Process Of Sharing Information Research Articles

Environmental uncertainty and entrepreneurial orientation in collectivist and individualist cultures: evidence from Brazil and Belgium

ABSTRACT A fundamental premise of the information processing approach in entrepreneurship theory is that the distribution and processing of information is key to opportunity identification. We propose that collectivist-individualist cultural values influence the efficacy of information processing leading to different levels of entrepreneurial orientation (EO). Specifically, we submit that collectivism enhances shared information processing and goal setting in a dynamic environment, while individualism facilitates creativity and divergent thinking that can help EO if sufficient informational input is available. To empirically verify our theory, we study the relationships using survey and archival data from a sample of 487 firms in six industries in Brazil and Belgium, two countries that contrast in collectivism-individualism. Consistent with our predictions, we find higher EO in the collectivist culture of Brazil under high environmental dynamism and low information availability, and this difference is increased by strategic planning.

COVID19 Sentiment Analysis using Machine Learning Classification Algorithms

Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fuelled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19’s informational crisis. The diverse use of social networking sites, like Twitter, speeds up the process of sharing information and having views on community events and health crises COVID-19 has been one of Twitter's trending areas. The Twitter messages created via Twitter are named Tweets. In this paper, we identify public sentiment associated with the pandemic using Coronavirus-specific Tweets and Python, along with its sentiment analysis packages. We provide an overview of two essential machine learning classification methods, in the context of textual analytics, and compare their effectiveness in classifying Coronavirus Tweets of varying lengths. This research provides insights into Coronavirus fear sentiment progression, associated methods, limitations, and different opportunities. In this project, we have designed a Sentiment analysis System that would identify the sentiment of a tweet and classify it into one of the five classes they include:”ExtremelyPositive”,“Positive”,”Neutral”, ”Negative” and “Extremely Negative”.

Optimizing the balance between task automation and human manual control in simulated submarine track management.

Automation can improve operator performance and reduce workload, but can also degrade operator situation awareness (SA) and the ability to regain manual control. In 3 experiments, we examined the extent to which automation could be designed to benefit performance while ensuring that individuals maintained SA and could regain manual control. Participants completed a simulated submarine track management task under varying task load. The automation was designed to facilitate information acquisition and analysis, but did not make task decisions. Relative to a condition with no automation, the continuous use of automation improved performance and reduced subjective workload, but degraded SA. Automation that was engaged and disengaged by participants as required (adaptable automation) moderately improved performance and reduced workload relative to no automation, but degraded SA. Automation engaged and disengaged based on task load (adaptive automation) provided no benefit to performance or workload, and degraded SA relative to no automation. Automation never led to significant return-to-manual deficits. However, all types of automation led to degraded performance on a nonautomated task that shared information processing requirements with automated tasks. Given these outcomes, further research is urgently required to establish how to design automation to maximize performance while keeping operators cognitively engaged. (PsycINFO Database Record

Using Neural Pattern Classifiers to Quantify the Modularity of Conflict-Control Mechanisms in the Human Brain

Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict-control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of "searchlight" classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict-control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict-control were not. Overall, these findings suggest a hybrid neural architecture of conflict-control that entails both modular (domain specific) and global (domain general) components.

Internet 2 – WWW: Where, When and Why?

Introduction General During the past decade, federal R&D agencies, the academic community and private companies have worked together to develop many of the Internet's technologies. This partnership has created a multi-billion dollar industry. Internet 2 (I2) is comprised of over 181 US research universities. These universities, working with federal research agencies and leaders of the information technology industry, teamed up to create the next stage of Internet development. The Internet 2 project is a collaboration for the development of a Next Generation Internet (NGI) for research and education that will include enhanced network services focusing on multimedia applications. The work is developmental and pre-competitive in nature (Bakos 1998). It was agreed upon that charter membership in the project remains open for a limited time to additional institutions that are in a position to commit the resources necessary for full participation. Today more than 250 institutions have committed themselves to participate in Internet 2. Objectives The objectives of the Internet 2 project were set as follows: * To maintain a common bearer service to support new and existing applications * To move from best effort packet delivery to a differentiated communications service * To provide the capabilities of tailoring network service characteristics to meet specific applications requirements * To achieve an advanced communications infrastructure for the Research and Education communities The need for a wide range of possibilities for data transmission is obvious and includes mainly current and future applications from the domains of Medicine, Education and Commerce. The list below emphasizes some of the current and future needs that encouraged the professionals to establish and develop the project (Brown 1999). * The idea that transmission rates, error rates, and other characteristics can, to some extent, be guaranteed in advance is known as Quality of Service or QoS. High Quality of Service and an efficient one-to-many broadband data transport including support for multimedia and shared information processing will be required for the broad use of distance learning (a.k.a. eLearning). * Leaders of the international research community are in need of high capacity infrastructure and selectable quality of service so that they can make effective use of national laboratories, computational facilities and large data repositories. * Medical researchers require support for remote consultation and diagnoses over highly reliable and predictable communications lines. * Physicists, and especially those who deal with vast astronomical or geophysical datasets, have similar needs. * As commercial transaction data reaches research focus, financial and economic analysts will need real-time access to masses of data. A major impediment to the realization of these applications is the lack of advanced communications services in the current commodity Internet--there is no test case, as yet, by which to prove their effectiveness, much less to implement them on a wide scale. The Novelty A number of technical and practical considerations underlie the overall architecture of the Internet 2 infrastructure. One of these is the need to minimize the overall costs of participating campuses. This is achieved by providing access to both the commodity Internet and advanced services through the same high-capacity local connection circuit. Another catered need is the accommodation of other campus programs and projects. This is done by means of a flexible regional interconnection architecture. For example, a metropolitan area network service might offer high capacity Internet services to students and faculty members. The new, key element in this architecture is the Gigapop (gigabit capacity point of presence) that presents a high capacity, state-of-the-art interconnection point where I2 participants may exchange advanced services traffic with other I2 participants. …

Shared information processing links managers and affect productivity

We aren't really sharing data or information yet. Technology is forcing us toward sharing. But we haven't learned and become skilled at shared information processing (sharing data, information, decision mechanisms, and information processors). We also haven't resolved the dilemma of sharing versus hoarding, or protecting, information. We must understand the concept of sharing and apply that understanding to shared information processing. I describe the general sharing experience. Within each sharing experience, I identify a sharing product, elements, tools, and process. In diagnosing, designing, or conducting a sharing experience, we must be able to characterize what we want from the experience and how to get what we want. I accomplish those characterizations through a model and focus on the sharing process. I'm interested in what the process does and how well the process does it. I describe the performance of the process and how the process affects the performance, or productivity, of the sharing stakeholders.