Search results for: housing data

Authors: Djelloul Benatiallah, Ali Benatiallah, Abdelkader Harouz

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Geographic Information Systems (GIS) include various methods and computer techniques to model, capture digitally, store, manage, view and analyze. Geographic information systems have the characteristic to appeal to many scientific and technical field, and many methods. In this article we will present a complete and operational geographic information system, following the theoretical principles of data management and adapting to spatial data, especially data concerning the monitoring of drinking water supply wells (DWS) Adrar region. The expected results of this system are firstly an offer consulting standard features, updating and editing beneficiaries and geographical data, on the other hand, provides specific functionality contractors entered data, calculations parameterized and statistics.

Keywords: GIS, DWS, drilling, Adrar

Procedia PDF Downloads 309

Authors: S. Habte, K. Ouazzane, P. Patel, S. Patel

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The dynamic and highly competitive nature of the consumer electronics retail industry means that businesses in this industry are experiencing different decision making challenges in relation to pricing, inventory control, consumer satisfaction and product offerings. To overcome the challenges facing retailers and create opportunities, we propose a generic data warehousing solution which can be applied to a wide range of consumer electronics retailers with a minimum configuration. The solution includes a dimensional data model, a template SQL script, a high level architectural descriptions, ETL tool developed using C#, a set of APIs, and data access tools. It has been successfully applied by ASK Outlets Ltd UK resulting in improved productivity and enhanced sales growth.

Keywords: consumer electronics, data warehousing, dimensional data model, generic, retail industry

Procedia PDF Downloads 411

Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

Procedia PDF Downloads 574

Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

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This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, traffic, weigh-in-motion, axle load distribution

Procedia PDF Downloads 343

Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

Procedia PDF Downloads 461

Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

Procedia PDF Downloads 185

Authors: Elvis Munyoka

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While the number of African refugees settling in Australia has significantly increased since the mid-1990s, the marginalisation and exclusion of young people from refugee backgrounds in employment remain a critical challenge. Unemployment or underemployment can negatively impact refugees in multiple areas, such as income, housing, life satisfaction, and social status. Higher rates of unemployment among refugees are linked in part to the intersection of pre-migration and daily challenges like trauma, racism, gender identity, and English language competency, all of which generate multiple employability disadvantages. However, the intersection of gender, race, social class, and age in impacting African refugee youth’s access to employment has received less attention. Using a qualitative case study approach, the presentation will explore how gender, race, social class, and age influence African refugee youth graduates’ access to employment in South Australia. The intersectionality theory and capability approach to social justice is used to explore intersecting factors impacting African refugee youth’s access to employment in South Australia. Participants were 16 African refugee graduates aged 18-30 living in South Australia who took part in the study for one year. Based on the trends in the data, the results suggest that long-term unemployment and underemployment, coupled with ongoing racism and marginalisation, have the potential to make refugees more vulnerable to several mental disorders such as depression, hopelessness, and suicidal thoughts. The analysis also reveals that resettlement challenges may limit refugees’ ability to recover from pre-migration trauma. The impact of resettlement challenges on refugee mental health highlights the need for comprehensive policy interventions to address the barriers refugees face in finding employment in resettlement communities. With African refugees constituting such an important part of Australian society, they should have equal access to meaningful employment, as decent work promotes good mental health, successful resettlement, hope, and self-sufficiency.

Keywords: African refugees, employment, mental health, Australia, underemployment

Procedia PDF Downloads 102

Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

Procedia PDF Downloads 259

Authors: Harold P. Villota, Alejandro Osorio B.

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The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

Procedia PDF Downloads 164

Authors: Jeni Stolow, Lina Moses, Carl Kendall

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Zika virus (ZIKV) reemerged as a global threat in 2015 with Brazil at its epicenter. Brazilians have a long history of combatting Aedes aegypti mosquitos as it is a common vector for dengue, chikungunya, and yellow fever. As a response to the epidemic, public health authorities promoted ZIKV prevention behaviors such as mosquito bite prevention, reproductive counseling for women who are pregnant or contemplating pregnancy, pregnancy avoidance, and condom use. Most prevention efforts from Brazil focused on the mosquito vector- utilizing recycled dengue approaches without acknowledging the context in which women were able to adhere to these prevention messages. This study used qualitative methods to explore how women in Fortaleza, Brazil perceive ZIKV, the Brazilian authorities’ ZIKV prevention recommendations, and the feasibility of adhering to these recommendations. A core study aim was to look at how women perceive their physical, social, and natural environment as it impacts women’s ability to adhere to ZIKV prevention behaviors. A Rapid Anthropological Assessment (RAA) containing observations, informational interviews, and semi-structured in-depth interviews were utilized for data collection. The study utilized Grounded Theory as the systematic inductive method of analyzing the data collected. Interviews were conducted with 35 women of reproductive age (15-39 years old), who primarily utilize the public health system. It was found that women’s self-identified economic class was associated with how strongly women felt they could prevent ZIKV. All women interviewed technically belong to the C-class, the middle economic class. Although all members of the same economic class, there was a divide amongst participants as to who perceived themselves as higher C-class versus lower C-class. How women saw their economic status was dictated by how they perceived their physical, social, and natural environment. Women further associated their environment and their economic class to their likelihood of contracting ZIKV, their options for preventing ZIKV, their ability to prevent ZIKV, and their willingness to attempt to prevent ZIKV. Women’s perceived economic status was found to relate to their structural environment (housing quality, sewage, and locations to supplies), social environment (family and peer norms), and natural environment (wetland areas, natural mosquito breeding sites, and cyclical nature of vectors). Findings from this study suggest that women’s perceived environment and economic status impact their perceived feasibility and desire to attempt behaviors to prevent ZIKV. Although ZIKV has depleted from epidemic to endemic status, it is suggested that the virus will return as cyclical outbreaks like that seen with similar arboviruses such as dengue and chikungunya. As the next ZIKV epidemic approaches it is essential to understand how women perceive themselves, their abilities, and their environments to best aid the prevention of ZIKV.

Keywords: Aedes aegypti, environment, prevention, qualitative, zika

Procedia PDF Downloads 133

Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

Procedia PDF Downloads 387

Authors: Elvis Munyoka

Abstract:

While the number of African refugees settling in Australia has significantly increased since the mid-1990s, the marginalisation and exclusion of young people from refugee backgrounds in employment remain a critical challenge. Unemployment or underemployment can negatively impact refugees in multiple areas, such as income, housing, life satisfaction, and social status. Higher rates of unemployment among refugees are linked in part to the intersection of pre-migration and daily challenges like trauma, racism, gender identity, and English language competency, all of which generate multiple employability disadvantages. However, the intersection of gender, race, social class, and age in impacting African refugee youth’s access to employment has received less attention. Using a qualitative case study approach, the paper will explore how gender, race, social class, and age influence African refugee youth graduates’ access to employment in South Australia. The intersectionality theory and capability approach to social justice is used to explore intersecting factors impacting African refugee youth’s access to employment in South Australia. Participants were 16 African refugee graduates aged 18-30 living in South Australia who took part in the study for one year. Based on the trends in the data, the results suggest that long-term unemployment and underemployment, coupled with ongoing racism and marginalisation, have the potential to make refugees more vulnerable to several mental disorders such as depression, hopelessness, and suicidal thoughts. The analysis also reveals that resettlement challenges may limit refugees’ ability to recover from pre-migration trauma. The impact of resettlement challenges on refugee mental health highlights the need for comprehensive policy interventions to address the barriers refugees face in finding employment in resettlement communities. With African refugees constituting such an important part of Australian society, they should have equal access to meaningful employment, as decent work promotes good mental health, successful resettlement, hope, and self-sufficiency.

Keywords: African refugee youth, mental health, employment, resettlement, racism

Procedia PDF Downloads 69

Authors: Muhammad Umer Zubair, Kamran Akhtar, Muhammad Arsalan Khan

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This paper is based on a research carried out on a failed slope in Defence Housing Authority (DHA) Phase I, Islamabad. The research included determination of Soil parameters, Site Surveying and Cost Estimation. Apart from these, the use of three dimensional (3D) slope stability analysis in conjunction with two dimensional (2D) analysis was used determination of slope conditions. In addition collection of soil reports, a detailed survey was carried out to create a 3D model in Surfer 8 software. 2D cross-sections that needed to be analyzed for stability were generated from 3D model. Slope stability softwares, Rocscience Slide 6.0 and Clara-W were employed for 2D and 3D Analyses respectively which have the ability to solve complex mathematical functions. Results of the analyses were used to confirm site conditions and the threats were identified to recommend suitable remedies.The most effective remedy was suggested for slope stability after analyzing all remedies in software Slide 6 and its feasibility was determined through cost benefit analysis. This paper should be helpful to Geotechnical engineers, design engineers and the organizations working with slope stability.

Keywords: slope stability, Rocscience, Clara W., 2d analysis, 3D analysis, sensitivity analysis

Procedia PDF Downloads 524

Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

Procedia PDF Downloads 104

Authors: Osakwe Jude Odiakaosa

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Today’s digital society is characterized by e-education or e-learning, e-commerce, and so on. All these have been propelled by digital revolution. Digital technology such as computer technology, Global Positioning System (GPS) and Geographic Information System (GIS) has been having a tremendous impact on the field of technology. This development has positively affected the scope, methods, speed of data acquisition, data management and the rate of delivery of the results (map and other map products) of data processing. This paper tries to address the impact of revolution brought by digital technology.

Keywords: digital revolution, internet, technology, data management

Procedia PDF Downloads 449

Authors: Matt S. Van Deren, Michael Papenfus

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Seattle is one of the hundreds of cities in the United States that relies on a combined sewer system to collect and convey municipal wastewater. By design, these systems convey all wastewater, including industrial and commercial wastewater, human sewage, and stormwater runoff, through a single network of pipes. Serious problems arise for combined sewer systems during heavy precipitation events when treatment plants and storage facilities are unable to accommodate the influx of wastewater needing treatment, causing the sewer system to overflow into local waterways through sewer outfalls. CSOs (Combined Sewer Overflows) pose a serious threat to human and environmental health. Principal pollutants found in CSO discharge include microbial pathogens, comprising of bacteria, viruses, parasites, oxygen-depleting substances, suspended solids, chemicals or chemical mixtures, and excess nutrients, primarily nitrogen and phosphorus. While concentrations of these pollutants can vary between overflow events, CSOs have the potential to spread disease and waterborne illnesses, contaminate drinking water supplies, disrupt aquatic life, and effect a waterbody’s designated use. This paper estimates the economic impact of CSOs on residential property values. Using residential property sales data from Seattle, Washington, this paper employs a hedonic valuation model that controls for housing and neighborhood characteristics, as well as spatial and temporal effects, to predict a consumer’s willingness to pay for improved water quality near their homes. Initial results indicate that a 100,000-gallon decrease in the average annual overflow discharged from a sewer outfall within 300 meters of a home is associated with a 0.053% increase in the property’s sale price. For the average home in the sample, the price increase is estimated to be $18,860.23. These findings reveal some of the important economic benefits of improving water quality by reducing the frequency and severity of combined sewer overflows.

Keywords: benefits, hedonic, Seattle, sewer

Procedia PDF Downloads 177

Authors: Abdullah Al Mamun, Talal Alkharobi

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As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

Procedia PDF Downloads 320

Authors: Snezana Savoska, Blagoj Ristevski, Violeta Manevska, Zlatko Savoski, Ilija Jolevski

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Big data is widely accepted by the pharmaceutical companies as a result of business demands create through legal pressure. Pharmaceutical companies have many legal demands as well as standards’ demands and have to adapt their procedures to the legislation. To manage with these demands, they have to standardize the usage of the current information technology and use the latest software tools. This paper highlights some important aspects of experience with big data projects implementation in a pharmaceutical Macedonian company. These projects made improvements of their business processes by the help of new software tools selected to comply with legal and business demands. They use IT as a strategic tool to obtain competitive advantage on the market and to reengineer the processes towards new Internet economy and quality demands. The company is required to manage vast amounts of structured as well as unstructured data. For these reasons, they implement projects for emerging and appropriate software tools which have to deal with big data concepts accepted in the company.

Keywords: big data, unstructured data, SAP ERP, documentum

Procedia PDF Downloads 271

Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

Procedia PDF Downloads 193

Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

Procedia PDF Downloads 517

Authors: Suzan Wedyan

Abstract:

Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

Procedia PDF Downloads 537

Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

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Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: data grids, fault tolerance, clustering, chandy-lamport

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Authors: Muhammet Dursun Kaya, Hasan Asil

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One of the most important factors of research and development is the deep insight into the evolutions of scientific development. The state-of-the-art tools and instruments can considerably assist the researchers, and many of the world organizations have become aware of the advantages of data mining for the acquisition of the knowledge required for the unstructured data. This paper was an attempt to review the articles on the information technology published in the past five years with the aid of data mining. A clustering approach was used to study these articles, and the research results revealed that three topics, namely health, innovation, and information systems, have captured the special attention of the researchers.

Keywords: information technology, data mining, scientific development, clustering

Procedia PDF Downloads 278

Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless nodes in a sensor network gather and process critical information designed to process and communicate, information flooding through such network is critical for decision making and data processing, the integrity of such data is one of the most critical factors in wireless security without compromising the processing and transmission capability of the network. This paper presents mechanism to securely transmit data over a chain of sensor nodes without compromising the throughput of the network utilizing available battery resources available at the sensor node.

Keywords: hybrid protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node data processing, Z-MAC

Procedia PDF Downloads 145

Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

Procedia PDF Downloads 537

Authors: Karishma Kashyap, Subha D. Parida

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Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance

Keywords: building optimization, green building, post occupancy evaluation, stakeholder engagement

Procedia PDF Downloads 357

Authors: Tauseef-ur-Rehman, Rao Zahid Abbas, Wasim Babar, Arbab Sikandar

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Babesiosis is an infection due to the multiplication of tick borne parasite, Babesia sp., in erythrocytes of host (variety of vertebrates) including small ruminants and is responsible for decreased livestock output and hence economic losses. A cross-sectional study was designed in order to evaluate the prevalence of Babesia and its relation with various associated factors in district Toba Tek Singh, Central Punjab, Pakistan in 2009-2010. A total 10.84% (50/461) out of 461 examined cases for Babesia were found positive for Babesia infection. Month-wise peak prevalence was observed in July (17.95%), while no positive case was recorded in Dec-2009 and Jan-2010. The prevalence of infection in different goat breeds was found as non-significant (P < 0.05) for Babesia infection. The prevalence of Babesia was found significantly (P < 0.05) dependent to the goat age and sex. The feeding system, housing system, floor type and herd size revealed strong correlation with Babesia prevalence, while watering system and body conditions were found to be non-significant (P < 0.05), and hence it is suggested that with the improvement of management precautions Babesiosis can be avoided.

Keywords: Babesia, goat, prevalence, Pakistan, risk factors

Procedia PDF Downloads 520

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

Procedia PDF Downloads 377

Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: Seyyed Hossein Alavi, Soudabe Mehri Talarposhti

Abstract:

Passages urban landscape is made up of various components that the component parts of the whole and vice versa has relationships. In today’s cities, we have not seen a dual relationship and only one side of the equation which is the relationships of the component parts are considered. However, the effect of the component to whole is stronger and also longer. This means that every time the outer shell of the building was constructed instant impact on the viewers while it takes a long time to understand the impact of the building in its environment and basically, it seems city portrait has the sensory and untouchable effect on observer. Today, building facades are designated individually and in isolation from the context. Designers are familiar with the details of the facade, but they are not informed with the science of combination and its impact on portrait. The importance of city and also more important than that, the city portrait haven’t confirmed for those involved in the building and authorities and the construction been changed to a market for more glaring taste of designers and attracting more business and the city and its landscape has been forgotten. This essay is an attempt to collect a part of the principles and definitions needed on perspective issues and portrait, and it is hoped that it will open arena for more research and studies in this field and other related fields.

Keywords: facade, urban housing, urban design, sustainable architecture

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