Steven J. Simske

Steven J. Simske
Colorado State University | CSU · Systems and Mechanical Engineering

About

373
Publications
52,308
Reads
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5,323
Citations
Introduction
Steven J. Simske is currently a Professor in Systems and Mechanical Engineering at Colorado State University. Steven does research in Algorithms, Analytics, Imaging, Supply Chain, Sensing and Intelligent Bots.
Additional affiliations
January 2018 - present
Colorado State University
Position
  • Professor
January 2000 - present
HP Inc.
Position
  • HP Fellow
January 1988 - August 1994
University of Colorado
Position
  • Professor

Publications

Publications (373)
Article
Huge advances in peer-to-peer systems and attempts to develop the semantic web have revealed a critical issue in information systems across multiple domains: the absence of semantic interoperability. Today, businesses operating in a digital environment require increased supply-chain automation, interoperability, and data governance. While research...
Article
Full-text available
Greenhouse gas emission is a major contributor to climate change and global warming. Many sustainability efforts are aimed at reducing greenhouse gas emissions. These include recycling and the use of renewable energy. In the case of recycling, the general population is typically required to at least temporarily store, and possibly haul, the materia...
Article
Extractive summarization is an important natural language processing approach used for document compression, improved reading comprehension, key phrase extraction, indexing, query set generation, and other analytics approaches. Extractive summarization has specific advantages over abstractive summarization in that it preserves style, specific text...
Article
Full-text available
High-density, high-permanence forms of carbon storage are in demand to save storage space on land or at sea while allowing the world to reach its climate targets. Biochar and calcium carbonate are two such forms that have been considered largely separately in the literature for carbon storage. In this paper, we consider how biochar and calcium carb...
Preprint
Full-text available
Businesses operating in a digital world require increased automation, interoperability, and data governance for supply chain activities. A substantial amount of data generated by these operations remains unused, disconnected, or latent. The purpose of this research is to demonstrate how semantic web development can leverage ontologies to optimise d...
Article
A reference architecture (RA) provides a common frame of reference with a common vocabulary, reusable designs, and principles that may be applied to future architectures. It can promote re-use of best practices, improve interoperability, and improve awareness of a system under development of the same mindset. The next version of the Department of D...
Article
The emergence of blockchain technology has sparked significant attention from the supply chain management (SCM) and logistics communities. In this paper, we present the results from a thorough bibliometric review that analytically and objectively identifies the intellectual structure of this field, the seminal papers, and the most influential schol...
Article
Full-text available
Blockchain can function as a foundational technology with numerous applications in smart cities. The objective of this paper is twofold. First, it provides a detailed overview of the extant literature on blockchain applications in smart cities; second, it reveals the trends and suggests future research directions for scholars who wish to contribute...
Article
Full-text available
This study examines the potentials and challenges of drones, or unmanned autonomous vehicles (UAVs), in supply chain management (SCM) and logistics. A systematic literature review was performed to capture the dynamics surrounding drones and to provide a timely and comprehensive overview of what has been studied so far and what needs to be investiga...
Article
Full-text available
This study investigates the capabilities, performance outcomes, and barriers of drones applied to humanitarian logistics (HL). A systematic literature review was conducted to synthesize prior research on drones and cumulatively identify current knowledge gaps which require further investigation. In order to identify the relevant literature on the t...
Article
In 2006, the French government discretely asked for an assessment of the highest accuracy means available at the time to translate Russian speech into French text. One of us was working with the Grenoble HP site at the time, and so promptly assessed the possibilities using existing speech-to-text and translation software (Nuance and Speechworks). T...
Article
Purpose The purpose of this study is to investigate the potentials of blockchain technologies (BC) for supply chain collaboration (SCC). Design/methodology/approach Building on a narrative literature review and analysis of seminal SCC research, BC characteristics are integrated into a conceptual framework consisting of seven key dimensions: inform...
Article
The demand for object tracking (OT) applications has been increasing for the past few decades in many areas of interest, including security, surveillance, intelligence gathering, and reconnaissance. Lately, newly-defined requirements for unmanned vehicles have enhanced the interest in OT. Advancements in machine learning, data analytics, and AI/dee...
Article
In some traditional development processes, engineering teams communicate their subsystem interfaces without much overlap o their respective disciplines and processes. However, for a systems engineering-driven design, a holistic, multidisciplined approach is implemented from the ground up, with considerable overlap between the teams in every phase o...
Article
A novel method is presented for evaluating the efficacy of object recognition algorithms on occluded images, called the occluded image function (OIF). The OIF describes system behavior in occluded environments and thus gives qualitative insight into their mechanisms; derivative metrics from OIF can also be used to quantitatively compare classifiers...
Article
Full-text available
This study reviews Internet of Things (IoT) research in supply chain management (SCM) and logistics. A thorough review and bibliometric analysis were conducted to analytically and objectively unearth the knowledge development in IoT research within the context of SCM and logistics. The analysis started with the selection of 807 journal articles pub...
Chapter
The trade on illegal goods and services, also known as illicit trade, is expected to drain 4.2 trillion dollars from the world economy and put 5.4 million jobs at risk by 2022. These estimates reflect the importance of combating illicit trade, as it poses a danger to individuals and undermines governments. To do so, however, we have to first unders...
Chapter
The trade in illicit items, such as counterfeits, not only leads to the loss of large sums of private and public revenue, but also poses a danger to individuals, undermines governments, and—in the most extreme cases—finances criminal organizations. It is estimated that in 2013 trade in illicit items accounted for \(2.5\%\) of the global commerce. T...
Article
The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockp...
Article
The demand for object tracking (OT) applications has been increasing for the past few decades in many areas of interest: security, surveillance, intelligence gathering, and reconnaissance. Lately, newly-defined requirements for unmanned vehicles have enhanced the interest in OT. Advancements in machine learning, data analytics, and deep learning ha...
Article
Full-text available
The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockp...
Conference Paper
Full-text available
This paper details the development and features of the CNN-corpus in Spanish, possibly the largest test corpus for single document extractive text summarization in the Spanish language. Its current version encompasses 1,117 well-written texts in Spanish, each of them has an abstractive and an extractive summary. The development methodology adopted...
Conference Paper
This paper details the features and the methodology adopted in the construction of the CNN-corpus, a test corpus for single document extractive text summarization of news articles. The current version of the CNN-corpus encompasses 3,000 texts in English, and each of them has an abstractive and an extractive summary. The corpus allows quantitative a...
Conference Paper
Full-text available
The DocEng'19 Competition on Extractive Text Summarization assessed the performance of two new and fourteen previously published extractive text sumarization methods. The competitors were evaluated using the CNN-Corpus, the largest test set available today for single document extractive summarization.
Conference Paper
Full-text available
In this tutorial, we consider important aspects (algorithms, approaches, considerations) for tagging both unstructured and structured text for downstream use. This includes summarization, in which text information is compressed for more efficient archiving, searching, and clustering. In the tutorial, we focus on the topic of automatic text summariz...
Conference Paper
Full-text available
We present some results from a joint project between HP Labs, Cardiff University and Dyfed Powys Police on predictive policing. Applications of the various techniques from recommender systems and text mining to the problem of crime patterns recognition are demonstrated. Our main idea is to consider crime records for different regions and time perio...
Article
Automatic Text Summarization is the process of creating a compressed representation of one or more related documents, keeping only the most valuable information. The extractive approach for summarization is the most studied and aims to generate a compressed version of a document by identifying, ranking, and selecting the most relevant sentences or...
Chapter
The previous chapter reviewed a number of alternatives for hardcopy communications using printed images as hosts while addressing distortions caused by the printing and scanning processes. An important class of media that is closely related to hardcopy communication is that of text documents. While in natural images there is a rich grey scale or ev...
Chapter
The literature presents an extensive research on digital watermarking applications with digital image, speech, music and video media. However, much less research effort has been applied to hardcopy communication via printed media. Hardcopy images can be used to convey side information required for many security, tracking, copyright and forensic app...
Chapter
This chapter discusses one type of overt (visible) communication by employing color print codes aiming to convey information over printed media. In the literature many print codes have been proposed for conveying information, ranging from simple shapes like the PARC (Palo Alto Research Center Incorporated) dataglyphs, the popular linear-1D and 2D b...
Conference Paper
Full-text available
Outlier detection (OD) has been popularly developed in many fields such as medical diagnosis, network intrusion detection, fraud detection and military surveillance. This paper presents an accumulated relative density (ARD) OD method to identify outliers which possess relatively low or high local density. Previously, many density-based OD methods,...
Book
This book presents covert, semi-covert and overt techniques for communication over printed media by modifying images, texts or barcodes within the document. Basic and advanced techniques are discussed aimed to modulate information into images, texts and barcodes. Conveying information over printed media can be useful for content authentication, aut...
Article
Full-text available
The learning tools necessary to prepare the next generation of students must be shaped by the socio-economic needs of the 21st century. The needs of the 21st century – from rebuilding city scale physical infrastructure to personalized healthcare – not only require learning from the wealth of global information available on the Internet, but also th...
Article
Current methods for detecting bacterial infections, such as culture and morphological analysis of bacterial colonies, are time and labor intensive. Through the direct detection of bacterial volatile organic compounds (VOCs), via surface enhanced Raman spectroscopy (SERS), we report here a reconfigurable assay for the identification and monitoring o...
Conference Paper
In the world of ground truthing--that is, the collection of highly valuable labeled training and validation data-there is a tendency to follow the path of first training on a set of data, then validating the data, and then testing the data. However, in many cases the labeled training data is of non-uniform quality, and thus of non-uniform value for...
Conference Paper
Document engineering is all about building systems and tools that allow people to work with documents and document collections. A key aspect is the usefulness and usability of these tools. In this tutorial, we will look at the many different kinds of user studies and user evaluations that can be used to inform the design and improve utility and usa...
Conference Paper
For distance learning applications, inferring the cognitive states of students, particularly, their concentration and comprehension levels during instruction, is important to assess their learning efficacy. In this paper, we investigated the feasibility of using EEG recordings generated from an off-the-shelf, wearable device to automatically classi...
Article
Paraphrase identification consists in the process of verifying if two sentences are semantically equivalent or not. It is applied in many natural language tasks, such as text summarization, information retrieval, text categorization, and machine translation. In general, methods for assessing paraphrase identification perform three steps. First, the...
Chapter
Inkjet printing is, on the surface, a relatively mature area of engineering. Ink can be jetted continuously, with ink flowing directly through a microscopic nozzle and the target determined by charging the inks during their passage through the printing mechanism and directing with an electrostatic mechanism, usually at the output of the nozzle. Con...
Chapter
Data handling in inkjet printing is primarily dictated by the x- and y-directional resolutions, the printing speed (in area/s, not cm/s), and the quality of the imaging performed. Image data captured by the modules is processed by the press controller in real time. Additionally, an automatic printhead service station performs wiping and other funct...
Chapter
Keyword and feature extraction is a fundamental problem in text data mining and document processing. A majority of document processing applications directly depend on the quality and speed of keyword extraction algorithms. In this article, an approach, introduced in [1], to rapid change detection in data streams and documents is developed and analy...
Preprint
Through the direct detection of bacterial volatile organic compounds (VOCs), via surface enhanced Raman spectroscopy (SERS), we report here a reconfigurable assay for the identification and monitoring of bacteria. We demonstrate differentiation between highly clinically relevant organisms: Escherichia coli , Enterobacter cloacae , and Serratia marc...
Conference Paper
Wearable digital self-tracking technologies for monitoring individuals' health condition have become more accessible to the public in recent years with the development of connected portable devices, such as smart phones, smart watches, smart bands, and other personal biometric monitoring devices. Mining behavioural patterns from such wearable data...
Conference Paper
Automatic single-document summarization is a process that receives a single input document and outputs a condensed version with only the most relevant information. This paper proposes an unsupervised concept-based approach for singledocument summarization using Integer Linear Programming (ILP). Such an approach maximizes the coverage of the importa...
Conference Paper
Mobile devices such as smart phones and tablets are omnipresent in modern societies. Such devices allow browsing the Internet. This paper briefly describes two tools for news article summarization in mobile devices that attempts to automatically collect and sieve the most important information of news article in WebPages.
Conference Paper
The existing automatic text summarization systems whenever applied to web-pages of news articles show poor performance as the text is encapsulated within a HTML page. This paper takes advantage of the link identification and content extraction techniques. The results show the validity of such a strategy.
Conference Paper
This paper presents a new method for improving the cohesiveness of summaries generated by extractive summarization systems. The solution presented attempts to improve the legibility and cohesion of the generated summaries through coreference resolution. It is based on a post-processing step that binds dangling coreference to the most important enti...
Conference Paper
Analytics obtained during the creation of a database of mass serialized codes can also be used to help enforcement of encryption policy on documents. In this paper, we introduce a set of metrics which complement traditional NIST cryptography methods -- 4 mass serialization and one entropy metric -- which in combination can allow a discrimination be...
Conference Paper
Some of the recent state-of-the-art systems for Automatic Text Summarization rely on the concept-based approach using Integer Linear Programming (ILP), mainly for multi-document summarization. A study on the suitability of such an approach to single-document summarization is still missing, however. This work presents an assessment of several method...
Conference Paper
Today, students are offered a wide variety of alternatives to printed material for the consumption of educational content. Previous research suggests that, while digital content has its advantages, printed content still offers benefits that cannot be matched by digital media. This paper introduces the Meaningful Education and Training Information S...
Article
The volume of text data has been growing exponentially in the last years, mainly due to the Internet. Automatic Text Summarization has emerged as an alternative to help users find relevant information in the content of one or more documents. This paper presents a comparative analysis of eighteen shallow sentence scoring techniques to compute the im...
Article
TF*IDF (term frequency times inverse document frequency) is a common metric used to automatically discover keywords in documents for use in classification and other text processing applications. We are interested in determining whether these measures can help in determining the most relevant sentences for summarization and classification purposes....
Chapter
Keyword and feature extraction is a fundamental problem in data mining and document processing. A majority of applications directly depend on the quality and speed of keyword and feature extraction pre-processing results. In the current paper we present novel algorithms for feature extraction and change detection in unstructured data, primarily in...