Valuation of online social networks taking into account users’ interconnectedness

Online social networks have been gaining increasing economic importance in light of the rising number of their users. Numerous recent acquisitions priced at enormous amounts have illustrated this development and revealed the need for adequate business valuation models. The value of an online social network is largely determined by the value of its users, the relationships between these users, and the resulting network effects. Therefore, the interconnectedness of a user within the network has to be considered explicitly to get a reasonable estimate for its economic value. Established standard business valuation models, however, do not account for these aspects sufficiently. Thus, we propose an economic model for the valuation of online social networks, which takes into account the users’ interconnectedness within the network. Furthermore, we analyze different centrality measures, which can be used to quantify users’ interconnectedness in online social networks and propose a measure which is based on the PageRank-algorithm. Finally, the practical application of the model is illustrated by an example of the European online social network XING.com.     

Sensitivity analysis for simulation-based decision making: Application to a hospital emergency service design

An increasing concern of decision makers when dealing with system design is preparation for a wide range of potentially uncertain operating conditions. This paper provides a novel multiobjective approach for simulation-driven decision making that accounts for not only the conventional average system performance indices, but also (i) upper-tail, or extreme, values of these indices, and (ii) measures of their sensitivity to uncertainty in model parameters. The proposed approach is applied to a hospital emergency department service design case study wherein different design alternatives are compared using total time-in-system performance metric under multiple uncertain operating conditions.     

A low-cost real time virtual system for postural stability assessment at home

Background and objective

The degeneration of the balance control system in the elderly and in many pathologies requires measuring the equilibrium conditions very often. In clinical practice, equilibrium control is commonly evaluated by using a force platform (stabilometric platform) in a clinical environment.In this paper, we demonstrate how a simple movement analysis system, based on a 3D video camera and a 3D real time model reconstruction of the human body, can be used to collect information usually recorded by a physical stabilometric platform.

Methods

The algorithm used to reconstruct the human body model as a set of spheres is described and discussed. Moreover, experimental measurements and comparisons with data collected by a physical stabilometric platform are also reported. The measurements were collected on a set of 6 healthy subjects to whom a change in equilibrium condition was stimulated by performing an equilibrium task.

Results

The experimental results showed that more than 95% of data collected by the proposed method were not significantly different from those collected by the classic platform, thus confirming the usefulness of the proposed system.

Conclusions

The proposed virtual balance assessment system can be implemented at low cost (about 500$) and, for this reason, can be considered a home use medical device. On the contrary, astabilometric platform has a cost of about 10,000$ and requires periodical calibration. The proposed system does not require periodical calibration, as is necessary for stabilometric force platforms, and it is easy to use. In future, the proposed system with little integration can be used, besides being an emulator of a stabilometric platform, also to recognize and track, in real time, head, legs, arms and trunk, that is to collect information actually obtained by sophisticated optoelectronic systems.     

Good Enough is Good Enough: Overcoming Disaster Response Organizations’ Slow Social Media Data Adoption

Organizations that respond to disasters hold unreasonable standards for data arising from technology-enabled citizen contributions. This has strong negative potential for the ability of these responding organizations to incorporate these data into appropriate decision points. We argue that the landscape of the use of social media data in crisis response is varied, with pockets of use and acceptance among organizations. In this paper we present findings from interviews conducted with representatives from large international disaster response organizations concerning their use of social media data in crisis response. We found that emergency responders already operate with less than reliable, or “good enough,” information in offline practice, and that social media data are useful to responders, but only in specific crisis situations. Also, responders do use social media, but only within their known community and extended network. This shows that trust first begins with people and not data. Lastly, we demonstrate the barriers used by responding organizations have gone beyond discussions of trustworthiness and data quality to that of more operational issues.     

A local landscape mapping method for protein structure prediction in the HP model

The hydrophobic-polar (HP) model has been widely studied in the field of protein structure prediction both for theoretical purposes and as a benchmark for new optimization strategies. In this work we present results of the recently proposed Hybrid Monte Carlo Ant Colony Optimization heuristic in the HP model using a fragment assembly-like strategy. Moreover we extend that method introducing a general framework for optimization in the HP model, called Local Landscape Mapping, and we test it using the pull moves set to generate solutions. We describe the heuristic and compare results obtained on well known HP instances in the 3-dimensional cubic lattice to those obtained with standard Ant Colony optimization and Simulated Annealing. Fragment assembly-like tests were performed using a modified objective function to prevent the creation of overlapping walks. Results show that our method performs better than the other heuristics in all benchmark instances when the fragment assembly-like strategy is used while in the case of pull moves-based neighborhood its performance is comparable to that of simulated annealing.     

Modelling formation and growth of H2SO4-H2O aerosols: Uncertainty analysis and experimental evaluation

An aerosol dynamics model, AERO2, is presented, which describes the formation of H₂SO₄-H₂O aerosol in a smog chamber. The model is used to analyse how the uncertainties on four input parameters are propagated through an aerosol dynamics model. The input parameters are: the rate of the reaction between SO₂ and OH (k₁), the ratio between the nucleation rate used in AERO2 and that derived from classical nucleation theory (t_n), the H₂SO₄ mass accommodation coefficient () and a measure of the turbulence intensity in the reactor (k_e). Uncertainties for these parameters are taken from the literature. One of the results of the analysis is that AERO2 and aerosol dynamics models in general can only predict upper bounds for the total number (N_tot) and total volume (V_tot) concentrations of the particles. The uncertainties on N_tot and V_tot are mainly due to the uncertainties on k₁, and t_n. An uncertainty factor of 20–100 still remains when the uncertainty on k₁, is reduced to ±5%. Aerosol measurements from three smog chamber experiments have therefore been used, in an attempt to reduce the uncertainty on k₁ and t_n. Values for k₁ are obtained in the reduced range 7.8 × 10⁻¹³ to 1.0 × 10⁻¹² cm³ s⁻¹, which is within the range found in the literature. For t_n, values in the range 10⁴–10⁷ are obtained, which is close to the upper bound of the range in literature. These values for t_n are in marked contrast with a recent set of experiments on nucleation in H₂SO₄-H₂O mixtures, which suggests a value for t_n of at most 10⁻⁵.     

Design of microfluidic channels for magnetic separation of malaria-infected red blood cells

This study is motivated by the development of a blood cell filtration device for removal of malaria-infected, parasitized red blood cells (pRBCs). The blood was modeled as a multi-component fluid using the computational fluid dynamics discrete element method (CFD-DEM), wherein plasma was treated as a Newtonian fluid and the red blood cells (RBCs) were modeled as soft-sphere solid particles which move under the influence of drag, collisions with other RBCs, and a magnetic force. The CFD-DEM model was first validated by a comparison with experimental data from Han and Frazier (Lab Chip 6:265–273, 2006) involving a microfluidic magnetophoretic separator for paramagnetic deoxygenated blood cells. The computational model was then applied to a parametric study of a parallel-plate separator having hematocrit of 40 % with 10 % of the RBCs as pRBCs. Specifically, we investigated the hypothesis of introducing an upstream constriction to the channel to divert the magnetic cells within the near-wall layer where the magnetic force is greatest. Simulations compared the efficacy of various geometries upon the stratification efficiency of the pRBCs. For a channel with nominal height of 100 µm, the addition of an upstream constriction of 80 % improved the proportion of pRBCs retained adjacent to the magnetic wall (separation efficiency) by almost twofold, from 26 to 49 %. Further addition of a downstream diffuser reduced remixing and hence improved separation efficiency to 72 %. The constriction introduced a greater pressure drop (from 17 to 495 Pa), which should be considered when scaling up this design for a clinical-sized system. Overall, the advantages of this design include its ability to accommodate physiological hematocrit and high throughput, which is critical for clinical implementation as a blood-filtration system.     

Knowledge base support for dynamic information system management

Enterprise activities are governed by regulations and laws that are multiple, heterogeneous and not always easy to understand. The arising and/or the modification of these regulations and laws can cause a significant impact in the business context, especially in terms of enterprise information systems adaptation. Currently, there are many methodological and technological tools that facilitate the application of regulations and procedures, but they are not integrated enough to ensure a complete problem management. Therefore, they are not sufficient to support organizations and companies in the management of their business processes. In this paper we propose a methodological and technological solution, able to model, manage, execute and monitor business processes of complex domains. The system allows both the design of an information system and its prototyping as a web application, by the extension of an appropriately selected Business Process Management suite. During both the design and the usage phases of the prototyped information system, it is possible to interface with a knowledge base that contains information about regulations and aspects that characterize the enterprise (organizational chart, tasks, etc.).     

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

We present a preliminary study of buffer overflow vulnerabilities in CUDA software running on GPUs. We show how an attacker can overrun a buffer to corrupt sensitive data or steer the execution flow by overwriting function pointers, e.g., manipulating the virtual table of a C++ object. In view of a potential mass market diffusion of GPU accelerated software this may be a major concern.