Collusion in the Indian Tea Industry in the Great Depression : An Analysis of Panel Data

This paper analyzes the effectiveness of the control schemes in the Indian tea industry during the Great Depression, whereby producers attempted to collude by reducing output. Analysis of data from a panel of plantations shows that collusion was effective. We suggest that the system of management of plantations by "managing agents" enhanced the degree of monopoly in the industry, thereby facilitating collusion. The social cohesiveness of expatriate business may have also contributed to the enforcement of collusion.

A Relation Between Network Computation and Functional Index Coding Problems

In contrast to the network coding problem wherein the sinks in a network demand subsets of the source messages, in a network computation problem the sinks demand functions of the source messages. Similarly, in the functional index coding problem, the side information and demands of the clients include disjoint sets of functions of the information messages held by the transmitter instead of disjoint subsets of the messages, as is the case in the conventional index coding problem. It is known that any network coding problem can be transformed into an index coding problem and vice versa. In this work, we establish a similar relationship between network computation problems and a class of functional index coding problems, viz., those in which only the demands of the clients include functions of messages. We show that any network computation problem can be converted into a functional index coding problem wherein some clients demand functions of messages and vice versa. We prove that a solution for a network computation problem exists if and only if a functional index code (of a specific length determined by the network computation problem) for a suitably constructed functional index coding problem exists. And, that a functional index coding problem admits a solution of a specified length if and only if a suitably constructed network computation problem admits a solution.Comment: 3 figures, 7 tables and 9 page

Helicopter external noise prediction and correlation with flight test

Mathematical analysis procedures for predicting the main and tail rotor rotational and broadband noise are presented. The aerodynamic and acoustical data from Operational Loads Survey (OLS) flight program are used for validating the analysis and noise prediction methodology. For the long method of rotational noise prediction, the spanwise, chordwise, and azimuthwise airloading is used. In the short method, the airloads are assumed to be concentrated at a single spanwise station and for higher harmonics an airloading harmonic exponent of 2.0 is assumed. For the same flight condition, the predictions from long and short methods of rotational noise prediction are compared with the flight test results. The short method correlates as well or better than the long method

Formation of iron nitride thin films with Al and Ti additives

In this work we investigate the process of iron nitride (Fe-N) phase formation using 2 at.% Al or 2 at.% Ti as additives. The samples were prepared with a magnetron sputtering technique using different amount of nitrogen during the deposition process. The nitrogen partial pressure (\pn) was varied between 0-50% (rest Argon) and the targets of pure Fe, [Fe+Ti] and [Fe+Al] were sputtered. The addition of small amount of Ti or Al results in improved soft-magnetic properties when sputtered using \pn $\leq$ 10\p. When \pn is increased to 50\p non-magnetic Fe-N phases are formed. We found that iron mononitride (FeN) phases (N at% $\sim$50) are formed with Al or Ti addition at \pn =50% whereas in absence of such addition \eFeN phases (N\pat$\sim$30) are formed. It was found that the overall nitrogen content can be increased significantly with Al or Ti additions. On the basis of obtained result we propose a mechanism describing formation of Fe-N phases Al and Ti additives.Comment: 9 Pages, 7 Figure

An Efficient Analytical Solution to Thwart DDoS Attacks in Public Domain

In this paper, an analytical model for DDoS attacks detection is proposed, in which propagation of abrupt traffic changes inside public domain is monitored to detect a wide range of DDoS attacks. Although, various statistical measures can be used to construct profile of the traffic normally seen in the network to identify anomalies whenever traffic goes out of profile, we have selected volume and flow measure. Consideration of varying tolerance factors make proposed detection system scalable to the varying network conditions and attack loads in real time. NS-2 network simulator on Linux platform is used as simulation testbed. Simulation results show that our proposed solution gives a drastic improvement in terms of detection rate and false positive rate. However, the mammoth volume generated by DDoS attacks pose the biggest challenge in terms of memory and computational overheads as far as monitoring and analysis of traffic at single point connecting victim is concerned. To address this problem, a distributed cooperative technique is proposed that distributes memory and computational overheads to all edge routers for detecting a wide range of DDoS attacks at early stage.Comment: arXiv admin note: substantial text overlap with arXiv:1203.240