Network effects as drivers of individual technology adoption: Analyzing adoption and diffusion of mobile communication services

Adoption research has largely ignored the dynamic impact of network effects on technology adoption and diffusion. For example, some technologies become more attractive the more social peers use them as well. But adoption at the same time increases the value for the peers and thereby their adoption decisions as well. Unfortunately, interdependencies like these make adoption and diffusion patterns very complex. Drawing on network effect theory, we develop an adoption and diffusion model that explicitly considers the role of direct and indirect network effects for individual technology adoption, using mobile commerce adoption as application example. By applying a simulation approach we can exemplify and analyze the fundamental adoption dynamics given rise to by network effects. We thereby propose a way of how to incorporate network effects into adoption research and disclose the role of the technology diffusion lifecycle for individual adoption.     

Towards a continuous microfluidic rheometer

In a previous paper we presented a way to measure the rheological properties of complex fluids on a microfluidic chip (Guillot et al., Langmuir 22:6438, 2006). The principle of our method is to use parallel flows between two immiscible fluids as a pressure sensor. In fact, in a such flow, both fluids flow side by side and the size occupied by each fluid stream depends only on both flow rates and on both viscosities. We use this property to measure the viscosity of one fluid knowing the viscosity of the other one, both flow rates and the relative size of both streams in a cross-section. We showed that using a less viscous fluid as a reference fluid allows to define a mean shear rate with a low standard deviation in the other fluid. This method allows us to measure the flow curve of a fluid with less than 250 μL of fluid. In this paper we implement this principle in a fully automated set up which controls the flow rate, analyzes the picture and calculates the mean shear rate and the viscosity of the studied fluid. We present results obtained for Newtonian fluids and complex fluids using this set up and we compare our data with cone and plate rheometer measurements. By adding a mixing stage in the fluidic network we show how this set up can be used to characterize in a continuous way the evolution of the rheological properties as a function of the formulation composition. We illustrate this by measuring the rheological curve of four formulations of polyethylene oxide solution with only 1.3 mL of concentrated polyethylene oxide solution. This method could be very useful in screening processes where the viscosity range and the behavior of the fluid to an applied stress must be evaluated.     

Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression

In this paper, we propose the application of the Kernel Principal Component Analysis (PCA) technique for feature selection in a high-dimensional feature space, where input variables are mapped by a Gaussian kernel. The extracted features are employed in the regression problems of chaotic Mackey–Glass time-series prediction in a noisy environment and estimating human signal detection performance from brain event-related potentials elicited by task relevant signals. We compared results obtained using either Kernel PCA or linear PCA as data preprocessing steps. On the human signal detection task, we report the superiority of Kernel PCA feature extraction over linear PCA. Similar to linear PCA, we demonstrate de-noising of the original data by the appropriate selection of various nonlinear principal components. The theoretical relation and experimental comparison of Kernel Principal Components Regression, Kernel Ridge Regression and ε-insensitive Support Vector Regression is also provided.     

The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications

The investigation of innovative Human-Computer Interfaces (HCI) provides a challenge for future multimedia research and development. Brain-Computer Interfaces (BCI) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as Amyotrophic Lateral Sclerosis (ALS) or spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity game, could define a new level of control possibilities also for healthy customers decoding information directly from the user’s brain, as reflected in electroencephalographic (EEG) signals which are recorded non-invasively from user’s scalp. This contribution introduces the Berlin Brain–Computer Interface (BBCI) and presents setups where the user is provided with intuitive control strategies in plausible gaming applications that use biofeedback. Yet at its beginning, BBCI thus adds a new dimension in multimedia research by offering the user an additional and independent communication channel based on brain activity only. First successful experiments already yielded inspiring proofs-of-concept. A diversity of multimedia application models, say computer games, and their specific intuitive control strategies, as well as various Virtual Reality (VR) scenarios are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates.

The introduction of sit-stand worktables; aspects of attitudes, compliance and satisfaction

The introduction of sit-stand worktables was examined in this study. Purchasers at four companies were interviewed regarding preparations prior to purchase, follow-up after installation, and if expectations had been fulfilled. Personnel at the four companies answered a questionnaire examining use of the worktables' sit-stand function, and the influence of some variables on this. Utilisation of the sit-stand function was less than what could be expected to relieve static musculoskeletal loading during VDU work. Pain experienced during the past year, and education on the use of the worktable gave rise to modest increases in utilisation. Investment in sit-stand worktables was satisfactory to purchasers, in terms of providing flexible furniture to suit modern organisational dynamics. Users were, in general, positive to the worktables, but showed poor compliance in using them. User and purchaser satisfaction with regard to improving individual health ergonomics was questionable in respect of the low level of usage.     

An oscillatory neural model of multiple object tracking

An oscillatory neural network model of multiple object tracking is described. The model works with a set of identical visual objects moving around the screen. At the initial stage, the model selects into the focus of attention a subset of objects initially marked as targets. Other objects are used as distractors. The model aims to preserve the initial separation between targets and distractors while objects are moving. This is achieved by a proper interplay of synchronizing and desynchronizing interactions in a multilayer network, where each layer is responsible for tracking a single target. The results of the model simulation are presented and compared with experimental data. In agreement with experimental evidence, simulations with a larger number of targets have shown higher error rates. Also, the functioning of the model in the case of temporarily overlapping objects is presented.     

A Chamber for Testing the Release of Volatile Substances Secreted by Animals,Especially Mammals,as Exemplified by Substances Released by Rats in Response to Stress

Abstract

The success of the testing of volatile organic compounds emitted by animals is dependent on the creation of appropriate conditions for air sampling subsequently used to assay and identify the compounds. These conditions play a particularly important role in the investigation of pheromones, which are secreted in extremely low concentrations. The authors have not come across any previous work which offers constructional solutions, which would allow avoidance of contamination of the air samples containing volatile substances secreted by animals.

A constructional solution was developed, which provides optimal conditions for their sampling and isolation. Its main advantages are as follows: the exposure chamber (the chamber in which the animal is studied) is filled with synthetic air; the exposure chamber is separated from the atmospheric air with a synthetic air “jacket”; the exposure chamber has been constructed using materials which do not release chemicals and absorb them in trace quantities.     

Differential nanofiller cluster formations in dental adhesive systems

Nanofillers are added to dental adhesives to improve mechanical properties of the hybrid layer. Ethanol or water added to the demineralized dentin to improve adhesive infiltration may produce filler aggregation. OBJECTIVE: To assess the effect of 5 vol% water or ethanol addition on nanoparticles distribution in dental adhesives. METHODS: Six available commercial adhesives systems were selected: Clearfil SE Bond (CSE), Clearfil Protect Bond (CPB), FL‐Bond (FLB), Clearfil S3 (CS3), Bond Force (BF), One Up Bond F plus (OUB), and an experimental adhesive system without filler (EXP). Polymer films were obtained by adding 0 (control) or 5 vol% water or ethanol into the bonding resins. Preparations were light‐cured (40 s). Three specimens were analyzed for each mixture. Three phases and 3D images were taken from each specimen by means of an atomic force microscope in taping mode (TM/AFM). Cluster sizes and surface nanoroughness were assessed. RESULTS: Control specimens from CSE, FLB, OUB, and BF presented clusters. The addition of solvents lead to particles aggregation in tested bonding resins. Ethanol addition produced more aggregates, particularly in adhesives containing fluoraluminosilicate as fillers. CONCLUSIONS: Nanofillers aggregation occurred in all adhesive systems in presence of additional solvents. In general, aggregate sizes were higher after the addition of ethanol. Formed clusters size values are always above the dimensions of the spaces existing between the demineralized collagen fibers. Microsc. Res. Tech. 75:749–757, 2012. © 2011 Wiley Periodicals, Inc.     

Predictable service overlay networks: Predictability through adaptive monitoring and efficient overlay construction and management

Providing bounded communication among participating nodes is significant for distributed systems. Internet-based applications suffer with lower performance due to absence of bounded latency. We describe PSON, an overlay network solution to this challenging problem. PSON has two components. The monitoring component, SyncProbe, utilizes efficient and adaptive monitoring techniques to measure latency, detect packet loss, and provide real-time estimates of maximum expected latency along paths of an Internet substrate. The QoSMap component constructs and manages overlay such that it yields application-level QoS and provides resilience against network failures. A distinctive feature of QoSMap is construction of QoS-compliant backup paths which facilitate in overlay management and operation during the period when primary overlay paths violate QoS. We evaluate PSON on PlanetLab to provide predictable communication for applications with different topology and QoS requirement. Our experiments confirm the effectiveness of PSON in providing an inexpensive and efficient application-layer solution to Internet’s unpredictable behavior.