99,517 research outputs found
Joshua Davis: Author of Spare Parts
No full textCitation: K-State First (2016). Joshua Davis: Author of Spare Parts [Flier]. Manhattan, Kansas: K-State First.Flyer advertising Joshua Davis's author talk at Kansas State University
Steven Johnson Author Talk Poster
No full textK-State Book NetworkA poster advertising an author talk by Steven Johnson at Kansas State University on September 3, 2014. Steven Johnson's book "The Ghost Map" was the 2014-2015 common book
Data privacy in knowledge discovery
No full textThis thesis addresses data privacy in various stages of extracting knowledge embedded in databases. Advances in computer networking and database technologies have enabled the collection and storage of vast quantities of data. Legal and ethical considerations might require measures to protect an individual's privacy in any use or release of the data. In this thesis, we address the problem of preserving privacy in the two following cases: (1) in distributed knowledge discovery; (2) in situations where the output of a data mining algorithm could itself breach privacy. We present results in two different models, namely secure multiparty computation (SMC) and differential privacy. The first part of the thesis presents privacy preserving protocols in the SMC model. Secure multiparty computation involves the collaborative computation of functions based on inputs from multiple parties. The privacy goal is to ensure that all parties receive only the final output without any party learning anything beyond what can be inferred from the output. Within this framework we address the problem of preserving privacy in the preprocessing and the data mining stages of knowledge discovery in databases. For the preprocessing stage, we present private protocols for the imputation of missing data in a dataset that is shared between two parties. For the data mining stage, we introduce the notion of arbitrarily partitioned data that generalizes both horizontally and vertically partitioned data. We present a privacy-preserving protocol for k-means clustering of arbitrarily partitioned data. We also develop a new simple k-clustering algorithm that was designed to be converted into a communication-efficient protocol for private clustering. The second part of the thesis deals with privacy in situations where the output of a data mining algorithm could itself breach privacy. In this setting, we present private inference control protocols in the SMC model for On-line Analytical Processing systems. In the differential privacymodel, the goal is to provide access to a statistical database while preserving the privacy of every individual in the database, irrespective of any auxiliary information that may be available to the database client. Under this privacy model, we present a practical privacy preserving decision tree classifier using random decision trees.Ph.D.Includes abstractVitaIncludes bibliographical referencesby Geetha Jagannatha
Lockdown farmers markets in Bengaluru: Direct marketing activities and potentials for rural-urban linkages in the food system
No full textRural-urban linkages are vital elements in a sustainable food system. As the COVID-19 pandemic unfolded, supply chains were disrupted and fear of infection impacted food shopping decisions, pushing consumers to seek local and safer options for procuring fresh produce. Direct marketing arose as a promising alternative for both consumers and producers. We undertook a study in Bengaluru, India, in order to understand what direct marketing activities have unfolded with the COVID-19 pandemic. Media reports highlighted the plight of farmers struggling to market their harvest during lockdown as well as the farm to fork initiatives and lockdown farmers markets that have been created as a response. We see this moment as an opportunity to develop Bengaluru’s food system to be more sustainable, specifically through the City Region Food System framework. This study conducted online and telephone surveys with both consumers and producers in Bengaluru to explore the elements of supply and demand that have fostered and hindered direct marketing schemes. We found that consumers are interested in sourcing fruits and vegetables directly from farmers, but communication and logistics between consumers and producers are major hindrances. Although producers are diversifying their marketing strategies, they need to be implemented at economically viable scales to ensure long-term success. We find that the role of technology, specifically messaging apps, can streamline direct marketing activities and remove the barriers that currently hamper rural-urban linkages. Furthermore, existing community and farmer organizations have the size and scale to make direct marketing schemes a worthy endeavor for both consumers and producers
Food Consumption Practices of Men and Women across Rural-Urban Interface of South Indian Megacity Bangalore
No full textFood consumption pattern and Body Mass Index assessment along rural-urban interface of the South Indian mega city of Bangalore
No full textFood consumption pattern are predictors of health and nutritional status.
Bangalore is one of the rapidly urbanizing South Indian megacity with a population of 11
millions. Study highlights gradient changes with reference to food consumption pattern and
Body Mass Index (BMI) among households in the rural-urban interface of Bangalore. A total of
300 middle income households were selected by purposive random sampling technique.
Standardized schedule was used to collect information on food consumption pattern and BMI
using standard protocols. Consumption of energy dense foods was significantly more than
adequacy. Average dietary diversity score was less than 50 per cent which is indicative of
routinely consumption of only few food groups among households. Fried (51.4%) and Readyto-
eat (51.0%) foods consumption was more frequent in rural. Prevalence of overweight (24.5%)
and obesity was more in urban (7.1%). Overall, incidences of overweight and obesity were more
compared to underweight. This reveals, that there is a need for intervention and promotion of
diversified and functional foods to address overweight and obesity, which are the root causes
for non-communicable diseases in order to protect health and nutritional status of individuals
along rural-urban interface of Bangalore
Carbon-efficient virtual machine placement based on dynamic voltage frequency scaling in geo-distributed cloud data centers
No full textThe tremendous growth of big data analysis and IoT (Internet of Things) has made cloud computing an integral part of society. The prominent problem associated with data centers is the growing energy consumption, which results in environmental pollution. Data centers can reduce their carbon emissions through efficient management of server power consumption for a given workload. Dynamic voltage frequency scaling (DVFS) can be applied to control the operating frequencies of the servers based on the workloads assigned to them, as this approach has a cubic increment relationship with power consumption. This research work proposes two DVFS-enabled host selection algorithms for virtual machine (VM) placement with a cluster selection strategy, namely the carbon and power-efficient optimal frequency (C-PEF) algorithm and the carbon-aware first-fit optimal frequency (C-FFF) algorithm. The main aims of the proposed algorithms are to balance the load among the servers and dynamically tune the cooling load based on the current workload. The cluster selection strategy is based on static and dynamic power usage effectiveness (PUE) values and the carbon footprint rate (CFR). The cluster selection is also extended to non-DVFS host selection policies, namely the carbon-and power-efficient (C-PE) algorithm, carbon-aware first-fit (C-FF) algorithm, and carbon-aware first-fit least-empty (C-FFLE) algorithm. The results show that C-FFF achieves 2% more power reduction than C-PEF and C-PE, and demonstrates itself as a power-efficient algorithm for CO2 reduction, retaining the same quality of service (QoS) as its counterparts with lower computational overheads
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
sj-docx-1-pie-10.1177_09544089231207421 - Supplemental material for Analytical modelling of a multifunctional heterogeneous beam-bending analysis
No full textSupplemental material, sj-docx-1-pie-10.1177_09544089231207421 for Analytical modelling of a multifunctional heterogeneous beam-bending analysis by Narayanan Kannaiyan Geetha, Pappula Bridjesh, Balram Yelamasetti, Kuldeep K Saxena and Nakul Gupta in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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