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- How to Hide Secrets from Operating System: Architecture Level Support for Dynamic Address Trace Obfuscation
- This technical report addresses how to hide secrets from an operating system. Abstract: The adversary model for digital rights management is much more powerful than for the traditional security scenarios. The adversary has complete control of the computing node - supervisory privileges, physical as well as architectural object observational capabilities. In essence, this makes the operating system (or any other layer around the architecture) itself the adversary. The repercussions of this observation are severe. It creates a need to "keep secrets" from the operating system. We argue for the need to keep secrets from the OS in hardware. This concept is demonstrated through architectural support for the obfuscation of dynamic address traces on the memory bus. The objective is to leak as little information about the executed program sequence as possible. This is done by handing over many of the virtual memory management responsibilities from the operating system to an architecturally isolated hardware black-box (VM black-box). The authors provide a detailed design for the VM blackbox and some microarchitecture level simulation derived performance data. We also describe a compiler directed prefetch scheme that uses both instruction and data prefetches to obfuscate the address traces on the address bus between on-chip L2 cache and memory. digital.library.unt.edu/ark:/67531/metadc94282/
- SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text
- This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%. digital.library.unt.edu/ark:/67531/metadc30961/
- WARM SRAM: A Novel Scheme to Reduce Static Leakage Energy in SRAM Arrays
- This presentation accompanies a paper discussing research on a novel scheme to reduce static leakage energy in SRAM arrays. The increasing sub-threshold leakage current levels with newer technology nodes have been identified by ITRS (2001) as one of the major fundamental problems faced by the semiconductor industry. Concurrently, the expected performance improvement and functionality integration expectations drive the continued reduction in feature size. This results in ever-increasing power per unit area and the accompanying problem of heat removal and cooling as stated in J.M.C. Stork (1995). Portable battery-powered applications, fuelled by pervasive and embedded computing, have seen tremendous growth and have reached a point where battery energy and power density can't be increased further according to T. Bell (1991). This raises the computational throughput per watt target for the future technology nodes. SRAM arrays which are used widely as a system component, such as caches and register files, in both high-performance and portable systems, are getting to be dominant power consumers because of their large capacity and area. Hence any reduction in cache energy can result in considerable overall power reduction. The authors propose a novel circuit technique using depletion mode devices, to reduce the static energy of SRAM array in an on-chip by 90% without any performance impact. digital.library.unt.edu/ark:/67531/metadc96819/
- Co-training and Self-training for Word Sense Disambiguation
- This paper investigates the application of co-training and self-training to word sense disambiguation. Optimal and empirical parameter selection methods for co-training and self-training are investigated, with various degrees of error reduction. A new method that combines co-training with majority voting is introduced, with the effect of smoothing the bootstrapping learning curves, and improving the average performance. digital.library.unt.edu/ark:/67531/metadc30955/
- Finding Semantic Associations on Express Lane
- This paper introduces a new codification scheme for efficient computation of measures in semantic networks. The scheme is particularly useful for fast computation of semantic associations between words and implementation of an informational retrieval operator for efficient search in semantic spaces. Other applications may also be possible. digital.library.unt.edu/ark:/67531/metadc30956/
- Impact of Interference Model on Capacity in CDMA Cellular Networks
- This paper discusses an impact of interference model on capacity in CDMA cellular networks. Abstract: An overwhelming number of models in the literature use average interference for calculation of capacity of a CDMA network. In this paper, we calculate the actual per-user interference and analyze the effect of user-distribution on the capacity of a CDMA network. We show that even though the capacity obtained using average interference is a good approximation to the capacity calculated using actual interference for a uniform user distribution, the deviation can be tremendously large for non-uniform user distributions. digital.library.unt.edu/ark:/67531/metadc30817/
- Open Text Semantic Parsing Using FrameNet and WordNet
- This paper describes a rule-based semantic parser that relies on a frame dataset (FrameNet), and a semantic network (WordNet), to identify semantic relations between words in open text, as well as shadow semantic features associated with concepts in the text. Parsing semantic structures allows semantic units and constitutes to be accessed and processed in a more meaningful way than syntactic parsing, moving the automation of understanding natural language text to a higher level. digital.library.unt.edu/ark:/67531/metadc30959/
- An Evaluation Exercise for Romanian Word Sense Disambiguation
- This paper discusses an evaluation exercise for Romanian word sense disambiguation. Abstract: This paper presents the task definition, resources, participating systems, and comparative results for a Romanian Word Sense Disambiguation task, which was organized as part of the SENSEVAL-3 evaluation exercise. Five teams with a total of seven systems were drawn to this task. digital.library.unt.edu/ark:/67531/metadc30954/
- Global versus Local Call Admission Control in CDMA Cellular Networks
- This presentation discusses interference model impacts on capacity, global call admission controls, local call admission controls, and the differences in global versus local call admission controls. digital.library.unt.edu/ark:/67531/metadc30931/
- Global versus Local Call Admission Control in CDMA Cellular Networks
- This paper discusses global versus local call admission control. Abstract: We design and implement global and local CAC algorithms for CDMA networks, and compare their network throughput for various mobility scenarios. The global CAC algorithms is inherently optimized and uses global information in making every call admission decision; it yields the best possible performance but has an intensive computational complexity. The design of the local CAC algorithm uses global information but its implementation in each cell uses only local information; it only requires the number of calls currently active in that cell and thus is very simple to implement. We show that our optimized local CAC algorithm achieves almost the same performance as our global CAC algorithm for a given call arrival rate profile. digital.library.unt.edu/ark:/67531/metadc30816/
- Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization
- Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks. digital.library.unt.edu/ark:/67531/metadc30957/
- Impact of Interference Model on Capacity in CDMA Cellular Networks
- This presentation introduces code division multiple access (CDMA) networks, average and actual interference models, optimized capacity, and the 2D Gaussian user model. digital.library.unt.edu/ark:/67531/metadc30932/
- The SENSEVAL-3 English Lexical Sample Task
- This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise. The task drew the participation of 27 teams from around the world, with a total of 47 systems. digital.library.unt.edu/ark:/67531/metadc30963/
- The SENSEVAL-3 Multilingual English-Hindi Lexical Sample Task
- This paper describes the English-Hindi Multilingual lexical sample task in SENSEVAL-3. Rather than tagging an English word with a sense from an English dictionary, this task seeks to assign the most appropriate Hindi translation to an ambiguous target word. Training data was solicited via the Open Mind Word Expert (OMWE) from Web users who are fluent in English and Hindi. digital.library.unt.edu/ark:/67531/metadc30964/
- TextRank: Bringing Order into Texts
- In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications. In particular, the authors propose two innovative unsupervised methods for keyword and sentence extraction, and show that the results obtained compare favorably with previously published results on established benchmarks. digital.library.unt.edu/ark:/67531/metadc30962/
- An Algorithm for Open Text Semantic Parsing
- Abstract: This paper describes an algorithm for open text shallow semantic parsing. The algorithm relies on a frame dataset (FrameNet) and a semantic network (WordNet), to identify semantic relations between words in open text, as well as shallow semantic features associated with concepts in the text. Parsing semantic structures allows semantic units and constituents to be accessed and processed in a more meaningful way than syntactic parsing, moving the automation of understanding natural language text to a higher level. digital.library.unt.edu/ark:/67531/metadc30953/
- PageRank on Semantic Networks, with Application to Word Sense Disambiguation
- This paper presents a new open text word sense disambiguation method that combines the use of logical interferences with PageRank-style algorithms applied on graphs extracted from natural language documents. The authors evaluate the accuracy of the proposed algorithm on several sense-annotated texts, and show that it consistently out-performs the accuracy of other previously proposed knowledge-based word sense disambiguation methods. The authors also explore and evaluate methods that combine several open-text word sense disambiguation algorithms. digital.library.unt.edu/ark:/67531/metadc30960/
- Subscriber Maximization in CDMA Cellular Networks
- This presentation gives an overview of code division multiple access (CDMA), traffic and mobility models, subscriber optimization formulation, and numerical results. digital.library.unt.edu/ark:/67531/metadc30933/
- Subscriber Maximization in CDMA Cellular Networks
- This paper discusses subscriber maximization in CDMA cellular networks. The author calculates the maximum number of subscribers in a CDMA cellular network for a given GoS requirement, QoS requirement, network topology, and user distribution profile. The author formulates a constrained optimization problem that maximizes the call arrival rates subject to upper bounds on the blocking probabilities and lower bounds on the bit energy to interference ratios. This paper presents examples for traditional and optimized network topologies with uniform and non-uniform user distribution profiles and different mobility scenarios. digital.library.unt.edu/ark:/67531/metadc30818/
- A Logic Programming Framework for Semantic Interpretation with WordNet and PageRank
- This paper describes applications of Logic Programming to Natural Language processing in combination with graph-algorithms and statistical methods. Google's PageRank and similar fast-converging recursive graph algorithms have provided practical means to statistically rank vertices of large graphs like the World Wide Web. By combining a fast Java-based PageRank implementation with a Prolog base inferential layer, running on top of an optimized WordNet graph, the authors describe applications to word sense disambiguation and evaluate their accuracy in comparison with human annotated corpus data. digital.library.unt.edu/ark:/67531/metadc30952/
- Current Research in Wireless at UNT
- This presentation discusses wireless networks, access point selections, traffic balancing, multi-cell CDMA, user distribution modeling, and call admission control. digital.library.unt.edu/ark:/67531/metadc30930/
- Making Sense Out of the Web
- This paper discusses the main lines of research in deriving efficient Word Sense Disambiguation. In the past few years, we have witnessed a tremendous growth of the World Wide Web, both in terms of number of Web pages accessible online - resulting in what represents today the largest publicly available corpus, and in terms of number of Web users - who now these two main dimensions - pages and users - has opened the doors to a realm of new approaches to data-hungry and knowledge-hungry language processing applications. Among these, Word Sense Disambiguation is one of the applications that has the potential of benefiting the most from the large amounts of Web-based data and from the availability of inexpensive Web user supervision. In this paper, the author discusses the main lines of research in deriving efficient Word Sense Disambiguation methods that exploit: (1) the Web as a corpus - which represents a view of the Web seen as an enormous collection of Web pages; and (2) the Web as collective mind - where the Web is regarded as a large group of Web users who can contribute their knowledge to the process of identifying word meanings. digital.library.unt.edu/ark:/67531/metadc30958/
- Putting Pieces Together: Combining FrameNet, VerbNet and WordNet for Robust Semantic Parsing
- This paper describes the authors' work in integrating three different lexical resources: FrameNet, VerbNet, and WordNet, into a unified, richer knowledge-base, to the end of enabling more robust semantic parsing. The construction of each of these lexical resources has required many years of laborious human effort, and they all have their strengths and shortcomings. By linking them together, the authors build an improved resource in which (1) the coverage of FrameNet is extended, (2) the VerbNet lexicon is augmented with frame semantics, and (3) selectional restrictions are implemented using WordNet semantic classes. The synergistic exploitation of various lexical resources is crucial for many complex language processing applications, and the authors prove it once again effective in building a robust semantic parser. digital.library.unt.edu/ark:/67531/metadc30973/
- Effects of Interference on Capacity in Multi-Cell CDMA Networks
- This article discusses the effects of interference on capacity in multi-cell CDMA networks. Abstract: An overwhelming number of models in the literature use average interference for calculation of capacity of a CDMA network. In this paper, we calculate the actual per-user interference and analyze the effect of user-distribution on the capacity of a CDMA network. We show that even though the capacity obtained using average interference is a good approximation to the capacity calculated using actual interference for a uniform user distributions, the deviation can be tremendously large for non-uniform user distributions. We also present an analytical model for approximating the user distributions using 2-dimensional Gaussian distributions by determining the means and the standard deviations of the distributions for every cell. This allows us to calculate the inter-cell interference and the reverse-link capacity of the network. We compare their model with simulation results and show that it is fast and accurate enough to be used efficiently in the planning process of large CDMA networks. digital.library.unt.edu/ark:/67531/metadc30826/
- Mobility-Based CAC Algorithm for Arbitrary Call-Arrival Rates in CDMA Cellular Systems
- This paper presents a novel approach for designing a call-admission control (CAC) algorithm for code-division multiple-access (CDMA) networks with arbitrary call-arrival rates. The design of the CAC algorithm uses global information; it incorporates the call-arrival rates and the user mobilities across the network and guarantees the users' quality of service (QoS) as well as prescribed blocking probabilities. On the other hand, its implementation in each cell uses local information; it only requires the number of calls currently active in that cell. The authors present several cases for a nontrivial network topology where their CAC algorithm guarantees QoS and blocking probabilities while achieving significantly higher throughput than that achieved by traditional techniques. The authors also calculate the network capacity, i.e., the maximum throughput for the entire network, for prespecified blocking probabilities and QoS requirements. digital.library.unt.edu/ark:/67531/metadc30821/
- PicNet: Augmenting Semantic Resources with Pictorial Representations
- In this paper, the authors introduce PicNet, a Web-based system for augmenting semantic resources with illustrative images using volunteer contributions over the Web. PicNet seeks to build rich knowledge-bases that encode word/image associations, to the end of combining the advantages and power of both visual and linguistic representations as means of defining world concepts. In this paper, the authors address some of the issues encountered in identifying prototypical illustrations for various concepts, as well as issues related to the construction of such pictorial knowledge-bases with the help of Web users. digital.library.unt.edu/ark:/67531/metadc30972/
- Semantic Document Engineering with WordNet and PageRank
- This paper describes natural language processing techniques for document engineering in combination with graph algorithms and statistical methods. Google's PageRank and similar fast-converging recursive graph algorithms have provided practical means to statistically rank vertices of large graphs like the World Wide Web. By combining a fast Java-based PageRank implementation with a Prolog base inferential layer, running on top of an optimized WordNet graph, the authors describe applications to word sense disambiguation and evaluate their accuracy on standard benchmarks. digital.library.unt.edu/ark:/67531/metadc30974/
- Throughput Optimization in Multi-Cell CDMA Networks
- In this paper, the authors investigate the performance of a multi-cell CDMA network by determining the maximum throughput that the network can archive for a given grade-of-service requirement, quality-of-service requirement, network topology and call arrival rate profile. The analysis is restricted to the reverse link and accounts for mobility of users between cell. A constrained nonlinear optimization problem is formulated that maximizes the network throughput subject to upper bounds on the blocking probabilities and a lower bound on the bit energy to interference ratio. The goal is to optimize the usage of network resources, provide consistent grade-of-service for all the cells in the network, and maintain a pre-specified quality-of-service. The solution to the optimization problem yields the maximum network throughput as well as the maximum number of calls that should be admitted in each cell for a given topology and call arrival rate profile. Our optimization algorithm yields significantly higher throughput compared with traditional call admission schemes. digital.library.unt.edu/ark:/67531/metadc30823/
- WiFi and WCDMA Network Design
- This presentation discusses WiFi access point selection and traffic balancing, multi-cell wideband code division multiple access (WCDMA) with multiple classes, user modeling using 2D Gaussian distribution, and intra-cell and inter-cell interference and capacity. digital.library.unt.edu/ark:/67531/metadc30935/
- Multi-Document Summarization with Iterative Graph-based Algorithms
- In this paper, the authors show how a meta-summarizer relying on a layered application of graph-based techniques for single-document summarization can be turned into an effective method for multi-document summarization. Through evaluations performed on standard data sets, the authors show that this method compares favorably with state-of-the-art techniques for multi-document summarization. digital.library.unt.edu/ark:/67531/metadc30970/
- Measuring the Semantic Similarity of Texts
- This paper presents a knowledge-based method for measuring the semantic-similarity of texts. While there is a large body of previous work focused on finding the semantic similarity of concepts and words, the application of these word-oriented methods to text similarity has not been yet explored. In this paper, the authors introduce a method that combines word-to-word similarity metrics into a text-to-text metric, and the authors show that this method outperforms the traditional text similarity metrics based on lexical matching. digital.library.unt.edu/ark:/67531/metadc30969/
- SenseLearner: Word Sense Disambiguation for All Words in Unrestricted Text
- This article describes SenseLearner, a minimally supervised word sense disambiguation system that attempts to disambiguate all content words in a text using WordNet senses. The authors evaluate the accuracy of SenseLearner on several standard sense-annotated data sets, and show that it compares favorably with the best results reported during the recent SENSEVAL evaluations. digital.library.unt.edu/ark:/67531/metadc30975/
- Word Alignment for Languages with Scarce Resources
- This paper presents the task definition, resources, participating systems, and comparative results for the shared task on word alignment which was organized as part of the Association for Computational Linguistics (ACL) 2005 Workshop on Building and Using Parallel Texts. The shared task included English-Inuktitut, Romanian-English, and English-Hindi sub-tasks, and drew the participation of ten teams from around the world with a total of 50 systems. digital.library.unt.edu/ark:/67531/metadc30979/
- Approximating User Distributions in WCDMA Networks Using 2-D Gaussian
- This paper discusses approximating user distributions in WCDMA networks using 2-D Gaussian. Abstract: In this paper, we present an analytical model for approximating the user distributions in multi-cell third generation WCDMA networks using 2-dimensional Gaussian distributions by determining the means and the standard deviations of the distributions for every cell. This allows us to calculate the inter-cell interference and the reverse-link capacity of the network. The authors compare their model with simulation results and show that it is fast and accurate enough to be used efficiently in the planning process of large WCDMA networks. digital.library.unt.edu/ark:/67531/metadc30820/
- Computational Laughing: Automatic Recognition of Humorous One-liners
- This paper discusses automatic recognition of humor. Abstract: Humor is one of the most interesting and puzzling aspects of human behavior. Despite the attention it has received in fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humor recognition or generation. In this paper, the authors bring empirical evidence that computational approaches can be successfully applied to the task of humor recognition. Through experiments performed on very large data sets, the authors show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, with significant improvements observed over apriori known baselines. digital.library.unt.edu/ark:/67531/metadc30966/
- Language Independent Extractive Summarization
- This paper discusses language independent extractive summarization. Abstract: We demonstrate TextRank - a system for unsupervised extractive summarization that relies on the application of iterative graph-based ranking algorithms to graphs encoding the cohesive structure of a text. An important characteristic of the system is that it does not rely on any language-specific knowledge resources or any manually constructed training data, and thus it is highly portable to new languages or domains. digital.library.unt.edu/ark:/67531/metadc30967/
- Optimal Access Point Selection and Traffic Allocation in IEEE 802.11 Networks
- This paper discusses optimal access point selection and the traffic allocation in IEEE 802.11 networks. The authors design an optimal access point (AP) selection and traffic allocation algorithm for IEEE 802.11 networks. Coverage and capacity are some key issues when selecting APs in a demand area. APs need to cover all users, i.e., a user is considered covered if the power received from its corresponding AP is greater than a given threshold. Moreover, from a capacity standpoint, APs need to provide certain bandwidth to users located in the coverage area. Our optimization balances the load on the entire network whereby demand clusters will not necessarily select the closest AP that has the largest signal level but one that can still service the demand cluster and provide ample bandwidth. digital.library.unt.edu/ark:/67531/metadc30822/
- An Efficient Non-Preemptive Real-Time Scheduling
- This paper discusses non-preemptive, real-time scheduling. Abstract: Traditional real-time systems are designed using preemptive scheduling and worst-case execution time estimates to guarantee the execution of high priority tasks. There is, however, an interest in exploring non-preemptive scheduling models for real-time systems, particularly for soft real-time multimedia applications. In this paper, we propose a new algorithm that uses multiple scheduling strategies. The goal of this research is to improve the success rate of the well-known Earliest Deadline First (EDF) approach even when the load on the system is very high. The approach, known as group-EDF (gEDF) is based on (dynamic) grouping of tasks with deadlines that are very close to each other, and using Shortest Job First (SJF) technique to schedule tasks within the group. We present results comparing gEDF and EDF using randomly generated tasks with varying execution times, release times, deadlines and tolerance to missing deadlines, under varying workloads. We believe that the grouping of tasks with similar deadlines and utilizing information other than deadlines (such as execution times, priorities or resource availability) for scheduling tasks within a group can lead to new and more efficient real-time scheduling algorithms. digital.library.unt.edu/ark:/67531/metadc30819/
- Parallel Texts
- This article discusses parallel texts. Parallel texts have become a vital element for natural language processing. The authors present a panorama of current research activities related to parallel texts, and offer some thoughts about the future of this rich field of investigation. digital.library.unt.edu/ark:/67531/metadc30971/
- Text Semantic Similarity, with Applications
- In this paper, the authors present a knowledge-based method for measuring the semantic-similarity of texts. Through experiments performed on two different applications: (1) paraphrase and entailment identification, and (2) word sense similarity, the authors show that this method outperforms the traditional text similarity metrics based on lexical matching. digital.library.unt.edu/ark:/67531/metadc30976/
- Using the Essence of Texts to Improve Document Classification
- This paper explores the possible benefits of the interaction between automatic extractive summarization and text classification. Through experiments performed on standard test collections, the authors show that techniques for extractive summarization can be effectively combined with classification methods, resulting in improved performance in a text categorization task. Moreover, comparative results suggest that the synergy between text summarization and text classification can be regarded as a new application-oriented evaluation testbed for automatic summarization. digital.library.unt.edu/ark:/67531/metadc30978/
- A Language Independent Algorithm for Single and Multiple Document Summarization
- This paper discusses a language independent algorithm for single and multiple document summarization. Abstract: This paper describes a method for language independent extractive summarization that relies on iterative graph-based ranking algorithms. Through evaluations performed on a single document summarization task for English and Portuguese, we show that the method performs equally well regardless of the language. Moreover, we show how a meta-summarizer relying on a layered application of techniques for single-document summarization can be turned into an effective method for multi-document summarization. digital.library.unt.edu/ark:/67531/metadc30965/
- Making Computers Laugh: Investigations in Automatic Humor Recognition
- This paper discusses investigations in automatic humor recognition. This Humor is one of the most interesting and puzzling aspects of human behavior. Despite the attention it has received in fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humor recognition or generation. In this paper, the authors bring empirical evidence that computational approaches can be successfully applied to the task of humor recognition. Through experiments performed on very large data sets, the authors show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, with significant improvements observed over apriori known baselines. digital.library.unt.edu/ark:/67531/metadc30968/
- Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling
- This paper introduces a graph-based algorithm for sequence data labeling, using random walks on graphs encoding label dependencies. The algorithm is illustrated and tested in the context of an unsupervised word sense disambiguation problem, and shown to significantly outperform the accuracy achieved through individual label assignment, as measured on standard sense-annotated data sets. digital.library.unt.edu/ark:/67531/metadc30977/
- Research, Teaching, and Outreach
- This presentation discusses research in sensor network routing, WiFi network optimization, 3G cellular call admission, and the outreach and resources needed. digital.library.unt.edu/ark:/67531/metadc30934/
- Capacity Allocations in Multi-cell UMTS Networks for Different Spreading Factors with Perfect and Imperfect Power Control
- This presentation discusses user and interference models, wideband code division multiple access (WCDMA) capacity with perfect and imperfect power control, and spreading factors with numerical results. digital.library.unt.edu/ark:/67531/metadc30937/
- Capacity Allocations in Multi-cell UMTS Networks for Different Spreading Factors with Perfect and Imperfect Power Control
- This paper discusses capacity allocation in multi-cell UMTS networks. Abstract: An analytical model for calculating capacity in multi-cell UMTS networks is presented. Capacity is maximized for different spreading factors and for perfect and imperfect power control. An analytical model is presented for approximating the user distributions in multi-cell third generation WCDMA networks using 2-dimensional Gaussian distributions by determining the means and the standard deviations of the distribution for every cell. This allows for the calculation of the inter-cell interference and the reverse-link capacity of the network. The capacity was determined for signal-to-interference threshold from 5 dB to 10 dB and spreading factor values of 256, 64, 16, and 4. digital.library.unt.edu/ark:/67531/metadc30825/
- Secure execution environments through reconfigurable lightweight cryptographic components
- This doctoral dissertation discusses secure execution environments through reconfigurable lightweight cryptographic components. Software protection is one of the most important problems in the area of computing as it affects a multitude of players like software vendors, digital content providers, users, and government agencies. There are multiple dimensions to this broad problem of software protection. The most important ones are: 1) protecting software from reverse engineering. 2) protecting software from tamper (or modification). 3) preventing software piracy. 4) verification of integrity of the software. In this thesis the authors focus on these areas of software protection. The basic requirement to achieve these goals is to provide a secure execution environment, which ensures that the programs behave in the same way as it was designed, and the execution platforms respect certain types of wishes specified by the program. The authors take the approach of providing secure execution environment through architecture support. The authors exploit the power of reconfigurable components in achieving this. The first problem the authors consider is to provide architecture support for obfuscation. This also achieves the goals of tamper resistance, copy protection, and IP protection indirectly. The authors' approach is based on the intuition that the software is a sequence of instructions (and data) and if the sequence as well the contents are obfuscated then all the required goals can be achieved. The second problem the authors solve is integrity verification of the software particularly in embedded devices. The authors' solution is based on the intuition that an obfuscated (permuted) binary image without any dynamic traces reveals very little information about the IP of the program. Moreover, if this obfuscation function becomes a shared secret between the verifier and the embedded device then verification can be performed in a trustworthy manner. Cryptographic components form the underlying building blocks/primitives of any secure execution environment. The authors use of reconfigurable components to provide software protection in both Arc3D and TIVA led us to an interesting observation about the power of reconfigurable components. Reconfigurable components provide the ability to use the secret (or key) in a much stronger way than the convention cryptographic designs. This opened up an opportunity for us to explore the use of reconfigurable gates to build cryptographic functions. digital.library.unt.edu/ark:/67531/metadc96840/
- Technologies That Make You Smile: Adding Humor to Text-Based Applications
- In this article, the authors explore computational approaches' applicability to the recognition and use of verbally expressed humor. Particularly, the authors focus on three important research questions related to this problem: Can we automatically gather large collections of humorous texts? Can we automatically recognize humor in text? And can we automatically insert humorous add-ons into existing applications? digital.library.unt.edu/ark:/67531/metadc30985/
- Creating a Testbed for the Evaluation of Automatically Generated Back-of-the-book Indexes
- This paper discusses automatic generating of back-of-the-book indexes. Abstract: The automatic generation of back-of-the-book indexes seems to be out of sight of the Information Retrieval and Natural Language Processing communities, although the increasingly large number of books available in electronic format, as well as recent advances in key-phrase extraction, should motivate an increased interest in this topic. In this paper, the authors describe the background relevant to the process of creating back-of-the-book indexes, namely (1) a short overview of the origin and structure of back-of-the-book indexes, and (2) the correspondence that can be established between techniques for automatic index construction and keyphrase extraction. Since the development of any automatic system requires in the first place an evaluation testbed, the authors describe their work in building a gold standard collection of books and indexes, and the authors present several metrics that can be used for the evaluation of automatically generated indexes against the gold standard. Finally, the authors investigate the properties of the gold standard index, such as index size, length of index entries, and upper bounds on coverage as indicated by the presence of index entries in the document. digital.library.unt.edu/ark:/67531/metadc30982/