Search results for: lidar Radar data fusion
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24950

Search results for: lidar Radar data fusion

23960 The Impact of Artificial Intelligence on Rural Life

Authors: Triza Edwar Fawzi Deif

Abstract:

In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

Procedia PDF Downloads 23
23959 An Embarrassingly Simple Semi-supervised Approach to Increase Recall in Online Shopping Domain to Match Structured Data with Unstructured Data

Authors: Sachin Nagargoje

Abstract:

Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

Procedia PDF Downloads 106
23958 Genodata: The Human Genome Variation Using BigData

Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

Abstract:

Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

Procedia PDF Downloads 236
23957 Noncritical Phase-Matched Fourth Harmonic Generation of Converging Beam by Deuterated Potassium Dihydrogen Phosphate Crystal

Authors: Xiangxu Chai, Bin Feng, Ping Li, Deyan Zhu, Liquan Wang, Guanzhong Wang, Yukun Jing

Abstract:

In high power large-aperture laser systems, such as the inertial confinement fusion project, the Nd: glass laser (1053nm) is usually needed to be converted to ultraviolet (UV) light and the fourth harmonic generation (FHG) is one of the most favorite candidates to achieve UV light. Deuterated potassium dihydrogen phosphate (DKDP) crystal is an optimal choice for converting the Nd: glass radiation to the fourth harmonic laser by noncritical phase matching (NCPM). To reduce the damage probability of focusing lens, the DKDP crystal is suggested to be set before the focusing lens. And a converging beam enters the FHG crystal consequently. In this paper, we simulate the process of FHG in the scheme and the dependence of FHG efficiency on the lens’ F is derived. Besides, DKDP crystal with gradient deuterium is proposed to realize the NCPM FHG of the converging beam. At every position, the phase matching is achieved by adjusting the deuterium level, and the FHG efficiency increases as a result. The relation of the lens’ F with the deuterium gradient is investigated as well.

Keywords: fourth harmonic generation, laser induced damage, converging beam, DKDP crystal

Procedia PDF Downloads 215
23956 Ontology for a Voice Transcription of OpenStreetMap Data: The Case of Space Apprehension by Visually Impaired Persons

Authors: Said Boularouk, Didier Josselin, Eitan Altman

Abstract:

In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

Procedia PDF Downloads 279
23955 Design and Development of a Platform for Analyzing Spatio-Temporal Data from Wireless Sensor Networks

Authors: Walid Fantazi

Abstract:

The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 239
23954 Prediction of Marine Ecosystem Changes Based on the Integrated Analysis of Multivariate Data Sets

Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

Abstract:

The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

Procedia PDF Downloads 98
23953 Optical Fiber Data Throughput in a Quantum Communication System

Authors: Arash Kosari, Ali Araghi

Abstract:

A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: absorption, data throughput, depolarization, optical fiber

Procedia PDF Downloads 275
23952 Event Driven Dynamic Clustering and Data Aggregation in Wireless Sensor Network

Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

Abstract:

Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

Procedia PDF Downloads 432
23951 Offshore Outsourcing: Global Data Privacy Controls and International Compliance Issues

Authors: Michelle J. Miller

Abstract:

In recent year, there has been a rise of two emerging issues that impact the global employment and business market that the legal community must review closer: offshore outsourcing and data privacy. These two issues intersect because employment opportunities are shifting due to offshore outsourcing and some States, like the United States, anti-outsourcing legislation has been passed or presented to retain jobs within the country. In addition, the legal requirements to retain the privacy of data as a global employer extends to employees and third party service provides, including services outsourced to offshore locations. For this reason, this paper will review the intersection of these two issues with a specific focus on data privacy.

Keywords: outsourcing, data privacy, international compliance, multinational corporations

Procedia PDF Downloads 395
23950 Weighted Data Replication Strategy for Data Grid Considering Economic Approach

Authors: N. Mansouri, A. Asadi

Abstract:

Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

Procedia PDF Downloads 245
23949 Spatial Data Mining by Decision Trees

Authors: Sihem Oujdi, Hafida Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

Procedia PDF Downloads 600
23948 Application of Simulated Annealing to Threshold Optimization in Distributed OS-CFAR System

Authors: L. Abdou, O. Taibaoui, A. Moumen, A. Talib Ahmed

Abstract:

This paper proposes an application of the simulated annealing to optimize the detection threshold in an ordered statistics constant false alarm rate (OS-CFAR) system. Using conventional optimization methods, such as the conjugate gradient, can lead to a local optimum and lose the global optimum. Also for a system with a number of sensors that is greater than or equal to three, it is difficult or impossible to find this optimum; Hence, the need to use other methods, such as meta-heuristics. From a variety of meta-heuristic techniques, we can find the simulated annealing (SA) method, inspired from a process used in metallurgy. This technique is based on the selection of an initial solution and the generation of a near solution randomly, in order to improve the criterion to optimize. In this work, two parameters will be subject to such optimisation and which are the statistical order (k) and the scaling factor (T). Two fusion rules; “AND” and “OR” were considered in the case where the signals are independent from sensor to sensor. The results showed that the application of the proposed method to the problem of optimisation in a distributed system is efficiency to resolve such problems. The advantage of this method is that it allows to browse the entire solutions space and to avoid theoretically the stagnation of the optimization process in an area of local minimum.

Keywords: distributed system, OS-CFAR system, independent sensors, simulating annealing

Procedia PDF Downloads 486
23947 Data-Driven Dynamic Overbooking Model for Tour Operators

Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 116
23946 Modeling and Statistical Analysis of a Soap Production Mix in Bejoy Manufacturing Industry, Anambra State, Nigeria

Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

Abstract:

The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

Procedia PDF Downloads 428
23945 Helping the Development of Public Policies with Knowledge of Criminal Data

Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

Abstract:

The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

Procedia PDF Downloads 66
23944 Optimization of Real Time Measured Data Transmission, Given the Amount of Data Transmitted

Authors: Michal Kopcek, Tomas Skulavik, Michal Kebisek, Gabriela Krizanova

Abstract:

The operation of nuclear power plants involves continuous monitoring of the environment in their area. This monitoring is performed using a complex data acquisition system, which collects status information about the system itself and values of many important physical variables e.g. temperature, humidity, dose rate etc. This paper describes a proposal and optimization of communication that takes place in teledosimetric system between the central control server responsible for the data processing and storing and the decentralized measuring stations, which are measuring the physical variables. Analyzes of ongoing communication were performed and consequently the optimization of the system architecture and communication was done.

Keywords: communication protocol, transmission optimization, data acquisition, system architecture

Procedia PDF Downloads 500
23943 The Duty of Application and Connection Providers Regarding the Supply of Internet Protocol by Court Order in Brazil to Determine Authorship of Acts Practiced on the Internet

Authors: João Pedro Albino, Ana Cláudia Pires Ferreira de Lima

Abstract:

Humanity has undergone a transformation from the physical to the virtual world, generating an enormous amount of data on the world wide web, known as big data. Many facts that occur in the physical world or in the digital world are proven through records made on the internet, such as digital photographs, posts on social media, contract acceptances by digital platforms, email, banking, and messaging applications, among others. These data recorded on the internet have been used as evidence in judicial proceedings. The identification of internet users is essential for the security of legal relationships. This research was carried out on scientific articles and materials from courses and lectures, with an analysis of Brazilian legislation and some judicial decisions on the request of static data from logs and Internet Protocols (IPs) from application and connection providers. In this article, we will address the determination of authorship of data processing on the internet by obtaining the IP address and the appropriate judicial procedure for this purpose under Brazilian law.

Keywords: IP address, digital forensics, big data, data analytics, information and communication technology

Procedia PDF Downloads 107
23942 Sourcing and Compiling a Maltese Traffic Dataset MalTra

Authors: Gabriele Borg, Alexei De Bono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale.

Keywords: Big Data, vehicular traffic, traffic management, mobile data patterns

Procedia PDF Downloads 93
23941 Comparative Study of Accuracy of Land Cover/Land Use Mapping Using Medium Resolution Satellite Imagery: A Case Study

Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

Abstract:

Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

Procedia PDF Downloads 491
23940 Effect of Genuine Missing Data Imputation on Prediction of Urinary Incontinence

Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

Abstract:

Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

Procedia PDF Downloads 151
23939 Mechanical Properties and Thermal Comfort of 3D Printed Hand Orthosis for Neurorehabilitation

Authors: Paulo H. R. G. Reis, Joana P. Maia, Davi Neiva Alves, Mariana R. C. Aquino, Igor B. Guimaraes, Anderson Horta, Thiago Santiago, Mariana Volpini

Abstract:

Additive manufacturing is a manufacturing technique used in many fields as a tool for the production of complex parts accurately. This technique has a wide possibility of applications in bioengineering, mainly in the manufacture of orthopedic devices, thanks to the versatility of shapes and surface details. The present article aims to evaluate the mechanical viability of a wrist-hand orthosis made using additive manufacturing techniques with Nylon 12 polyamide and compare this device with the wrist-hand orthosis manufactured by the traditional process with thermoplastic Ezeform. The methodology used is based on the application of computational simulations of voltage and temperature, from finite element analysis, in order to evaluate the properties of displacement, mechanical stresses and thermal comfort in the two devices. The execution of this work was carried out through a case study with a 29-year-old male patient. The modeling software involved was Meshmixer from US manufacturer Autodesk and Fusion 360 from the same manufacturer. The results demonstrated that the orthosis developed by 3D printing, from Nylon 12, presents better thermal comfort and response to the mechanical stresses exerted on the orthosis.

Keywords: additive manufacturing, finite elements, hand orthosis, thermal comfort, neurorehabilitation

Procedia PDF Downloads 174
23938 Database Management System for Orphanages to Help Track of Orphans

Authors: Srivatsav Sanjay Sridhar, Asvitha Raja, Prathit Kalra, Soni Gupta

Abstract:

Database management is a system that keeps track of details about a person in an organisation. Not a lot of orphanages these days are shifting to a computer and program-based system, but unfortunately, most have only pen and paper-based records, which not only consumes space but it is also not eco-friendly. It comes as a hassle when one has to view a record of a person as they have to search through multiple records, and it will consume time. This program will organise all the data and can pull out any information about anyone whose data is entered. This is also a safe way of storage as physical data gets degraded over time or, worse, destroyed due to natural disasters. In this developing world, it is only smart enough to shift all data to an electronic-based storage system. The program comes with all features, including creating, inserting, searching, and deleting the data, as well as printing them.

Keywords: database, orphans, programming, C⁺⁺

Procedia PDF Downloads 128
23937 Early Cell Cultures Derived from Human Prostate Cancer Tissue Express Tissue-Specific Epithelial and Cancer Markers

Authors: Vladimir Ryabov, Mikhail Baryshevs, Mikhail Voskresenskey, Boris Popov

Abstract:

The human prostate gland (PG) samples were obtained from patients who had undergone radical prostatectomy for prostate cancer (PC) and used to extract total RNA and prepare the prostate stromal cell cultures (PSCC) and patients-derived organoids (PDO). Growth of the cell cultures was accessed under microscopic evaluation in transmitted light and the marker expression by reverse polymerase chain reaction (RT-PCR), immunofluorescence, and immunoblotting. Some PCR products from prostate tissue, PSCC, and PDO were cloned and sequenced. We found that the cells of early and late passages of PSCC and corresponding PDO expressed luminal (androgen receptor, AR; cytokeratin 18, CK18) and basal (CK5, p63) epithelial markers, the production of which decreased or disappeared in late PSCC and PDO. The PSCC and PDO of early passages from cancer tissue additionally produced cancer markers AMACR, TMPRSS2-ERG, and Ezh2. The expression of TMPRSS2-ERG fusion transcripts was verified by cloning and sequencing the PCR products. The results obtained suggest that early passages of PSCC might be used as a pre-clinical model for the evaluation of early markers of prostate cancer.

Keywords: localized prostate cancer, prostate epithelial markers, prostate cancer markers, AMACR, TMPRSS2-ERG, prostate stromal cell cultures, PDO

Procedia PDF Downloads 91
23936 Research of Control System for Space Intelligent Robot Based on Vision Servo

Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

Abstract:

Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

Procedia PDF Downloads 408
23935 Impact of Western Music Instruments on Indian Classical Music

Authors: Hukam Chand

Abstract:

Over the past few years, the performance of Indian classical music has been improved a lot due to the technical inclusion of western instruments. Infect, the Indian classical music is all about raags which portray a mood and sentiments expressed through a microtonal scale based on natural harmonic series. And, most of the western instruments are not based on natural harmonic series and the tonal system is the only system which has considerable influence on the Indian classical music. However, the use of western instruments has been growing day by day in one way or the other by the Indian artists due to their quality of harmony. As a result of which, there are some common instruments such as harmonium, violin, guitar, saxophone, synthesizer which are being used commonly by Indian and western artists. On the other hand, a lot of fusion has taken place in the music of both sides due to the similar characteristics in their instruments. For example, harmonium which was originally the western instrument has now acquired an important position in Indian classical music to perform raags. Besides, a lot of suggestions for improving in the Indian music have been given by the artists for technical modification in the western instruments to cater the needs of Indian music through melody approach. Pt. Vishav Mohan Bhatt an Indian musician has developed Mohan Veena (called guitar) to perform raags. N. Rajam the Indian lady Violinist has made a remarkable work on Indian classical music by accompanied with vocal music. The purpose of the present research paper is to highlight the changes in Indian Classical Music through performance by using modified western music instruments.

Keywords: Indian classical music, Western instruments, harmonium, guitar, Violin and impact

Procedia PDF Downloads 509
23934 New Two-Way Map-Reduce Join Algorithm: Hash Semi Join

Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

Abstract:

Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

Procedia PDF Downloads 499
23933 Using Implicit Data to Improve E-Learning Systems

Authors: Slah Alsaleh

Abstract:

In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.

Keywords: e-learning, implicit data, user behavior, data mining

Procedia PDF Downloads 296
23932 Enabling Quantitative Urban Sustainability Assessment with Big Data

Authors: Changfeng Fu

Abstract:

Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

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23931 Development of Generalized Correlation for Liquid Thermal Conductivity of N-Alkane and Olefin

Authors: A. Ishag Mohamed, A. A. Rabah

Abstract:

The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

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