Thomas D. Griffin

Recognition enhancement by linear tournament verification

The recent significant enhancement of OCR systems recognition rates has been driven mainly by combining different feature sets or by adopting a voting scheme using multiple independent algorithms. Voting is effective but computationally expensive. A general framework for economical enhancement of recognition rate that focuses on a critical reordering of a few top candidates is described. After the execution of the base OCR algorithm (a three-layer neural network), a linear tournament verification is executed using one-to-one small network verifiers to improve the ordering of the top candidates. Thirty-four one-to-one verifiers were developed for the uppercase English alphabet. Fourteen of these use special features; however, the rest use the same features as those in the base algorithm. On the NIST uppercase data set, the recognition rate for the new system is 95.8%, showing a 1.2% improvement over the system without verification. Although the improvement is modest, the costs in both efficiency and development effort are small.<<ETX>>

Using adaptive read voltage thresholds to enhance the reliability of MLC NAND flash memory systems

NAND Flash memory is not only the ubiquitous storage medium in consumer applications, but has also started to appear in enterprise storage systems as well. MLC and TLC Flash technology made it possible to store multiple bits in the same silicon area as SLC, thus reducing the cost per amount of data stored. However, at current sub-20nm technology nodes, MLC Flash devices fail to provide the levels of raw reliability, mainly cycling endurance, that are required by typical enterprise applications. Advanced signal-processing and coding schemes are needed to improve the Flash bit error rate and thus elevate the device reliability to the desired level. In this paper, we report on the use of adaptive voltage thresholds in the read operation of NAND Flash devices. We discuss how the optimal read voltage thresholds can be determined, and assess the benefit of adapting the read voltage thresholds in terms of cycling endurance, data retention and resilience to read disturb.

SIMPLE: A Strategic Information Mining Platform for Licensing and Execution

Intellectual Properties (IP), such as patents and trademarks, are one of the most critical assets in today’s enterprises and research organizations. They represent the core innovation and differentiators of an organization. When leveraged effectively, they not only protect a business from its competition, but also generate significant opportunities in licensing, execution, long term research and innovation. In certain industries, e. g., Pharmaceutical industry, patents lead to multi-billion dollar revenue per year. In this paper, we present a holistic information mining solution, called SIMPLE, which mines large corpus of patents and scientific literature for insights. Unlike much prior work that deals with specific aspects of analytics, SIMPLE is an integrated and end-to-end IP analytics solution which addresses a wide range of challenges in patent analytics such as the data complexity, scale, and nomenclature issues. It encompasses techniques for patent data processing and modeling, analytics algorithms, web interface and web services for analytics service delivery and end-user interaction. We use real-world case studies to demonstrate the effectiveness of SIMPLE.

A digital library system for periodicals distribution

As part of IBMs Digital Library Initiative, IBMs Almaden Research Center has teamed with the Institute for Scientific Information in a joint project to deliver on-line access to the bibliographic information and abstracts from the scientific journal articles indexed in Current Contents/Life Sciences as well as articles offered by the respective publishers. This requires both adaptation of existing technologies and development of new capabilities, especially regarding copyright protection. Since the Fall of 1995, a pilot system has been installed at four universities, two corporate libraries, and a major public research library, beginning a study that involves many publishers, libraries, and users to test the system and to experiment with new economic models. This article describes some requirements we identified for this system, and the solutions we have devised for these requirements.

SIMPLE: Interactive Analytics on Patent Data

Intellectual Properties (IP), such as patents and trademarks, are one of the most critical assets in today’s enterprises and research organizations. They represent the core innovation and differentiators of an organization. When leveraged effectively, they not only protect freedom of action, but also generate significant opportunities in licensing, execution, long term research and innovation. In this paper, we expand upon a previous paper describing a solution called SIMPLE, which mines large corpus of patents and scientific literature for insights. In this paper we focus on the interactive analytics aspects of SIMPLE, which allow the analyst to explore large unstructured information collections containing mixed information in a dynamic way. We use real-world case studies to demonstrate the effectiveness of interactive analytics in SIMPLE.

Enhancing the Reliability of MLC NAND Flash Memory Systems by Read Channel Optimization

NAND flash memory is not only the ubiquitous storage medium in consumer applications but has also started to appear in enterprise storage systems as well. MLC and TLC flash technology made it possible to store multiple bits in the same silicon area as SLC, thus reducing the cost per amount of data stored. However, at current sub-20nm technology nodes, MLC flash devices fail to provide the levels of raw reliability, mainly cycling endurance, that are required by typical enterprise applications. Advanced signal processing and coding schemes are needed to improve the flash bit error rate and thus elevate the device reliability to the desired level. In this article, we report on the use of adaptive voltage thresholds and cell-to-cell interference cancellation in the read operation of NAND flash devices. We discuss how the optimal read voltage thresholds can be determined and assess the benefit of cancelling cell-to-cell interference in terms of cycling endurance, data retention, and resilience to read disturb.

Effect of Read Disturb on Incomplete Blocks in MLC NAND Flash Arrays

The effect of read disturb on partially programmed blocks of MLC NAND is evaluated using experimental data from 2y-, 1y- and 1x-nm Flash memory devices. We demonstrate that when a partially programmed block is exposed to a large number of reads before it is finalized in terms of page programming, the remaining pages will exhibit a significant bit error-rate (BER) increase. The page-BER is characterized in terms of program-erase cycles and read cycles and is further analyzed based on the programmed threshold voltage distributions. The impact of the page programming algorithm is also discussed.

The Almaden Distributed Digital Library System

In this chapter we describe the architecture for the Almaden Distributed Digital Library System, which is intended to support an emerging “information marketplace”. Using a distributed server approach and accommodating heterogeneous environments, the system is designed to meet the diverse needs of the publishers, distributors, and users of scientific journal information at low cost, while protecting the information assets of the publishers and the privacy of the users. A prototype is currently being implemented in a joint effort by IBM Almaden Research Center and the Institute for Scientific Information. A pilot is planned to test the system and to explore new economic models.

Advanced search system for IT support services

IBMs Technical Support Services division runs remote support centers, where agents provide phone support for client problems related to IBM and non-IBM hardware and software products. Support center personnel use numerous pieces of information—including many searches, log files, and records of historical support tickets, from disparate data sources—to recommend solutions for customer technical problems. We have built an advanced search system to assist support agents who are resolving customer service requests and improving our client experience. The system has been deployed and used globally by thousands of support center personnel. In this paper, we describe the systems architecture, the technical challenges, and the innovative solution we have built. In addition, we discuss the novel ideas to address the unique requirements and challenges of the support services domain. These ideas include using system logs and domain knowledge to automatically expand agent queries, incorporating implicit agent feedback, and selecting features to extract useful information from highly unstructured and noisy ticket data. Results on the effectiveness of the system are presented. We also discuss future work on enhancing the systems capability to automatically diagnose customer hardware and software problems and remediate them.

An iBeacon Training App for Indoor Fingerprinting

Indoor positioning systems have become widely available due to the increased number of wireless technologies available today. A type of wireless device that has become very popular in the past years has been the Bluetooth Low Energy (BLE) beacon. This compact, battery-powered device can enable location-based and proximity services across in-door spaces. Several indoor positioning techniques have been explored to achieve indoor localization using these wireless devices. One of these techniques is the fingerprinting technique, which requires careful collection of training data at known locations. We developed an app to facilitate and expedite the process of collecting training data with iOS devices. The training data is collected by our app and saved in the cloud for future retrieval. We collected training data from different floor maps, performed initial analysis on this data, and tested a fingerprinting algorithm in order to provide indoor localization. We developed several tools to evaluate and visualize the training data and tested our indoor localization algorithm in a real-time scenario.