Cooperative Profit Sharing in Coalition-Based Resource Allocation in Wireless Networks

We consider a network in which several service providers offer wireless access to their respective subscribed customers through potentially multihop routes. If providers cooperate by jointly deploying and pooling their resources, such as spectrum and infrastructure (e.g., base stations) and agree to serve each others' customers, their aggregate payoffs, and individual shares, may substantially increase through opportunistic utilization of resources. The potential of such cooperation can, however, be realized only if each provider intelligently determines with whom it would cooperate, when it would cooperate, and how it would deploy and share its resources during such cooperation. Also, developing a rational basis for sharing the aggregate payoffs is imperative for the stability of the coalitions. We model such cooperation using the theory of transferable payoff coalitional games. We show that the optimum cooperation strategy, which involves the acquisition, deployment, and allocation of the channels and base stations (to customers), can be computed as the solution of a concave or an integer optimization. We next show that the grand coalition is stable in many different settings, i.e., if all providers cooperate, there is always an operating point that maximizes the providers' aggregate payoff, while offering each a share that removes any incentive to split from the coalition. The optimal cooperation strategy and the stabilizing payoff shares can be obtained in polynomial time by respectively solving the primals and the duals of the above optimizations, using distributed computations and limited exchange of confidential information among the providers. Numerical evaluations reveal that cooperation substantially enhances individual providers' payoffs under the optimal cooperation strategy and several different payoff sharing rules.

Mutual inhibition and capacity sharing during parallel preparation of serial eye movements

Many common activities, like reading, scanning scenes, or searching for an inconspicuous item in a cluttered environment, entail serial movements of the eyes that shift the gaze from one object to another. Previous studies have shown that the primate brain is capable of programming sequential saccadic eye movements in parallel. Given that the onset of saccades directed to a target are unpredictable in individual trials, what prevents a saccade during parallel programming from being executed in the direction of the second target before execution of another saccade in the direction of the first target remains unclear. Using a computational model, here we demonstrate that sequential saccades inhibit each other and share the brain's limited processing resources (capacity) so that the planning of a saccade in the direction of the first target always finishes first. In this framework, the latency of a saccade increases linearly with the fraction of capacity allocated to the other saccade in the sequence, and exponentially with the duration of capacity sharing. Our study establishes a link between the dual-task paradigm and the ramp-to-threshold model of response time to identify a physiologically viable mechanism that preserves the serial order of saccades without compromising the speed of performance.

Sensitivity enhancement in slice-selective NMR experiments through polarization sharing

The polarization sharing technique is utilized in gradient based slice selective experiments to transfer polarization from unutilized protons to selectively excited protons. This facilitates rapid data acquisition without any customary inter-scan relaxation delay, resulting in an average of 2-fold sensitivity enhancement per unit time.

Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Relative stabilities of condensed face sharing mono- and di-carboranes: CB20H18 and C2B19H18+

The relative energies of triangular face sharing condensed macro polyhedral carboranes: CB20H18 and C2B19H18+ derived from mono- and di-substitution of carbons in (4) B21H18- is calculated at B3LYP/6-31G* level. The relative energies, H center dot center dot center dot H non-bonding distances, NICS values, topological charge analysis and orbital overlap compatibility connotes the face sharing condensed macro polyhedral mono-carboranes, 8 (4-CB20H18) to be the lowest energy isomer. The di-carba- derivative, (36) 4,4'a-C2B19H18+ with carbons substituted in a different B-12 cage in (4) B21H18- in anti-fashion is the most stable isomer among 28 possibilities. This structure has less non-bonding H center dot center dot center dot H interaction and is in agreement with orbital-overlap compatibility, and these two have the pivotal role in deciding the stability of these clusters. An estimate of the inherent stability of these carboranes is made using near-isodesmic equations which show that CB20H18 (8) is in the realm of the possible. (C) 2015 Elsevier B.V. All rights reserved.

Ink-jet printing of carbon nanotube thin film transistors

Ink-jet printing is an important process for placing active electronics on plastic substrates. We demonstrate ink-jet printing as a viable method for large area fabrication of carbon nanotube (CNT) thin film transistors (TFTs). We investigate different routes for producing stable CNT solutions ("inks"). These consist of dispersion methods for CNT debundling and the use of different solvents, such as N -methyl-2-pyrrolidone. The resulting printable inks are dispensed by ink-jet onto electrode bearing silicon substrates. The source to drain electrode gap is bridged by percolating networks of CNTs. Despite the presence of metallic CNTs, our devices exhibit field effect behavior, with effective mobility of ∼0.07 cm2 /V s and ON/OFF current ratio of up to 100. This result demonstrates the feasibility of ink-jet printing of nanostructured materials for TFT manufacture. © 2007 American Institute of Physics.

High performance nanocomposite thin film transistors with bilayer carbon nanotube-polythiophene active channel by ink-jet printing

Nanocomposite thin film transistors (TFTs) based on nonpercolating networks of single-walled carbon nanotubes (CNTs) and polythiophene semiconductor [poly [5, 5′ -bis(3-dodecyl-2-thienyl)- 2, 2′ -bithiophene] (PQT-12)] thin film hosts are demonstrated by ink-jet printing. A systematic study on the effect of CNT loading on the transistor performance and channel morphology is conducted. With an appropriate loading of CNTs into the active channel, ink-jet printed composite transistors show an effective hole mobility of 0.23 cm 2 V-1 s-1, which is an enhancement of more than a factor of 7 over ink-jet printed pristine PQT-12 TFTs. In addition, these devices display reasonable on/off current ratio of 105-10 6, low off currents of the order of 10 pA, and a sharp subthreshold slope (<0.8 V dec-1). The work presented here furthers our understanding of the interaction between polythiophene polymers and nonpercolating CNTs, where the CNT density in the bilayer structure substantially influences the morphology and transistor performance of polythiophene. Therefore, optimized loading of ink-jet printed CNTs is crucial to achieve device performance enhancement. High performance ink-jet printed nanocomposite TFTs can present a promising alternative to organic TFTs in printed electronic applications, including displays, sensors, radio-frequency identification (RFID) tags, and disposable electronics. © 2009 American Institute of Physics.

Jet diameters and velocity profiles in continuous ink-jets

Theoretical predictions of the diameters of continuous ink-jets downstream of long nozzles are generalized to include the important cases of ink-jet fluids and shorter nozzles where the velocity profile at the nozzle exit is undeveloped (non-parabolic). Comparisons of the new predictions with experiments and simulations are made for fairly long nozzles with tapered profiles and short nozzles with conical profiles; experimental and simulated profiles are also compared downstream of the nozzle exit for both industrial and large scale ink-jet print heads. Precise measurements of the un-modulated jet diameters downstream of the nozzle exit can set really useful limits to the possible shapes of the flow profile right at the nozzle exit, and in particular allow some assessment of the axial velocity gradients and fluid shear rates at the nozzle exit where direct speed measurement is usually impractical. Simulations allow further study of the relaxation of the velocity profile downstream of the nozzle exit, and are reported for both un-modulated and modulated CIJ jetting. Implications of this work include speeding up CIJ simulations, absolute calibration of the applied CIJ system modulation, and the likely magnitude of dynamic surface tension effects on observed CIJ satellite speeds.