranium production workers with the genetic effects.

Authors: P. Kazymbet, G. Abildinova, K.Makhambetov, M. Bakhtin, D. Rybalkina, K. Zhumadilov

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Conducted cytogenetic research in workers Stepnogorsk Mining-Chemical Combine (Akmola region) with the study of 26341 chromosomal metaphase. Using a regression analysis with program DataFit, version 5.0, dependence between exposure dose and the following cytogenetic exponents has been studied: frequency of aberrant cells, frequency of chromosomal aberrations, frequency of the amounts of dicentric chromosomes, and centric rings. Experimental data on calibration curves "dose-effect" enabled the development of a mathematical model, allowing on data of the frequency of aberrant cells, chromosome aberrations, the amounts of dicentric chromosomes and centric rings calculate the absorbed dose at the time of the study. In the dose range of 0.1 Gy to 5.0 Gy dependence cytogenetic parameters on the dose had the following equation: Y = 0,0067е^0,3307х (R2 = 0,8206) – for frequency of chromosomal aberrations; Y = 0,0057е^0,3161х (R2 = 0,8832) –for frequency of cells with chromosomal aberrations; Y =5 Е-0,5е^0,6383 (R2 = 0,6321) – or frequency of the amounts of dicentric chromosomes and centric rings on cells. On the basis of cytogenetic parameters and regression equations calculated absorbed dose in workers of uranium production at the time of the study did not exceed 0.3 Gy.

Keywords: Stepnogorsk, mathematical modeling, cytogenetic, dicentric chromosomes

Procedia PDF Downloads 456
307 Comparative Sustainability Performance Analysis of Australian Companies Using Composite Measures

Authors: Ramona Zharfpeykan, Paul Rouse

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Organizational sustainability is important to both organizations themselves and their stakeholders. Despite its increasing popularity and increasing numbers of organizations reporting sustainability, research on evaluating and comparing the sustainability performance of companies is limited. The aim of this study was to develop models to measure sustainability performance for both cross-sectional and longitudinal comparisons across companies in the same or different industries. A secondary aim was to see if sustainability reports can be used to evaluate sustainability performance. The study used both a content analysis of Australian sustainability reports in mining and metals and financial services for 2011-2014 and a survey of Australian and New Zealand organizations. Two methods ranging from a composite index using uniform weights to data envelopment analysis (DEA) were employed to analyze the data and develop the models. The results show strong statistically significant relationships between the developed models, which suggests that each model provides a consistent, systematic and reasonably robust analysis. The results of the models show that for both industries, companies that had sustainability scores above or below the industry average stayed almost the same during the study period. These indices and models can be used by companies to evaluate their sustainability performance and compare it with previous years, or with other companies in the same or different industries. These methods can also be used by various stakeholders and sustainability ranking companies such as the Global Reporting Initiative (GRI).

Keywords: data envelopment analysis, sustainability, sustainability performance measurement system, sustainability performance index, global reporting initiative

Procedia PDF Downloads 156
306 Strategic Mine Planning: A SWOT Analysis Applied to KOV Open Pit Mine in the Democratic Republic of Congo

Authors: Patrick May Mukonki

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KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately 10 years withnice pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long-term mine plan for a big copper mine such as KOV pit. The approach taken, discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in this paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. The same logic is applied in terms of the opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high grade ore body.

Keywords: mine planning, mine optimization, mine scheduling, SWOT analysis

Procedia PDF Downloads 210
305 Short Answer Grading Using Multi-Context Features

Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

Procedia PDF Downloads 117
304 Recursion, Merge and Event Sequence: A Bio-Mathematical Perspective

Authors: Noury Bakrim

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Formalization is indeed a foundational Mathematical Linguistics as demonstrated by the pioneering works. While dialoguing with this frame, we nonetheless propone, in our approach of language as a real object, a mathematical linguistics/biosemiotics defined as a dialectical synthesis between induction and computational deduction. Therefore, relying on the parametric interaction of cycles, rules, and features giving way to a sub-hypothetic biological point of view, we first hypothesize a factorial equation as an explanatory principle within Category Mathematics of the Ergobrain: our computation proposal of Universal Grammar rules per cycle or a scalar determination (multiplying right/left columns of the determinant matrix and right/left columns of the logarithmic matrix) of the transformable matrix for rule addition/deletion and cycles within representational mapping/cycle heredity basing on the factorial example, being the logarithmic exponent or power of rule deletion/addition. It enables us to propone an extension of minimalist merge/label notions to a Language Merge (as a computing principle) within cycle recursion relying on combinatorial mapping of rules hierarchies on external Entax of the Event Sequence. Therefore, to define combinatorial maps as language merge of features and combinatorial hierarchical restrictions (governing, commanding, and other rules), we secondly hypothesize from our results feature/hierarchy exponentiation on graph representation deriving from Gromov's Symbolic Dynamics where combinatorial vertices from Fe are set to combinatorial vertices of Hie and edges from Fe to Hie such as for all combinatorial group, there are restriction maps representing different derivational levels that are subgraphs: the intersection on I defines pullbacks and deletion rules (under restriction maps) then under disjunction edges H such that for the combinatorial map P belonging to Hie exponentiation by intersection there are pullbacks and projections that are equal to restriction maps RM₁ and RM₂. The model will draw on experimental biomathematics as well as structural frames with focus on Amazigh and English (cases from phonology/micro-semantics, Syntax) shift from Structure to event (especially Amazigh formant principle resolving its morphological heterogeneity).

Keywords: rule/cycle addition/deletion, bio-mathematical methodology, general merge calculation, feature exponentiation, combinatorial maps, event sequence

Procedia PDF Downloads 110
303 Synergy Effect of Energy and Water Saving in China's Energy Sectors: A Multi-Objective Optimization Analysis

Authors: Yi Jin, Xu Tang, Cuiyang Feng

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The ‘11th five-year’ and ‘12th five-year’ plans have clearly put forward to strictly control the total amount and intensity of energy and water consumption. The synergy effect of energy and water has rarely been considered in the process of energy and water saving in China, where its contribution cannot be maximized. Energy sectors consume large amounts of energy and water when producing massive energy, which makes them both energy and water intensive. Therefore, the synergy effect in these sectors is significant. This paper assesses and optimizes the synergy effect in three energy sectors under the background of promoting energy and water saving. Results show that: From the perspective of critical path, chemical industry, mining and processing of non-metal ores and smelting and pressing of metals are coupling points in the process of energy and water flowing to energy sectors, in which the implementation of energy and water saving policies can bring significant synergy effect. Multi-objective optimization shows that increasing efforts on input restructuring can effectively improve synergy effects; relatively large synergetic energy saving and little water saving are obtained after solely reducing the energy and water intensity of coupling sectors. By optimizing the input structure of sectors, especially the coupling sectors, the synergy effect of energy and water saving can be improved in energy sectors under the premise of keeping economy running stably.

Keywords: critical path, energy sector, multi-objective optimization, synergy effect, water

Procedia PDF Downloads 345
302 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

Procedia PDF Downloads 390
301 Multi-Source Data Fusion for Urban Comprehensive Management

Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

Procedia PDF Downloads 366
300 Mining the Proteome of Fusobacterium nucleatum for Potential Therapeutics Discovery

Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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299 Numerical Simulation of Fracturing Behaviour of Pre-Cracked Crystalline Rock Using a Cohesive Grain-Based Distinct Element Model

Authors: Mahdi Saadat, Abbas Taheri

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Understanding the cracking response of crystalline rocks at mineralogical scale is of great importance during the design procedure of mining structures. A grain-based distinct element model (GBM) is employed to numerically study the cracking response of Barre granite at micro- and macro-scales. The GBM framework is augmented with a proposed distinct element-based cohesive model to reproduce the micro-cracking response of the inter- and intra-grain contacts. The cohesive GBM framework is implemented in PFC2D distinct element codes. The microstructural properties of Barre granite are imported in PFC2D to generate synthetic specimens. The microproperties of the model is calibrated against the laboratory uniaxial compressive and Brazilian split tensile tests. The calibrated model is then used to simulate the fracturing behaviour of pre-cracked Barre granite with different flaw configurations. The numerical results of the proposed model demonstrate a good agreement with the experimental counterparts. The GBM framework proposed thus appears promising for further investigation of the influence of grain microstructure and mineralogical properties on the cracking behaviour of crystalline rocks.

Keywords: discrete element modelling, cohesive grain-based model, crystalline rock, fracturing behavior

Procedia PDF Downloads 111
298 A Comparative Study on Supercritical C02 and Water as Working Fluids in a Heterogeneous Geothermal Reservoir

Authors: Musa D. Aliyu, Ouahid Harireche, Colin D. Hills

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The incapability of supercritical C02 to transport and dissolve mineral species from the geothermal reservoir to the fracture apertures and other important parameters in heat mining makes it an attractive substance for Heat extraction from hot dry rock. In other words, the thermodynamic efficiency of hot dry rock (HDR) reservoirs also increases if supercritical C02 is circulated at excess temperatures of 3740C without the drawbacks connected with silica dissolution. Studies have shown that circulation of supercritical C02 in homogenous geothermal reservoirs is quite encouraging; in comparison to that of the water. This paper aims at investigating the aforementioned processes in the case of the heterogeneous geothermal reservoir located at the Soultz site (France). The MultiPhysics finite element package COMSOL with an interface of coupling different processes encountered in the geothermal reservoir stimulation is used. A fully coupled numerical model is developed to study the thermal and hydraulic processes in order to predict the long-term operation of the basic reservoir parameters that give optimum energy production. The results reveal that the temperature of the SCC02 at the production outlet is higher than that of water in long-term stimulation; as the temperature is an essential ingredient in rating the energy production. It is also observed that the mass flow rate of the SCC02 is far more favourable compared to that of water.

Keywords: FEM, HDR, heterogeneous reservoir, stimulation, supercritical C02

Procedia PDF Downloads 366
297 A Framework for Event-Based Monitoring of Business Processes in the Supply Chain Management of Industry 4.0

Authors: Johannes Atug, Andreas Radke, Mitchell Tseng, Gunther Reinhart

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In modern supply chains, large numbers of SKU (Stock-Keeping-Unit) need to be timely managed, and any delays in noticing disruptions of items often limit the ability to defer the impact on customer order fulfillment. However, in supply chains of IoT-connected enterprises, the ERP (Enterprise-Resource-Planning), the MES (Manufacturing-Execution-System) and the SCADA (Supervisory-Control-and-Data-Acquisition) systems generate large amounts of data, which generally glean much earlier notice of deviations in the business process steps. That is, analyzing these streams of data with process mining techniques allows the monitoring of the supply chain business processes and thus identification of items that deviate from the standard order fulfillment process. In this paper, a framework to enable event-based SCM (Supply-Chain-Management) processes including an overview of core enabling technologies are presented, which is based on the RAMI (Reference-Architecture-Model for Industrie 4.0) architecture. The application of this framework in the industry is presented, and implications for SCM in industry 4.0 and further research are outlined.

Keywords: cyber-physical production systems, event-based monitoring, supply chain management, RAMI (Reference-Architecture-Model for Industrie 4.0)

Procedia PDF Downloads 214
296 A Patient Passport Application for Adults with Cystic Fibrosis

Authors: Tamara Vagg, Cathy Shortt, Claire Hickey, Joseph A. Eustace, Barry J. Plant, Sabin Tabirca

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Introduction: Paper-based patient passports have been used advantageously for older patients, patients with diabetes, and patients with learning difficulties. However, these passports can experience issues with data security, patients forgetting to bring the passport, patients being over encumbered, and uncertainty with who is responsible for entering and managing data in this passport. These issues could be resolved by transferring the paper-based system to a convenient platform such as a smartphone application (app). Background: Life expectancy for some Cystic Fibrosis (CF) patients are rising and as such new complications and procedures are predicted. Subsequently, there is a need for education and management interventions that can benefit CF adults. This research proposes a CF patient passport to record basic medical information through a smartphone app which will allow CF adults access to their basic medical information. Aim: To provide CF patients with their basic medical information via mobile multimedia so that they can receive care when traveling abroad or between CF centres. Moreover, by recording their basic medical information, CF patients may become more aware of their own condition and more active in their health care. Methods: This app is designed by a CF multidisciplinary team to be a lightweight reflection of a hospital patient file. The passport app is created using PhoneGap so that it can be deployed for both Android and iOS devices. Data entered into the app is encrypted and stored locally only. The app is password protected and includes the ability to set reminders and a graph to visualise weight and lung function over time. The app is introduced to seven participants as part of a stress test. The participants are asked to test the performance and usability of the app and report any issues identified. Results: Feedback and suggestions received via this testing include the ability to reorder the list of clinical appointments via date, an open format of recording dates (in the event specifics are unknown), and a drop down menu for data which is difficult to enter (such as bugs found in mucus). The app is found to be usable and accessible and is now being prepared for a pilot study with adult CF patients. Conclusions: It is anticipated that such an app will be beneficial to CF adult patients when travelling abroad and between CF centres.

Keywords: Cystic Fibrosis, digital patient passport, mHealth, self management

Procedia PDF Downloads 231
295 Optimised Path Recommendation for a Real Time Process

Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

Procedia PDF Downloads 315
294 Visual Text Analytics Technologies for Real-Time Big Data: Chronological Evolution and Issues

Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

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New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: information visualization, visual analytics, text mining, visual text analytics tools, big data visualization

Procedia PDF Downloads 383
293 Classification of Land Cover Usage from Satellite Images Using Deep Learning Algorithms

Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

Procedia PDF Downloads 124
292 Visual Template Detection and Compositional Automatic Regular Expression Generation for Business Invoice Extraction

Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

Procedia PDF Downloads 109
291 Anthropogenic Impact on Migration Process of River Yamuna in Delhi-NCR Using Geospatial Techniques

Authors: Mohd Asim, K. Nageswara Rao

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The present work was carried out on River Yamuna passing through Delhi- National Capital Region (Delhi-NCR) of India for a stretch of about 130 km to assess the anthropogenic impact on the channel migration process for a period of 200 years with the help of satellite data and topographical maps with integration of geographic information system environment. Digital Shoreline Analysis System (DSAS) application was used to quantify river channel migration in ArcGIS environment. The average river channel migration was calculated to be 22.8 m/year for the entire study area. River channel migration was found to be moving in westward and eastward direction. Westward migration is more than 4 km maximum in length and eastward migration is about 4.19 km. The river has migrated a total of 32.26 sq. km of area. The results reveal that the river is being impacted by various human activities. The impact indicators include engineering structures, sand mining, embankments, urbanization, land use/land cover, canal network. The DSAS application was also used to predict the position of river channel in future for 2032 and 2042 by analyzing the past and present rate and direction of movement. The length of channel in 2032 and 2042 will be 132.5 and 141.6 km respectively. The channel will migrate maximum after crossing Okhla Barrage near Faridabad for about 3.84 sq. km from 2022 to 2042 from west to east.

Keywords: river migration, remote sensing, river Yamuna, anthropogenic impacts, DSAS, Delhi-NCR

Procedia PDF Downloads 108
290 Implementation Association Rule Method in Determining the Layout of Qita Supermarket as a Strategy in the Competitive Retail Industry in Indonesia

Authors: Dwipa Rizki Utama, Hanief Ibrahim

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The development of industry retail in Indonesia is very fast, various strategy was undertaken to boost the customer satisfaction and the productivity purchases to boost the profit, one of which is implementing strategies layout. The purpose of this study is to determine the layout of Qita supermarket, a retail industry in Indonesia, in order to improve customer satisfaction and to maximize the rate of products’ sale as a whole, so as the infrequently purchased products will be purchased. This research uses a literature study method, and one of the data mining methods is association rule which applied in market basket analysis. Data were tested amounted 100 from 160 after pre-processing data, so then the distribution department and 26 departments corresponding to the data previous layout will be obtained. From those data, by the association rule method, customer behavior when purchasing items simultaneously can be studied, so then the layout of the supermarket based on customer behavior can be determined. Using the rapid miner software by the minimal support 25% and minimal confidence 30% showed that the 14th department purchased at the same time with department 10, 21st department purchased at the same time with department 13, 15th department purchased at the same time with department 12, 14th department purchased at the same time with department 12, and 10th department purchased at the same time with department 14. From those results, a better supermarket layout can be arranged than the previous layout.

Keywords: industry retail, strategy, association rule, supermarket

Procedia PDF Downloads 171
289 A Fuzzy-Rough Feature Selection Based on Binary Shuffled Frog Leaping Algorithm

Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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288 Intelligent Recognition of Diabetes Disease via FCM Based Attribute Weighting

Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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287 Geomechanics Properties of Tuzluca (Eastern. Turkey) Bedded Rock Salt and Geotechnical Safety

Authors: Mehmet Salih Bayraktutan

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Geomechanical properties of Rock Salt Deposits in Tuzluca Salt Mine Area (Eastern Turkey) are studied for modeling the operation- excavation strategy. The purpose of this research focused on calculating the critical value of span height- which will meet the safety requirements. The Mine Site Tuzluca Hills consist of alternating parallel bedding of Salt ( NaCl ) and Gypsum ( CaS04 + 2 H20) rocks. Rock Salt beds are more resistant than narrow Gypsum interlayers. Rock Salt beds formed almost 97 percent of the total height of the Hill. Therefore, the geotechnical safety of Galleries depends on the mechanical criteria of Rock Salt Cores. General deposition of Tuzluca Basin was finally completed by Tuzluca Evaporites, as for the uppermost stratigraphic unit. They are currently running mining operations performed by classic mechanical excavation, room and pillar method. Rooms and Pillars are currently experiencing an initial stage of fracturing in places. Geotechnical safety of the whole mining area evaluated by Rock Mass Rating (RMR), Rock Quality Designation (RQD) spacing of joints, and the interaction of groundwater and fracture system. In general, bedded rock salt Show large lateral deformation capacity (while deformation modulus stays in relative small values, here E= 9.86 GPa). In such litho-stratigraphic environments, creep is a critical mechanism in failure. Rock Salt creep rate in steady-state is greater than interbedding layers. Under long-lasted compressive stresses, creep may cause shear displacements, partly using bedding planes. Eventually, steady-state creep in time returns to accelerated stages. Uniaxial compression creep tests on specimens were performed to have an idea of rock salt strength. To give an idea, on Rock Salt cores, average axial strength and strain are found as 18 - 24 MPa and 0.43-0.45 %, respectively. Uniaxial Compressive strength of 26- 32 MPa, from bedded rock salt cores. Elastic modulus is comparatively low, but lateral deformation of the rock salt is high under the uniaxial compression stress state. Poisson ratio = 0.44, break load = 156 kN, cohesion c= 12.8 kg/cm2, specific gravity SG=2.17 gr/cm3. Fracture System; spacing of fractures, joints, faults, offsets are evaluated under acting geodynamic mechanism. Two sand beds, each 4-6 m thick, exist near to upper level and at the top of the evaporating sequence. They act as aquifers and keep infiltrated water on top for a long duration, which may result in the failure of roofs or pillars. Two major active seismic ( N30W and N70E ) striking Fault Planes and parallel fracture strands have seismically triggered moderate risk of structural deformation of rock salt bedding sequence. Earthquakes and Floods are two prevailing sources of geohazards in this region—the seismotectonic activity of the Mine Site based on the crossing framework of Kagizman Faults and Igdir Faults. Dominant Hazard Risk sources include; a) Weak mechanical properties of rock salt, gypsum, anhydrite beds-creep. b) Physical discontinuities cutting across the thick parallel layers of Evaporite Mass, c) Intercalated beds of weak cemented or loose sand, clayey sandy sediments. On the other hand, absorbing the effects of salt-gyps parallel bedded deposits on seismic wave amplitudes has a reducing effect on the Rock Mass.

Keywords: bedded rock salt, creep, failure mechanism, geotechnical safety

Procedia PDF Downloads 178
286 Simultaneous Measurement of Wave Pressure and Wind Speed with the Specific Instrument and the Unit of Measurement Description

Authors: Branimir Jurun, Elza Jurun

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The focus of this paper is the description of an instrument called 'Quattuor 45' and defining of wave pressure measurement. Special attention is given to measurement of wave pressure created by the wind speed increasing obtained with the instrument 'Quattuor 45' in the investigated area. The study begins with respect to theoretical attitudes and numerous up to date investigations related to the waves approaching the coast. The detailed schematic view of the instrument is enriched with pictures from ground plan and side view. Horizontal stability of the instrument is achieved by mooring which relies on two concrete blocks. Vertical wave peak monitoring is ensured by one float above the instrument. The synthesis of horizontal stability and vertical wave peak monitoring allows to create a representative database for wave pressure measuring. Instrument ‘Quattuor 45' is named according to the way the database is received. Namely, the electronic part of the instrument consists of the main chip ‘Arduino', its memory, four load cells with the appropriate modules and the wind speed sensor 'Anemometers'. The 'Arduino' chip is programmed to store two data from each load cell and two data from the anemometer on SD card each second. The next part of the research is dedicated to data processing. All measured results are stored automatically in the database and after that detailed processing is carried out in the MS Excel. The result of the wave pressure measurement is synthesized by the unit of measurement kN/m². This paper also suggests a graphical presentation of the results by multi-line graph. The wave pressure is presented on the left vertical axis, while the wind speed is shown on the right vertical axis. The time of measurement is displayed on the horizontal axis. The paper proposes an algorithm for wind speed measurements showing the results for two characteristic winds in the Adriatic Sea, called 'Bura' and 'Jugo'. The first of them is the northern wind that reaches high speeds, causing low and extremely steep waves, where the pressure of the wave is relatively weak. On the other hand, the southern wind 'Jugo' has a lower speed than the northern wind, but due to its constant duration and constant speed maintenance, it causes extremely long and high waves that cause extremely high wave pressure.

Keywords: instrument, measuring unit, waves pressure metering, wind seed measurement

Procedia PDF Downloads 183
285 Spreading Japan's National Image through China during the Era of Mass Tourism: The Japan National Tourism Organization’s Use of Sina Weibo

Authors: Abigail Qian Zhou

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Since China has entered an era of mass tourism, there has been a fundamental change in the way Chinese people approach and perceive the image of other countries. With the advent of the new media era, social networking sites such as Sina Weibo have become a tool for many foreign governmental organizations to spread and promote their national image. Among them, the Japan National Tourism Organization (JNTO) was one of the first foreign official tourism agencies to register with Sina Weibo and actively implement communication activities. Due to historical and political reasons, cognition of Japan's national image by the Chinese has always been complicated and contradictory. However, since 2015, China has become the largest source of tourists visiting Japan. This clearly indicates that the broadening of Japan's national image in China has been effective and has value worthy of reference in promoting a positive Chinese perception of Japan and encouraging Japanese tourism. Within this context and using the method of content analysis in media studies through content mining software, this study analyzed how JNTO’s Sina Weibo accounts have constructed and spread Japan's national image. This study also summarized the characteristics of its content and form, and finally revealed the strategy of JNTO in building its international image. The findings of this study not only add a tourism-based perspective to traditional national image communications research, but also provide some reference for the effective international dissemination of national image in the future.

Keywords: national image, international communication, tourism, Japan, China

Procedia PDF Downloads 111
284 Relationship between the Ability of Accruals and Non-Systematic Risk of Shares for Companies Listed in Stock Exchange: Case Study, Tehran

Authors: Lina Najafian, Hamidreza Vakilifard

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The present study focused on the relationship between the quality of accruals and non-systematic risk. The independent study variables included the ability of accruals, the information content of accruals, and amount of discretionary accruals considered as accruals quality measures. The dependent variable was non-systematic risk based on the Fama and French Three Factor model (FFTFM) and the capital asset pricing model (CAPM). The control variables were firm size, financial leverage, stock return, cash flow fluctuations, and book-to-market ratio. The data collection method was based on library research and document mining including financial statements. Multiple regression analysis was used to analyze the data. The study results showed that there is a significant direct relationship between financial leverage and discretionary accruals and non-systematic risk based on FFTFM and CAPM. There is also a significant direct relationship between the ability of accruals, information content of accruals, firm size, and stock return and non-systematic based on both models. It was also found that there is no relationship between book-to-market ratio and cash flow fluctuations and non-systematic risk.

Keywords: accruals quality, non-systematic risk, CAPM, FFTFM

Procedia PDF Downloads 142
283 Fraud in the Higher Educational Institutions in Assam, India: Issues and Challenges

Authors: Kalidas Sarma

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Fraud is a social problem changing with social change and it has a regional and global impact. Introduction of private domain in higher education along with public institutions has led to commercialization of higher education which encourages unprecedented mushrooming of private institutions resulting in fraudulent activities in higher educational institutions in Assam, India. Presently, fraud has been noticed in in-service promotion, fake entry qualification by teachers in different levels of work-place by using fake master degrees, master of philosophy and doctor of philosophy degree certificates. The aim and objective of the study are to identify grey areas in maintenance of quality in higher educational institutions in Assam and also to draw the contour for planning and implementation. This study is based on both primary and secondary data collected through questionnaire and seeking information through Right to Information Act 2005. In Assam, there are 301 undergraduate and graduate colleges distributed in 27 (Twenty seven) administrative districts with 11000 (Eleven thousand) college teachers. Total 421 (Four hundred twenty one) college teachers from the 14 respondent colleges have been taken for analysis. Data collected has been analyzed by using 'Hypertext Pre-processor' (PhP) application with My Sequel Structure Query Language (MySQL) and Google Map Application Programming Interface (APIs). Graph has been generated by using open source tool Chart.js. Spatial distribution maps have been generated with the help of geo-references of the colleges. The result shows: (i) the violation of University Grants Commission's (UGCs) Regulation for the awards of M. Phil/Ph.D. clearly exhibits. (ii) There is a gap between apex regulatory bodies of higher education at national and as well as state level to check fraud. (iii) Mala fide 'No Objection Certificate' (NOC) issued by the Government of Assam have played pivotal role in the occurrence of fraudulent practices in higher educational institutions of Assam. (iv) Violation of verdict of the Hon'ble Supreme Court of India regarding territorial jurisdiction of Universities for the awards of Ph.D. and M. Phil degrees in distance mode/study centre is also a responsible factor for the spread of these academic frauds in Assam and other states. The challenges and mitigation of these issues have been discussed.

Keywords: Assam, fraud, higher education, mitigation

Procedia PDF Downloads 149