Search results for: symbolic data

Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

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This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

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Authors: Kalpeshkumar Patel, Nikita Manvi

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The paper is an attempt to understand the influence and depiction of power in an urban space by throwing light across a few examples across the architectural timeline. Power has been the medium through which ideologies function, as witnessed across the timeline. The center to understand this ideology is to apprehend how power is formed, captured, owned, traded, and distorted. Every urban space has power embedded in it, either for the people who are imposing it or for the public who are receiving it. The most fundamental question in the issue of power is who – who will judge, whose tastes will matter and whose interests are being served. Power is expressed and reinforced by regular means, a boundary and gates, a parade route, a dominant landmark, play of shape or scale in elevation, ceremonial axis, boulevards and avenues, the vista, bilateral symmetry, or regular order. Even if people accept the psychological efficacy of these forms, the way they perceive them may vary depending on the subject. They are cold devices of power used to make some people submit to others. Yet it is also true that these symbolic forms are attractive because they speak to the deep emotions of people. They do indeed give us a sense of security, stability and continuity, awe and pride. The Urban Space for mass assembly is an idea that continues to seduce dictators and democracies. It is a tradition as old as an agora and as manipulative as Baroque Rome.

Keywords: urban space, aggrandization, city planning, landscape, supremacy, democratic

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: Mukhamad Fatkhullah, Arfan Fadli, Marini Kristina Situmeang, Siti Hazar Sitorus

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The emergence of a community of people with disabilities along with the various works produced has made great progress to open the public eye to their existence in society. This study focuses attention on a community that is suspected to be one of the pioneers in pursuing the movement. It is Deaf Art Community (DAC), a community of persons with disabilities based in Yogyakarta, with deaf and speech-impaired members who use sign language in everyday communication. Knowing the movement of disabled communities is a good thing, the description of the things behind it then important to know as the basis for initiating similar movements. This research focuses on the question of how community of people with disabilities begin to take shape in different regions and interact with collaborative events. Qualitative method with in-depth interview as data collection techniques was used to describe the process of formation and the emergence of community. The analytical unit in the study initially focuses on the subject in the community, but in the process, it develops to institutional analysis. Therefore some informants were determined purposively and expanded using the snowball technique. The theory used in this research is Phenomenology of Alfred Schutz to be able to see reality from the subject and institutional point of view. The results of this study found that the community is formed because the existing educational institutions (both SLB and inclusion) are less able to empower and make children with disabilities become equal with the society. Through the SLB, the presence of children with disabilities becomes isolated from the society, especially in children of his or her age. Therefore, discrimination and labeling will never be separated from society's view. Meanwhile, facilities for the basic needs of children with disabilities can not be fully provided. Besides that, the guarantee of discrimination, glances, and unpleasant behavior from children without disability does not exist, which then indicates that the existing inclusion schools offer only symbolic acceptance. Thus, both in SLB and Inclusive Schools can not empower children with disabilities. Community-based assistance, in this case, has become an alternative to actually empowering children with disabilities. Not only giving them a place to interact, through the same community, children with disabilities will be guided to discover their talents and develop their potential to be self-reliant in the future.

Keywords: children with disabilities, community-based assessment, community empowerment, social equity

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: Sami Kabir, Sadek Hossain Khoka

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Open Government Data (OGD) refers to all data produced by government which are accessible in reusable way by common people with access to Internet and at free of cost. In line with “Digital Bangladesh” vision of Bangladesh government, the concept of open data has been gaining momentum in the country. Opening all government data in digital and customizable format from single platform can enhance e-governance which will make government more transparent to the people. This paper presents a well-in-progress case study on OGD portal by Bangladesh Government in order to link decentralized data. The initiative is intended to facilitate e-service towards citizens through this one-stop web portal. The paper further discusses ways of collecting data in digital format from relevant agencies with a view to making it publicly available through this single point of access. Further, possible layout of this web portal is presented.

Keywords: e-governance, one-stop web portal, open government data, reusable data, web of data

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Authors: C. B. Abhilash, Kavi Mahesh

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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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Authors: Dina Ahmad Alkhodary

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This study aimed to investigate the practices of Data Mining on the telecommunication companies in Jordan, from the viewpoint of the respondents. In order to achieve the goal of the study, and test the validity of hypotheses, the researcher has designed a questionnaire to collect data from managers and staff members from main department in the researched companies. The results shows improvements stages of the telecommunications companies towered Data Mining.

Keywords: data, mining, development, business

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Authors: Chananart Meenanan

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The composition Isan Symphonic Variations for Chorus and Orchestra is a musical composition inspired by Isan Folk music tunes. The composer has created the well crafted melodic variations and cultural sound character of the piece based on the Klon Lum Tang Isan Keaw (Green Isan’s short poems). Meanwhile, the poetic lyric has been motivatedly recreated to bring the abundance of Northeastern Thailand region’s sentiment back to life. Moreover, the sound of xylophone (Ponglang), the instruments of the orchestra and the chorus were blended in order to present Isan folk music’s character via the Western musical idiom. The 3 movement of this composition is divided as following: In Movement I (Allegro), the introduction has been represented the uniqueness in Isan folk music’s liveliness by expressing it through the sound of chorus and orchestra. The composer also added the melodious sound flavor by utilizing the variety of the muting sound style on trumpets and horns. In Movement II (Moderato), the aspect of the heterophonic approach music has been implied to the main idea of the entire movement whereby its formatted transformation worked effectively through chorus and the orchestra. In Movement III (Allegretto) the harmonic chromaticism was modified and applied as the symbolic icon of the entire movement. The transparence of Isan cultural sound was perfectly designed to be the highlight of this spectacular episode.

Keywords: Isan, symphonic variations, chorus, orchestra

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Authors: Amal M. Alrayes

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Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance.Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: data quality, performance, system quality, Kingdom of Bahrain

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Authors: Shagufta Jahangir, Raisa Jahangir, Nadeemullah

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In many societies sports is considered inappropriate for women. It traditionally associated with mascunity. The proposed study aims at undertaking a critical situation analysis of sports women in Pakistan from a gender perspective by examining various aspects of sports women by gender including wrong social values, unstable economical position, wrong religious perspective and the role of media towards women in sports, while sports can provide a channel for informing women about their social and legal rights as well as their health issues, productive health and others. A major concern of the study is to identify the basic causes which depriving Pakistani women from sports. The Human Rights Commission of Pakistan and the Joint Action Committee for People’s Rights organized a symbolic mini marathon on 21 May 2005 in Pakistan to challenge arbitrary curbs on women’s public participation in sport and to highlight rising violence against women. Historically, sport has engaged the perception of gender-hierarchy in order to reproduce the ideology of male superiority, a notion which is often translated into ‘usual superiority’ within the superior communal order. However, it is argued here that we are presently in a state of communal instability with esteem to women's participation in sport.

Keywords: mascunity, gender, productive health, inappropriate, rights

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research and transfers of big data are not confined to a particular jurisdiction, but there is a lack of clarity regarding the legal requirements for importing and exporting such data. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Tejinder Singh

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Information system is the flow of data from different levels to different directions for decision making and data operations in information system (IS). Data can be violated by different manner like manual or technical errors, data tampering or loss of integrity. Security system called firewall of IS is effected by such type of violations. The flow of data among various levels of Information System is done by networking system. The flow of data on network is in form of packets or frames. To protect these packets from unauthorized access, virus attacks, and to maintain the integrity level, network security is an important factor. To protect the data to get pirated, various security techniques are used. This paper represents the various security techniques and signifies different harmful attacks with the help of detailed data analysis. This paper will be beneficial for the organizations to make the system more secure, effective, and beneficial for future decisions making.

Keywords: information systems, data integrity, TCP/IP network, vulnerability, decision, data

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Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

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The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

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Authors: Theddeus Tochukwu Akano, Omotayo Abayomi Fakinlede

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Proper understanding of the behavior of compliant mechanisms use by athletes is important in order to avoid catastrophic failure. Such compliant mechanisms like the flex-run require the knowledge of their dynamic response and deformation behavior under quickly varying loads. The modeling of finite deformations of the compliant athletic system is described by Neo-Hookean model under contact-impact conditions. The dynamic impact-contact governing equations for both the target and impactor are derived based on the updated Lagrangian approach. A method where contactor and target are considered as a united body is applied in the formulation of the principle of virtual work for the bodies. In this paper, methods of continuum mechanics and nonlinear finite element method were deployed to develop a model that could capture the behavior of the compliant athletic system under quickly varying loads. A hybrid system of symbolic algebra (AceGEN) and a compiled back end (AceFEM) were employed, leveraging both ease of use and computational efficiency. The simulated results reveal the effect of the various contact-impact conditions on the deformation behavior of the impacting compliant mechanism.

Keywords: eigenvalue problems, finite element method, robin boundary condition, sturm-liouville problem

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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Authors: Luvisa Kusuma, Panji Yudha Prakasa

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Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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Authors: Priscila A. M. Rodrigues

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In Brazil, higher education is usually offered in three parts of the day: in the morning, afternoon and evening. Students have to decide what part of the day they are going to study in the application process. Most of the admitted students who choose to study in the evening also work during the day, because of their financial conditions. Brazilian higher education courses in the evening were initially created to meet the demand for teacher training. These teacher-training courses are socially discredited and considered easily accessible in the country, mostly due to the fact that students who enroll for those courses come from very poor basic education. The research has analyzed the differences between the social profiles and studying conditions of students of teacher education, especially the training intended for would-be elementary education teachers. An investigation has been conducted with these undergraduate students, who were divided into a group of those who study both in the morning and in the afternoon (group 1) and a group of those who study in the evening (group 2). The hypothesis predicted that students in group 1 would perform better than students in group 2. The analysis of training and studying conditions departed from the point of view of students and their teachers. The hypothesis predicted that students in group 1 would perform better than students in group 2. The analysis of training and studying conditions departed from the point of view of students and their teachers. Data was collected from survey, qualitative interviews, field observation and reports from students. Sociological concepts of habitus, cultural capital, trajectories and strategies are essential for this study as well as the literature on quality of higher education. The research revealed that there are differences of studying conditions between group 1 and group 2, precisely when it comes to the university atmosphere, that is to say, academic support resources and enrichment activities which promote educational, cultural and social opportunities, for example conferences, events, scholarships of different types, etc. In order to counteract the effects of their poor educational performance, students who generally come from popular strata require conditions of greater dedication and investment in higher education, which most of them do not have. Despite the considerable difficulties that students in group 2 encounter in their academic experience, the university experience per se brings a gain for the lives of these students, which translates into the expansion of their capital structure – i.e. symbolic, cultural and educational capital – with repercussions on their social trajectory, especially in professional conditions.

Keywords: higher education, higher education students’ performance, quality of higher education, teacher’s education

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Authors: Miho Tsukamoto

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Since the initial creation of the Barbie doll in 1959, it became a symbol of US society. Likewise, the Licca-chan, a Japanese doll created in 1967, also became a Japanese symbolic doll of Japanese society. Prior to the introduction of Licca-chan, Barbie was already marketed in Japan but their sales were dismal. Licca-chan (an actual name: Kayama Licca) is a plastic doll with a variety of sizes ranging from 21.0 cm to 29.0 cm which many Japanese girls dream of having. For over 35 years, the manufacturer, Takara Co., Ltd. has sold over 48 million dolls and has produced doll houses, accessories, clothes, and Licca-chan video games for the Nintendo DS. Many First-generation Licca-chan consumers still are enamored with Licca-chan, and go to Licca-chan House, in an amusement park with their daughters. These people are called Licca-chan maniacs, as they enjoy touring the Licca-chan’s factory in Tohoku or purchase various Licca-chan accessories. After the successful launch of Licca-chan into the Japanese market, a mixed-like doll from the US and Japan, a doll, JeNny, was later sold in the same Japanese market by Takara Co., Ltd. in 1982. Comparison of these cultural iconic dolls, Barbie and Licca-chan, are analyzed in this paper. In fact, these dolls have concepts of girls’ dreams. By using concepts of mythology of Jean Baudrillard, these dolls can be represented idealized images of figures in the products for consumers, but at the same time, consumers can see products with different perspectives, which can cause controversy.

Keywords: Barbie, dolls, JeNny, idealization, Licca-chan

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

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Authors: K. Raghu, Sree Harsha

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The interrelationship between the technology and architecture of tall buildings is investigated from the emergence of tall buildings in late 19th century to the present. In the late 19th century early designs of tall buildings recognized the effectiveness of diagonal bracing members in resisting lateral forces. Most of the structural systems deployed for early tall buildings were steel frames with diagonal bracings of various configurations such as X, K, and eccentric. Though the historical research a filtering concept is developed original and remedial technology- through which one can clearly understand inter-relationship between the technical evolution and architectural esthetic and further stylistic transition buildings. Diagonalized grid structures – “diagrids” - have emerged as one of the most innovative and adaptable approaches to structuring buildings in this millennium. Variations of the diagrid system have evolved to the point of making its use non-exclusive to the tall building. Diagrid construction is also to be found in a range of innovative mid-rise steel projects. Contemporary design practice of tall buildings is reviewed and design guidelines are provided for new design trends. Investigated in depths are the behavioral characteristics and design methodology for diagrids structures, which emerge as a new direction in the design of tall buildings with their powerful structural rationale and symbolic architectural expression. Moreover, new technologies for tall building structures and facades are developed for performance enhancement through design integration, and their architectural potentials are explored. By considering the above data the analysis and design of 40-100 storey diagrids steel buildings is carried out using E-TABS software with diagrids of various angle to be found for entire building which will be helpful to reduce the steel requirement for the structure. The present project will have to undertake wind analysis, seismic analysis for lateral loads acting on the structure due to wind loads, earthquake loads, gravity loads. All structural members are designed as per IS 800-2007 considering all load combination. Comparison of results in terms of time period, top storey displacement and inter-storey drift to be carried out. The secondary effect like temperature variations are not considered in the design assuming small variation.

Keywords: diagrid, bracings, structural, building

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