Muncie, IN, United States
Muncie, IN, United States

Ball State University, commonly referred to as Ball State or BSU, is a public coeducational research university in Muncie, Indiana, United States. On July 25, 1917, the Ball Brothers, industrialists and founders of the Ball Corporation, acquired the foreclosed Indiana Normal Institute for $35,100 and gave the school and surrounding land to Indiana. The Indiana General Assembly accepted it in the spring of 1918, with an initial 235 students enrolling at the Indiana State Normal School–Eastern Division on June 17, 1918.Ball State is classified by the Carnegie Classification of Institutions of Higher Education as a high research activity university and a member of the American Association of State Colleges and Universities. The university is composed of seven academic colleges, including the College of Architecture and Planning, the College of Communication, Information, and Media, the Miller College of Business, and Teachers College. Other institutions include Burris Laboratory School, the Indiana Academy for Science, Mathematics, and Humanities, and the Center for Business and Economic Research.Total 2013 enrollment consists of 21,053 students, 16,652 undergraduate students and 4,401 graduate students. Ball State University students hail from 48 states, two U.S. territories, 43 countries, and every one of Indiana's 92 counties. The university offers about 180 undergraduate majors and 130 minor areas of study, 175 bachelor's, 103 master's, and 17 doctoral degrees. There are 381 active student organizations and clubs on campus, including 34 fraternities and sororities. Ball State athletic teams compete in Division I of the NCAA and are known as the Ball State Cardinals. The university is a member of the Mid-American Conference and the Midwestern Intercollegiate Volleyball Association. Wikipedia.


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Chen R.,Ball State University
Decision Support Systems | Year: 2013

In this article, the author examines voluntary self-disclosure phenomenon among social networking sites. Self-disclosure enables member interactions, service customizations, targeted marketing, and digital content generation; hence the level of self-disclosure is imperative to the success of social networking sites. Yet, members are often reluctant to reveal themselves despite their desire for socialization in the ever-increasingly popular cyber community. Drawing upon relevant literature, we developed a succinct research model that identifies key stimuli and inhibitors of member self-disclosure. These influences stem from personality traits (e.g., extroversion and privacy value), networking service attributes (e.g., perceived critical mass), and computing environments (e.g., perceived Internet risk). The research model was validated through survey data collected from 222 social networking site users and the analysis results provided support to the hypothesized relationships. The current study generates new knowledge concerning the roles that varying factors play in shaping members' self-disclosure; it also informs networking service providers about how to better encourage members to reveal themselves online. © 2013 Elsevier B.V.


Chen R.,Ball State University
Decision Support Systems | Year: 2013

In this research the authors examine members' voluntary use of social networking sites. Site use leads to the growth of social relationships, increased volume of site visits and traffic, and an accumulation of user generated contents; hence it is imperative to the success of social networking sites. Drawing upon Social Exchange Theory (SET), we develop a research model that examines the major determinants of member site use behavior through a cost-benefit framework. This model also investigates the key antecedents to site use that stem from website designs, personal traits, and personal beliefs in the environment. The research model has been validated through survey data collected from 222 social networking site users, and the analysis results provide strong support to the hypothesized relationships. The current study generates new knowledge on the literature of SET and social networking sites; it also sheds lights on site management for networking service providers. © 2012 Elsevier B.V.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: MACROSYSTEM BIOLOGY | Award Amount: 190.79K | Year: 2015

The need to understand and manage ecosystems at larger regional to continental scale macrosystem levels is becoming increasingly crucial with global climate changes and impacts of exotic plants and animals in freshwater rivers and lakes. Macrosystem management requires an understanding of how different levels of spatial complexity (within a stream reach to entire river valley scales) and biotic organization (populations to ecosystems) affect the functioning of rivers and lakes. The present study will provide this information for 18 rivers spread equally between the two largest temperate steppe biomes of the world: the North American Great Plains and the Euro-Asian Steppes (including those in Mongolia). This project will provide research experiences for under-represented participants (particularly rural and Native American students), stimulate STEM program recruitment in largely under-represented (EPSCoR) states, support some faculty and students at primarily undergraduate institutions, and contribute to scientific education at both graduate and undergraduate institutions in two countries.

These rivers flow through 3 major types of ecoregions within these temperate steppe biomes: mountain steppe shrublands, short-to-tall grasslands, and semi-arid shrublands. Scientists and students from the USA and Mongolia will sample the structure and functioning of these 18 rivers in a variety of hydrogeomorphic areas, such as constricted, meandering, braided, and anastomosing channel sections. Despite their similarity in biome and ecoregional types, the river macrosystems of the Great Plains and the Mongolian steppes vary substantially in fauna, flora, and community through ecosystem functioning. These variations result from differences in climatic patterns, the degree of riverine landscape modification (e.g., by dams, levees, and riparian modification), and the naturalness of the resident fauna. For example, most rivers in the USA contain some dams and many exotic fauna have been introduced, while the vast majority of Mongolian rivers contain no dams and their aquatic fauna is almost exclusively natural and different from those in the USA. Moreover, the Central Asian subcontinental area of Mongolia has one of the strongest warming signals on earth, with air temperatures rising three times faster than the overall northern hemisphere average. Consequently, riverine macrosystems in the USA can help predict changes to Mongolian rivers as a result of pending dam construction and possible species introductions to some rivers, while knowledge of responses of Mongolian macrosystems to more rapid climatic changes can help predict future effects in U.S. rivers. Therefore, this projects goals are to: (a) compare and contrast hierarchical scaling relationships and effects of system drivers and cross-scale interactions on rivers in similar biomes and ecoregions of the two continents; and (b) evaluate effects of climatic changes and anthropogenic disturbance to these river macrosystems.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: MAJOR RESEARCH INSTRUMENTATION | Award Amount: 196.97K | Year: 2015

With this award from the Major Research Instrumentation (MRI) and Chemistry Research Instrumentation and Facilities (CRIF) programs, Ball State University will acquire a liquid chromatography-mass ppectrometry (LC-MS) system. The system is used to determine the composition of mixtures of materials obtained from various sources including samples obtained from chemical syntheses, environmental or biological sources. In this instrument the liquid chromatograph (LC) separates the complex mixture into its individual components, then mass spectrometer (MS) is used to determine the mass of the components by measuring the mass to charge ratio (m/z) of ions produced from the components. LC-MS is a powerful analytical tool for finding out what the components are in a complex sample. The instrument will be used by students in their research, training them for its usage in their careers. It will also be used in outreach to disabled students and underrepresented groups.


The instrument will be used in research especially in areas such as (a) characterizating nitrogen heterocycles for materials and medicine; (b) designing RNA nanovehicles for drug delivery in phototherapy; (c) studying photochemistry of organic pollutants at air-water interface; (d) determining the role of mammalian CDC42 in cell signaling pathways with implications in bacterial infections; (e) understanding of the mechanism of apolipoprotein beta degradation with relevance to cholesterol related pathologies; (f) studying nanoparticle catalyzed photodegradation of organic compounds for environmental remediation; and (g) enabling the elucidating chemistry emanating from highly reactive aryl nitrenes and oxypyridinium salts to access synthetically useful motifs.


Grant
Agency: NSF | Branch: Continuing grant | Program: | Phase: INDUSTRY/UNIV COOP RES CENTERS | Award Amount: 541.57K | Year: 2015

The Security and Software Engineering Research Center (S2ERC) is an Industry/University Cooperative Research Center devoted to applied and basic research addressing security and software engineering issues that plague both industrial (defense and commercial) companies and government agencies. Nearly all companies market products and services that involve software. The software is either a commercial product or a supporting technology for other products or services. Advances in software engineering are critical to the technical dominance and market performance not only of IT companies, but also of producers of products such as aircraft and their components, automobiles, medical devices, sensors, computer-aided diagnostics and robotics. Software developers and customers desire software that costs less, matches users needs, is secure, has credible defenses and fewer defects, executes faster, is easier to update and is completed on time. With societies growing dependence on software, it is important that software engineers build secure software cost-effectively and reliably. The investment in S2ERC has the potential to produce significant results given the expertise at the university sites, the many technical affiliate partners, and the importance of software to our national security and competitiveness. S2ERC researchers are focused on discovering unique solutions for security and software engineering issues which in turn benefits the whole of society as technology is properly constructed and managed.

The S2ERCs technical goals are the creation and transfer of innovative software technologies and engineering skills to its affiliates and the training of both graduate and undergraduate students in promising research directions. The S2ERC research initiatives include intrusion detection, ad-hoc network security, wireless security, attack-tolerant systems, trustworthiness in cloud and mobile applications, security and vulnerability analyses, information protection, requirements capturing, software design, software metrics, software feature analysis, software testing, software reliability, user interface design, usability issues, global software development, migrating software to multi-core architectures, visualization environments, interactive collaborative environments, dynamic and static analyses, and testing and model checking for concurrent programs. As S2ERC partners with industry and federal agencies, it is expected that security and software engineering research will continue to integrate into broader programs and activities of national interest.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: ARCHAEOLOGY | Award Amount: 262.66K | Year: 2014

Social scientists need to better understand the processes through which social interactions at multiple scales lead to the emergence and integration of larger social groups such as communities and societies. These processes are not limited to modern societies, and studying them in prehistoric contexts adds a deeper understanding of these processes. Drs. Mark A. Hill, Kevin C. Nolan, and Mark F. Seeman seek to understand the social world of prehistoric groups commonly referred to as Ohio Hopewell. Hopewell (ca. 50 AD-350 AD) has captivated scholars and the public alike for over a century. This study applies Social Network Analysis (SNA) to discover the differing scales and nature of interaction that will allow a reconstruction of the texture of variable group membership in Ohio Hopewell. This will not only help to understand the broad sweep of prehistory and the specific social realities that molded the past, but will also provide a better understanding of the integration of human social groups in general.

There is no one Hopewell; the many Hopewell-linked groups are characterized by variable participation in a variety of information and goods exchange networks. Until explicit and robust methods of classification and analysis are applied to understanding social interaction and integration, researchers will be unable to grasp the complexity, detail, and meaning of each overlying network. SNA has been successfully used in ethnographic and archaeological research around the world, and is now the most appropriate tool for beginning to disentangle the complex web that forms Ohio Hopewell. SNA offers a robust and objective set of quantitative methods for reconstructing connections among groups and its application here will be the first in the region, and among the first in eastern North America. This study, assumes that what falls under the Ohio Hopewell rubric is a series of dispersed family clusters choosing to participate variably in networks at a number of related, but distinct scales. Many divisions of Ohio Hopewell have been proposed; however, there has been no consistent or replicated method or conclusion of network classification. As a first step, the research focuses on Ohio Hopewell communities within the Scioto River watershed of southcentral Ohio. The project analyzes three explicit spatial scales of interaction through a combination of micro- and macro-stylistic attributes, and raw material source analysis. (1) The local/community level is targeted by a series of ceramic production traits which would be learned through enculturation and apprenticeships but not readily visible to outsiders (micro-style). (2) The regional/intercommunity level is targeted by analyzing the distribution of lithic raw material proportions and ceramic vessel elements that are externally observable (macro-style) and can be transmitted among communities. (3) The extra-regional scale of interaction is targeted by the sourcing of rare exotic materials (copper, silver) via Laser Ablation Inductively Couple Plasma Mass Spectrometry.

There will be patterns (and potentially many) at each scale. With this multi-scalar approach, the project will build a detailed picture of how the larger Ohio Hopewell networks are constructed from the bottom up, by families and communities.


Grant
Agency: NSF | Branch: Continuing grant | Program: | Phase: RES IN NETWORKING TECH & SYS | Award Amount: 134.35K | Year: 2016

Networks with higher degrees of complexity generally require more manual intervention to manage, are more difficult to reason about, and are more prone to human errors. Despite its critical importance, complexity remains one of the least understood aspects of a network, and has not been well characterized or modeled. There is a general perception that for the same target network multiple designs often exist to meet the same set of operational objectives (e.g., security and resiliency requirements), and that some designs could be significantly easier to manage than others; however the decisions on complexity are typically made subjectively or via qualitative terms.

This project aims at developing a fundamentally new understanding of, and metrics and models for, network complexity. The project studies how a networks design characteristics impact the complexity in its management, through a novel white-box approach that involves reverse-engineering the network design from device configurations, identifying design patterns that differ from conventional wisdom, and iterative discussions with network operators to capture perceived complexity. A suite of bottom-up metrics will be developed to accurately quantify the complexity of a given design. These metrics enable comparisons of alternative design proposals and what-if analyses of how design changes might impact the management complexity. A top-down framework will be developed to model the interplay among network design, operational objectives, and the resulting management complexity. The framework formally abstracts the objectives of a given design task thus allowing reasoning about whether and how a combination of design primitives will meet those objectives, decomposes the design task into its constituent primitives, and applies the metrics to quantify the complexity of individual primitives.

If successful this project will advance the state-of-the-art in understanding, quantifying, and modeling network complexity. The modeling framework enables complexity-aware top-down network design by guiding the search through the design space. The insights obtained from this project may inform the design of future network architectures, management applications, and configuration languages. The projects PI will actively interact with the research community, operator community, and Internet Engineering Task Force to disseminate the research findings. Results from the project will be incorporated into graduate-level network management classes. As Florida International University is a designated Hispanic-serving institution, this project will serve as a vehicle to advance the involvement of underrepresented minorities in computer science research.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Secure &Trustworthy Cyberspace | Award Amount: 100.00K | Year: 2015

Nontechnical Description
According to recent reports in the press, the Office of Personnel Management (OPM) was hit hard in two recent cyber-attacks (OPM 2015). In April 2015, OPM discovered that personal data (e.g., Social Security Numbers, full name, and birth date) of 4.2 million current and former Federal government employees had been stolen (referred to as personnel records incident hereafter). Later in June 2015, OPM discovered that around 21.5 million employees - current and former Federal employees and contractors - were affected as their personal information such as Social Security Numbers, fingerprints, and background investigation records were compromised (referred to as background investigation records incident hereafter). Unlike other information, sensitive data such as the background investigation records, which include personal histories, relationships, and biometrics, reveal employees personal lives are difficult to be re-issued. Typical protection such as a few months of credit monitoring may be insufficient in protecting victims from determined attackers. To date, little is known about how and why people decide and act in the aftermath of breaches involving their personal data. In particular, the role of data breach fatigue, manifested by insensitivity to data breaches and low estimate of fraud loss, in affecting peoples decisions and actions is unknown. The existing research has also been silent on employees decision making and reactions in response to data breaches. To fill this research gap, in this proposal, we plan to conduct a study that reveals the key decision factors, response actions, and the potential effect of data breach fatigue in the context of anxiety over the possible outcomes of the breach. Findings of the study will help in understanding employee reactions towards data breaches. New knowledge will help industry and policy makers develop intervention strategies that avert the effect of breach fatigue

Technical Description
This proposal will explore the crucial issues that influence employees responses in the context of the recent two OPM data breach incidents. This proposed research will compare these two different incidents and their impacts on different types of victims, employees who receive notification of the personnel records incident (now), employees who receive notification of both incidents (future), and employees who only receive notification of the background investigation records incident (future). We will also survey employees who have not received any notification, as a control group. In addition to self-reported data through surveys, we shall extend this study by capturing organic Twitter messages related to the two breach incidents in the respective time periods in 2015 to study how people coped with breach incidents. Utilizing natural language processing, we intend to (1) explore patterns of discourses associated with the data breach fatigue, (2) extract coping mechanisms from the discourses, and (3) compare coping mechanisms of employees, identified from the survey and those derived from the data mining.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Macromolec/Supramolec/Nano | Award Amount: 295.60K | Year: 2016

In this project funded by the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Sergiy Rosokha of the Department of Chemistry at Ball State University studies intermolecular interactions between molecules that have a halogen atom (fluorine, chlorine, bromine, iodine) and molecules with a negative charge (anions). These types of chemical interactions are recognized as a powerful tool for recognizing molecules, preparing materials, and designing pharmaceuticals. Professor Rosokha is studying the role of these novel types of intermolecular interactions in facilitating certain chemical reactions. These mechanistic studies should aid the development of more efficient synthetic methods and the study of chemical reactions in the environment. Professor Rosokha is also providing research and training opportunities for undergraduate and masters students at Ball State University.

Professor Rosokha is studying the mechanistic role of anion-pi and halogen-bonded complexes in electron-transfer reactions. More generally, he is addressing solution-phase chemical transformations of both halogenated electrophiles and anionic nucleophiles. Through a combination of spectral (UV-Vis, FT-IR, NMR, ESR) measurements, electrochemical, X-ray structural studies, and computational analysis, Professor Rosokha is establishing the structural, thermodynamic and spectral characteristics of highly-reactive pre-equilibrium halogen-bonded and anion-pi complexes. The properties of these complexes are then being used to explain, predict and, ultimately, control kinetics and stereochemistry of the reactions of halogen-containing molecules with anions.


Patel P.C.,Ball State University
Journal of Operations Management | Year: 2011

Increased firm formalization helps emerging firms develop stable routines and processes to increase their chances of survival. However, uncertain and dynamic task environments of emerging firms require more flexible organizational structures. Such duality of structural prescriptions stems from competing demands of task and institutional environments. We propose that manufacturing flexibility could help decouple activities required in task environments from those required in institutional environments, thereby mitigating the conflict of adopting flexible and rigid structures at the same time. An emerging venture could meet demands of institutional environments through formalized structures, and use manufacturing flexibility to address needs of task environment in order to mitigate liabilities of newness. Using a sample of 167 high-technology manufacturing firms in the UK, we use a moderated polynomial regression approach to test the proposed framework. Results indicate that formalized structures in conjunction with manufacturing flexibility lead to enhanced performance. The findings extend literature on organizational structures in operations management and entrepreneurship. © 2010 Elsevier B.V.

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