Search results for: positive count data.
7296 Foundation of the Information Model for Connected-Cars
Authors: Hae-Won Seo, Yong-Gu Lee
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Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.Keywords: Connected-car, data modeling, route planning, navigation system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19637295 Family Communication Patterns between Muslim and Santal Communities in Rural Bangladesh: A Cross-Cultural Perspective
Authors: Md. Emaj Uddin
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This study compares family communication patterns in association with family socio-cultural status, especially marriage and family pattern, and couples- socio-economic status between Muslim and Santal communities in rural Bangladesh. A total of 288 couples, 145 couples from the Muslim and 143 couples from the Santal were randomly selected through cluster sampling procedure from Kalna village situated in Tanore Upazila of Rajshahi district of Bangladesh, where both the communities dwell as neighbors. In order to collect data from the selected samples, interview method with semistructural questionnaire schedule was applied. The responses given by the respondents were analyzed by Pearson-s chi-squire test and bivariate correlation techniques. The results of Pearson-s chi-squire test revealed that family communication patterns (X2= 25. 90, df= 2, p<0.01, p>0.05) were significantly different between the Muslim and Santal communities. In addition, Spearman-s bivariate correlation coefficients suggested that among the exogenous factors, family type (rs=.135, p<0.05) and occupation of both husband (rs= .197, p<0.01) and wife (rs= .265, p<0.01) were significantly positive associations, and marital arrangement (rs= -.177, p<0.01), education of husband (rs= -.108, p<0.05) and wife (rs= -.142, p<0.01 & p<0.05), and family income (rs= -.164, p<0.01) were significantly negative relations with the family communication patterns followed between the two communities, although age difference between husband and wife, family head and residence patterns were not significant relations with ones.
Keywords: Bangladesh, Cross-Cultural Comparison, Family Communication Patterns, Family Socio-Cultural Status, Muslim, Santal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25767294 Fault Detection and Identification of COSMED K4b2 Based On PCA and Neural Network
Authors: Jing Zhou, Steven Su, Aihuang Guo
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COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.
Keywords: BP Neural Network, Exercising Testing, Fault Detection and Identification, Principal Component Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30777293 Array Data Transformation for Source Code Obfuscation
Authors: S. Praveen, P. Sojan Lal
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Obfuscation is a low cost software protection methodology to avoid reverse engineering and re engineering of applications. Source code obfuscation aims in obscuring the source code to hide the functionality of the codes. This paper proposes an Array data transformation in order to obfuscate the source code which uses arrays. The applications using the proposed data structures force the programmer to obscure the logic manually. It makes the developed obscured codes hard to reverse engineer and also protects the functionality of the codes.Keywords: Reverse Engineering, Source Code Obfuscation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20367292 Culture Dimensions of Information Systems Security in Saudi Arabia National Health Services
Authors: Saleh Alumaran, Giampaolo Bella, Feng Chen
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The study of organisations’ information security cultures has attracted scholars as well as healthcare services industry to research the topic and find appropriate tools and approaches to develop a positive culture. The vast majority of studies in Saudi national health services are on the use of technology to protect and secure health services information. On the other hand, there is a lack of research on the role and impact of an organisation’s cultural dimensions on information security. This research investigated and analysed the role and impact of cultural dimensions on information security in Saudi Arabia health service. Hypotheses were tested and two surveys were carried out in order to collect data and information from three major hospitals in Saudi Arabia (SA). The first survey identified the main cultural-dimension problems in SA health services and developed an initial information security culture framework model. The second survey evaluated and tested the developed framework model to test its usefulness, reliability and applicability. The model is based on human behaviour theory, where the individual’s attitude is the key element of the individual’s intention to behave as well as of his or her actual behaviour. The research identified a set of cultural and sub-cultural dimensions in SA health information security and services.
Keywords: Behaviour theory, Culture dimensions, Electronic health records, Information security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23387291 Applying Fuzzy FP-Growth to Mine Fuzzy Association Rules
Authors: Chien-Hua Wang, Wei-Hsuan Lee, Chin-Tzong Pang
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In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.Keywords: Data mining, association rule, fuzzy frequent patterngrowth.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18007290 A Supervised Learning Data Mining Approach for Object Recognition and Classification in High Resolution Satellite Data
Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad
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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars, and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.Keywords: Remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20537289 Investigating Crime Hotspot Places and their Implication to Urban Environmental Design: A Geographic Visualization and Data Mining Approach
Authors: Donna R. Tabangin, Jacqueline C. Flores, Nelson F. Emperador
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Information is power. Geographical information is an emerging science that is advancing the development of knowledge to further help in the understanding of the relationship of “place" with other disciplines such as crime. The researchers used crime data for the years 2004 to 2007 from the Baguio City Police Office to determine the incidence and actual locations of crime hotspots. Combined qualitative and quantitative research methodology was employed through extensive fieldwork and observation, geographic visualization with Geographic Information Systems (GIS) and Global Positioning Systems (GPS), and data mining. The paper discusses emerging geographic visualization and data mining tools and methodologies that can be used to generate baseline data for environmental initiatives such as urban renewal and rejuvenation. The study was able to demonstrate that crime hotspots can be computed and were seen to be occurring to some select places in the Central Business District (CBD) of Baguio City. It was observed that some characteristics of the hotspot places- physical design and milieu may play an important role in creating opportunities for crime. A list of these environmental attributes was generated. This derived information may be used to guide the design or redesign of the urban environment of the City to be able to reduce crime and at the same time improve it physically.Keywords: Crime mapping, data mining, environmental design, geographic visualization, GIS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26237288 Learning and Evaluating Possibilistic Decision Trees using Information Affinity
Authors: Ilyes Jenhani, Salem Benferhat, Zied Elouedi
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This paper investigates the issue of building decision trees from data with imprecise class values where imprecision is encoded in the form of possibility distributions. The Information Affinity similarity measure is introduced into the well-known gain ratio criterion in order to assess the homogeneity of a set of possibility distributions representing instances-s classes belonging to a given training partition. For the experimental study, we proposed an information affinity based performance criterion which we have used in order to show the performance of the approach on well-known benchmarks.Keywords: Data mining from uncertain data, Decision Trees, Possibility Theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15157287 Air Quality Forecast Based on Principal Component Analysis-Genetic Algorithm and Back Propagation Model
Authors: Bin Mu, Site Li, Shijin Yuan
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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.
Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10287286 Regression Approach for Optimal Purchase of Hosts Cluster in Fixed Fund for Hadoop Big Data Platform
Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu
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Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.
Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance empirical formula, typical SQL query tasks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8377285 Analysis of Palm Perspiration Effect with SVM for Diabetes in People
Authors: Hamdi Melih Saraoğlu, Muhlis Yıldırım, Abdurrahman Özbeyaz, Feyzullah Temurtas
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In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.
Keywords: Palm perspiration, Diabetes, Support Vector Machine, Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19467284 Elemental Graph Data Model: A Semantic and Topological Representation of Building Elements
Authors: Yasmeen A. S. Essawy, Khaled Nassar
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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.
Keywords: Building information modeling, elemental graph data model, geometric and topological data models, and graph theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12037283 Innovative Activity and Development: Analyzing Firm Data from Eurozone Country-Members
Authors: Ilias A. Makris
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In this work, we attempt to associate firm characteristics with innovative activity. We collect microdata from listed firms of selected Eurozone Country-members, after the beginning of 2007 financial crisis. The following literature, several indicators of growth and performance were selected and tested for their ability to interpret innovative activity. The main scope is to examine the possible differences in performance and growth between innovative and non-innovative firms, during a severe recession. Additionally to that, a special focus will be held on whether macroeconomic performance and national innovation system, determines the extent of innovators' performance. Preliminary findings, through correlation matrices and non-parametric tests, strongly indicate the positive relation between innovative activity and most of the measures used (profitability, size, employment), confirming that even during a recessionary period, innovative firms not only survive but also seem to succeed better economic results in almost all indexes relative to non-innovative. However, even though innovators seem to perform better in all economies examined, the extent of that performance seems to be strongly affected by the supportive mechanisms (financial and structural) that their country provides. Thus, it is clear, that the technologically intensive 'gap' between European South and North, during the economic crisis, became chaotic, due to the harsh austerity measures and reduced budgets in those countries, even in sectors with high potentials in economic activity and employment, impairing the effects of crisis and enhancing the vicious circle of recession.Keywords: Eurozone, innovative activity, development, firm performance, non-parametric tests.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14497282 A Materialized View Approach to Support Aggregation Operations over Long Periods in Sensor Networks
Authors: Minsoo Lee, Julee Choi, Sookyung Song
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The increasing interest on processing data created by sensor networks has evolved into approaches to implement sensor networks as databases. The aggregation operator, which calculates a value from a large group of data such as computing averages or sums, etc. is an essential function that needs to be provided when implementing such sensor network databases. This work proposes to add the DURING clause into TinySQL to calculate values during a specific long period and suggests a way to implement the aggregation service in sensor networks by applying materialized view and incremental view maintenance techniques that is used in data warehouses. In sensor networks, data values are passed from child nodes to parent nodes and an aggregation value is computed at the root node. As such root nodes need to be memory efficient and low powered, it becomes a problem to recompute aggregate values from all past and current data. Therefore, applying incremental view maintenance techniques can reduce the memory consumption and support fast computation of aggregate values.Keywords: Aggregation, Incremental View Maintenance, Materialized view, Sensor Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15407281 Organic Agriculture Harmony in Nutrition, Environment and Health: Case Study in Iran
Authors: Sara Jelodarian
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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.
Keywords: Development, production markets, progress, strategic role, technology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4997280 Real Time Data Communication with FlightGear Using Simulink over a UDP Protocol
Authors: Adil Loya, Ali Haider, Arslan A. Ghaffor, Abubaker Siddique
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Simulation and modelling of Unmanned Aerial Vehicle (UAV) has gained wide popularity in front of aerospace community. The demand of designing and modelling optimized control system for UAV has increased ten folds since last decade, as next generation warfare is dependent on unmanned technologies. Therefore, this research focuses on the simulation of nonlinear UAV dynamics on Simulink and its integration with Flightgear. There has been lots of research on implementation of optimizing control using Simulink, however, there are fewer known techniques to simulate these dynamics over Flightgear and a tedious technique of acquiring data has been tackled in this research horizon. Sending data to Flightgear is easy but receiving it from Simulink is not that straight forward, i.e. we can only receive control data on the output. However, in this research we have managed to get the data out from the Flightgear by implementation of level 2 s-function block within Simulink. Moreover, the results captured from Flightgear over a Universal Datagram Protocol (UDP) communication are then compared with the attitude signal that were sent previously. This provide useful information regarding the difference in outputs attained from Simulink to Flightgear. It was found that values received on Simulink were in high agreement with that of the Flightgear output. And complete study has been conducted in a discrete way.
Keywords: aerospace, flight control, FlightGear, communication, Simulink
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11517279 Comparing Data Analysis, Communication and Information Technologies Expertise Levels in Undergraduate Psychology Students
Authors: Ana Cázares
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Aims for this study: first, to compare the expertise level in data analysis, communication and information technologies in undergraduate psychology students. Second, to verify the factor structure of E-ETICA (Escala de Experticia en Tecnologias de la Informacion, la Comunicacion y el Análisis or Data Analysis, Communication and Information'Expertise Scale) which had shown an excellent internal consistency (α= 0.92) as well as a simple factor structure. Three factors, Complex, Basic Information and Communications Technologies and E-Searching and Download Abilities, explains 63% of variance. In the present study, 260 students (119 juniors and 141 seniors) were asked to respond to ETICA (16 items Likert scale of five points 1: null domain to 5: total domain). The results show that both junior and senior students report having very similar expertise level; however, E-ETICA presents a different factor structure for juniors and four factors explained also 63% of variance: Information E-Searching, Download and Process; Data analysis; Organization; and Communication technologies.Keywords: Data analysis, Information, Communications Technologies, Expertise'Levels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12867278 Omni: Data Science Platform for Evaluate Performance of a LoRaWAN Network
Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello
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Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.Keywords: Internet of Things, LoRa, LoRaWAN, smart cities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7137277 Integration of Image and Patient Data, Software and International Coding Systems for Use in a Mammography Research Project
Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst
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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19457276 Efficient Pre-Processing of Single-Cell Assay for Transposase Accessible Chromatin with High-Throughput Sequencing Data
Authors: Fan Gao, Lior Pachter
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The primary tool currently used to pre-process 10X chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.
Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11597275 Crossover Memories and Code-Switching in the Narratives of Arabic-Hebrew and Hebrew-English Bilingual Adults in Israel
Authors: Amani Jaber-Awida
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This study examines two bilingual phenomena in the narratives of Arabic Hebrew and Hebrew-English bilingual adults in Israel: CO memories and code-switching (CS). The study examined these phenomena in the context of autobiographical memory, using a cue word technique. Student experimenters held two sessions in the homes of the participants. In separate language sessions, the participant was asked to look first at each of 16 cue words and then to state a concrete memory. After stating the memory, participants reported whether their memories were in the same language of the experiment session or different. Memories were classified as ‘Crossovers’ (CO) or ‘Same Language’ (SL) according to participants' self-reports. Participants were also required to elaborate about the setting, interlocutors and other languages involved in the specific memory. Beyond replicating the procedure of cuing technique, one memory from a specific lifespan period was chosen per participant, and the participant was required to provide further details about it. For the more detailed memories, CS count was conducted. Both bilingual groups confirmed the Reminiscence Bump phenomenon, retrieving more memories in the 10-30 age period. CO memories prevailed in second language sessions (L2). Same language memories were more abundant in first language sessions (L1). Higher CS frequency was found in L2 sessions. Finally, as predicted, 'individual' CS was prevalent in L2 sessions, but 'community-based' CS was not higher in L1 sessions. The two bilingual measures in this study, crossovers, and CS came from different research traditions, the former from an experimental paradigm in the psychology of autobiographical memory based on self-reported judgments, the latter a behavioral measure from linguistics. This merger of approaches offers new insight into the field of bilingual autobiographical memory. In addition, the study attempted to shed light on the investigation of motivations for CS, beginning with Walters’ SPPL Model and concluding with a distinction between ‘community-based’ and individual motivations.
Keywords: Autobiographical memory, code-switching, crossover memories, reminiscence bump.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7867274 Urban Big Data: An Experimental Approach to Building-Value Estimation Using Web-Based Data
Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin
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Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.Keywords: Big data, building-value analysis, machine learning, price prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11647273 A Concept Study to Assist Non-Profit Organizations to Better Target Developing Countries
Authors: Malek Makki
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The main purpose of this research study is to assist non-profit organizations (NPOs) to better segment a group of least developing countries and to optimally target the most needier areas, so that the provided aids make positive and lasting differences. We applied international marketing and strategy approaches to segment a sub-group of candidates among a group of 151 countries identified by the UN-G77 list, and furthermore, we point out the areas of priorities. We use reliable and well known criteria on the basis of economics, geography, demography and behavioral. These criteria can be objectively estimated and updated so that a follow-up can be performed to measure the outcomes of any program. We selected 12 socio-economic criteria that complement each other: GDP per capita, GDP growth, industry value added, export per capita, fragile state index, corruption perceived index, environment protection index, ease of doing business index, global competitiveness index, Internet use, public spending on education, and employment rate. A weight was attributed to each variable to highlight the relative importance of each criterion within the country. Care was taken to collect the most recent available data from trusted well-known international organizations (IMF, WB, WEF, and WTO). Construct of equivalence was carried out to compare the same variables across countries. The combination of all these weighted estimated criteria provides us with a global index that represents the level of development per country. An absolute index that combines wars and risks was introduced to exclude or include a country on the basis of conflicts and a collapsing state. The final step applied to the included countries consists of a benchmarking method to select the segment of countries and the percentile of each criterion. The results of this study allowed us to exclude 16 countries for risks and security. We also excluded four countries because they lack reliable and complete data. The other countries were classified per percentile thru their global index, and we identified the needier and the areas where aids are highly required to help any NPO to prioritize the area of implementation. This new concept is based on defined, actionable, accessible and accurate variables by which NPO can implement their program and it can be extended to profit companies to perform their corporate social responsibility acts.
Keywords: Developing countries, International marketing, non-profit organization, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9907272 Qualitative Data Analysis for Health Care Services
Authors: Taner Ersoz, Filiz Ersoz
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This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.
Keywords: Multiple correspondence analysis, optimal scaling, multivariate categorical data, health care services, health satisfaction survey, statistical visualizing, Turkey.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8767271 Stability and Bifurcation Analysis in a Model of Hes1 Selfregulation with Time Delay
Authors: Kejun Zhuang, Hailong Zhu
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The dynamics of a delayed mathematical model for Hes1 oscillatory expression are investigated. The linear stability of positive equilibrium and existence of local Hopf bifurcation are studied. Moreover, the global existence of large periodic solutions has been established due to the global bifurcation theorem.Keywords: Hes1, Hopf bifurcation, time delay, transcriptional repression loop
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13947270 Comparison of Different Types of Sources of Traffic Using SFQ Scheduling Discipline
Authors: Alejandro Gomez Suarez, H. Srikanth Kamath
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In this paper, SFQ (Start Time Fair Queuing) algorithm is analyzed when this is applied in computer networks to know what kind of behavior the traffic in the net has when different data sources are managed by the scheduler. Using the NS2 software the computer networks were simulated to be able to get the graphs showing the performance of the scheduler. Different traffic sources were introduced in the scripts, trying to establish the real scenario. Finally the results were that depending on the data source, the traffic can be affected in different levels, when Constant Bite Rate is applied, the scheduler ensures a constant level of data sent and received, but the truth is that in the real life it is impossible to ensure a level that resists the changes in work load. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21387269 Studies of Rule Induction by STRIM from the Decision Table with Contaminated Attribute Values from Missing Data and Noise — In the Case of Critical Dataset Size —
Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno
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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to real-world data
Keywords: Rule induction, decision table, missing data, noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14637268 Necessary Condition to Utilize Adaptive Control in Wind Turbine Systems to Improve Power System Stability
Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi
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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.
Keywords: Almost strictly positive real, doubly-fed induction generator, simple adaptive control, subsynchronous oscillations, wind turbine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11267267 The Comparison of Anchor and Star Schema from a Query Performance Perspective
Authors: Radek Němec
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Today's business environment requires that companies have access to highly relevant information in a matter of seconds. Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by star schemas. Dimensional modeling is already recognized as a leading industry standard in the field of data warehousing although several drawbacks and pitfalls were reported. This paper focuses on the analysis of another data warehouse modeling technique - the anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show information about performance of queries executed on database schemas structured according to principles of each database modeling technique.Keywords: Data warehousing, anchor modeling, star schema, anchor schema, query performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3319