Comment: Monitoring Networked Applications With Incremental Quantile Estimation

Our comments are in two parts. First, we make some observations regarding the methodology in Chambers et al. [arXiv:0708.0302]. Second, we briefly describe another interesting network monitoring problem that arises in the context of assessing quality of service, such as loss rates and delay distributions, in packet-switched networks.Comment: Published at http://dx.doi.org/10.1214/088342306000000600 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

SOME FORENSIC ASPECTS OF BALLISTIC IMAGING

Analysis of ballistics evidence (spent cartridge casings and bullets) has been a staple of forensic criminal investigation for almost a century. Computer-assisted databases of images of ballistics evidence have been used since the mid-1980s to help search for potential matches between pieces of evidence. In this article, we draw on the 2008 National Research Council Report Ballistic Imaging to assess the state of ballistic imaging technology. In particular, we discuss the feasibility of creating a national reference ballistic imaging database (RBID) from test-fires of all newly manufactured or imported firearms. A national RBID might aid in using crime scene ballistic evidence to generate investigative leads to a crime gun’s point of sale. We conclude that a national RBID is not feasible at this time, primarily because existing imaging methodologies have insufficient discriminatory power. We also examine the emerging technology of micro- stamping for forensic identification purposes: etching a known identifier on firearm or ammunition parts so that they can be directly read and recovered from crime scene evidence. Microstamping could provide a stronger basis for identification based on ballistic evidence than the status quo, but substantial further research is needed to thoroughly assess its practical viability

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Introduction to Exotics and Trans-Boundary Movement of Aquatic Organisms: Policy Requirements and Relevance to Indian Aquaculture in the Post-WTO Scenario

Aquaculture is one of the fastest growing industries with an annual growth rate of more than 11 per cent for the past 10 years, producing about 16 per cent of the world supply of animal protein, primarily for human consumption. FAO (2007) has estimated the production from aquaculture at 47.8 million tonnes in 2005 and the global aquaculture production in comparison has overtaken the global production of meat from bovine, ovine, porcine and poultry. Global aquaculture production has jumped from a mere 3.9 per cent of the food produced in 1970 to an impressive 47 per cent in 2006, which indicates a 10 per cent per annum growth. The Indian aquaculture sector led by shrimp and carp farming has recorded an impressive growth during the past decades, raising itself to the status of an industry and a major source of foreign exchange to the country to the tune of @15000 crores/year. The strength of Indian aquaculture lies in (a) large water bodies suitable for aquaculture, (b) tropical Climate, (c) species diversity and (d) availability of cheap labour. While the weakness include (a) unregulated development, (b) disease problems and (c) lack of scientific approaches and (d) non-compliance with guidelines and regulations

Diseases in Ornamental Fishes

Any impairment that interferes with the performance of normal funcrions including responses to environmental factors, roxicants, dimare, nutrition, infectious agents etc can be termed a disease. Diseases can be caused by a variety of factors, the most important being pathogens. Other factors contributing cowards the development of disease conditions include stress, environmental/water qualiry, physical agents, nutritional imbalance, toxins etc. or a combination of these

Wireless Emitter Location Estimation Based on Linear and Nonlinear Algorithms using TDOA Technique

Low-power devices such as cell phones, and wireless routers are commonly used to control Improvised Explosive Devices (IEDs) and as the communication nodes for the sake of command and control. Quickly locating the source of these signals is ambitious, specifically in a metropolitan environment where buildings and towers may cause intervention. This presents a geolocation system that compounds the attributes of several proven geolocation and error mitigation methods to locate an emitter of interest in an urban environment. The proposed geolocation system uses a Time Difference of Arrival (TDOA) approach to estimate the position of the emitter of interest. Using multiple sensors at known locations, TDOA estimates are achieved by the cross-correlation of the signal received at all the sensors. A Weighted Least Squares (WLS) solution, Linear least Square (LLS) method and maximum likelihood (ML) estimation is used to estimate the emitter's location. If the variance of this location estimate is too high, a sensor is detected and identified as possessing a Non-Line of Sight (NLOS) path from the emitter. This poorly located sensor is then removed from the geolocation system and a new position estimate is computed with the remaining sensor TDOA information. The performance of the TDOA system is determined through modeling and simulations. Test results confirm the feasibility of identifying a NLOS sensor, thereby improving the geolocation system's accurateness in a metropolitan environment

Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models

Low-order functional ANOVA (fANOVA) models have been rediscovered in the machine learning (ML) community under the guise of inherently interpretable machine learning. Explainable Boosting Machines or EBM (Lou et al. 2013) and GAMI-Net (Yang et al. 2021) are two recently proposed ML algorithms for fitting functional main effects and second-order interactions. We propose a new algorithm, called GAMI-Tree, that is similar to EBM, but has a number of features that lead to better performance. It uses model-based trees as base learners and incorporates a new interaction filtering method that is better at capturing the underlying interactions. In addition, our iterative training method converges to a model with better predictive performance, and the embedded purification ensures that interactions are hierarchically orthogonal to main effects. The algorithm does not need extensive tuning, and our implementation is fast and efficient. We use simulated and real datasets to compare the performance and interpretability of GAMI-Tree with EBM and GAMI-Net.Comment: 25 pages plus appendi