ppxscal/embedding_network huggingface dataset:
A systematic design approach for low-power 10-bit 100MS/s pipelined ADC
Authors: D. Meganathan, Amrith Sukumaran, M. M. Dinesh Babu, S. Moorthi, R. Deepalakshmi
Venue: Microelectronics Journal (2009)

A systematic design approach for low-power 10-bit, 100MS/s pipelined analog-to-digital converter (ADC) is presented. At architectural level various per-stage-resolution are analyzed and most suitable architecture is selected for designing 10-bit, 100MS/s pipeline ADC. At Circuit level a modified wide-bandwidth and high-gain two-stage operational transconductance amplifier (OTA) proposed in this work is used in track-and-hold amplifier (THA) and multiplying digital-to-analog converter (MDAC) sections, to reduce power consumption and thermal noise contribution by the ADC. The signal swing of the analog functional blocks (THA and MDAC sections) is allowed to exceed the supply voltage (1.8V), which further increases the dynamic range of the circuit. Charge-sharing comparator is proposed in this work, which reduces the dynamic power dissipation and kickback noise of the comparator circuit. The bootstrap technique and bottom plate sampling technique is employed in THA and MDAC sections to reduce the nonlinearity error associated with the input signal resulting in a signal-to-noise-distortion ratio of 58.72/57.57dB at 2MHz/Nyquist frequency, respectively. The maximum differential nonlinearity (DNL) is +0.6167/-0.3151LSB and the maximum integral nonlinearity (INL) is +0.4271/-0.4712LSB. The dynamic range of the ADC is 58.72dB for full-scale input signal at 2MHz input frequency. The ADC consumes 52.6mW at 100MS/s sampling rate. The circuit is implemented using UMC-180nm digital CMOS technology.
Discovering global patterns in linguistic networks through spectral analysis: a case study of the consonant inventories
Authors: Animesh Mukherjee, Monojit Choudhury, Ravi Kannan
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

Recent research has shown that language and the socio-cognitive phenomena associated with it can be aptly modeled and visualized through networks of linguistic entities. However, most of the existing works on linguistic networks focus only on the local properties of the networks. This study is an attempt to analyze the structure of languages via a purely structural technique, namely spectral analysis, which is ideally suited for discovering the global correlations in a network. Application of this technique to PhoNet, the co-occurrence network of consonants, not only reveals several natural linguistic principles governing the structure of the consonant inventories, but is also able to quantify their relative importance. We believe that this powerful technique can be successfully applied, in general, to study the structure of natural languages.
Designing and assessing modeling and visualization technologies (MVT) enhanced learning
Authors: BaoHui Zhang, Michael J. Jacobson, Beaumie Kim, Feng Deng, Suneeta Pathak, Hans G. Lossman, Xiuqin Lin, Pratim Sengupta, Uri Wilensky, Kenneth E. Hay
Venue: Proceedings of the 8th international conference on International conference for the learning sciences - Volume 3 (2008)

Models are the core of scientific theory. Some researchers have argued that modeling is fundamental to scientific inquiry (e.g. Clement, 2000). There has been increased literature on how to use inquiry and modeling for science learning. However, challenges still exist. For example, how do different modeling tools and learning activities shape student learning trajectories? How do they impact student science learning? What are the assessment measures that can serve as formative and/or summative purposes in the different learning environments? This symposium introduces how computer-based MVT (i.e., NetLogo, Biologica, and Astronomicon) were integrated into different learning environments, and highlights how alternative and formative assessment measures have been used for assessing student learning progression and outcomes. The symposium concludes with some general principles for designing MVT enhanced learning environments and understanding of models and modelling as assessment toolkits to gain an insight into student conceptual development.
Reducing concurrent analysis under a context bound to sequential analysis
Authors: Akash Lal, Thomas Reps
Venue: Formal Methods in System Design (2009)

This paper addresses the analysis of concurrent programs with shared memory. Such an analysis is undecidable in the presence of multiple procedures. One approach used in recent work obtains decidability by providing only a partial guarantee of correctness: the approach bounds the number of context switches allowed in the concurrent program, and aims to prove safety, or find bugs, under the given bound. In this paper, we show how to obtain simple and efficient algorithms for the analysis of concurrent programs with a context bound. We give a general reduction from a concurrent program P, and a given context bound K, to a sequential program P s K such that the analysis of P s K can be used to prove properties about P. The reduction introduces symbolic constants and assume statements in P s K . Thus, any sequential analysis that can deal with these two additions can be extended to handle concurrent programs as well, under a context bound. We give instances of the reduction for common program models used in model checking, such as Boolean programs, pushdown systems (PDSs), and symbolic PDSs.
Empirical Analysis of Beijing Logistics Industry's GDP Contribution to the National Economy
Authors: Sun Yong Bo
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

This article based on Beijing Statistical yearbook and the information announced by Beijing Statistical bureau official website has selected data of gross national product and the total cargo turnover during the period of 11 years from 1996 to 2006 in Beijing area and analyzed logistics industry's GDP contribution to the national economy in Beijing.
An Algebra for Kripke Polynomial Coalgebras
Authors: Marcello Bonsangue, Jan Rutten, Alexandra Silva
Venue: Proceedings of the 2009 24th Annual IEEE Symposium on Logic In Computer Science (2009)

Several dynamical systems, such as deterministic automata and labelled transition systems, can be described as coalgebras of so-called Kripke polynomial functors, built up from constants and identities, using product, coproduct and powerset. Locally finite Kripke polynomial coalgebras can be characterized up to bisimulation by a specification language that generalizes Kleene’s regular expressions for finite automata. In this paper, we equip this specification language with an axiomatization and prove it sound and complete with respect to bisimulation, using a purely coalgebraic argument. We demonstrate the usefulness of our framework by providing a finite equational system for (non-)deterministic finite automata, la-belled transition systems with explicit termination, and automata on guarded strings.
Mining very long sequences in large databases with PLWAPLong
Authors: C. I. Ezeife, Kashif Saeed, Dan Zhang
Venue: Proceedings of the 2009 International Database Engineering & Applications Symposium (2009)

Position Coded Pre-order Linked Web Access Pattern (PLWAP) mining algorithm is one of the existing efficient web sequential pattern mining algorithms, which stores the frequent sequences of the entire sequential database in a compressed tree form with position coded nodes. However, for very long sequences exceeding thirty two nodes, the number of bits an integer position code can hold, the PLWAP algorithm's performance begins to degrade because it employs linked lists to store conjunctions of long position codes and the linked list traversals slow down the algorithm both during tree construction and mining. PLWAP algorithm also uses each and every node in the frequent 1-item event queue to test for that event inclusion in the suffix tree root set during mining. This paper proposes (1) using a different position code numbering scheme where each node is assigned two numeric codes (startPosition, endPosition) instead of one, (2) using pre-knowledge of "Last Descendant" of each tree branch to lower the cost of creating the suffix tree root sets during mining. Experiments show that the proposed new scheme, the PLWAPLong outperforms the PLWAP for long sequences and large databases as well as regular databases.
Object Tag Architecture for Innovative Intelligent Transportation Systems
Authors: Krishan Sabaragamu Koralalage, Noriaki Yoshiura
Venue: Proceedings of the 13th East European Conference on Advances in Databases and Information Systems (2009)

Safety is the paramount reason for Intelligent Transportation Systems (ITS). There are three main actors in ITS system: users, vehicles and infrastructure. Though the communications among those three actors are very vital, there is no common platform to make extensive communication among those three actors yet. That is one of the main reasons to occur fatalities. Therefore we consider the Radio Frequency (RF) identification as a candidate technology and develop a novel tag architecture called OTag (Object Tag) to enable the communication among them including vehicle to vehicle. In this paper we explain the OTag architecture and its protocol which enables a common communication platform. Furthermore, access control mechanisms, ability to be interoperable, stand-alone, self-describing, and plug and play usage are also described. Thus, how OTag architecture will advance the existing ITSs and create novel applications to support safe, secure, comfortable and productive social life in eco-friendly manner are concentrated.
Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Venue: ACL Workshops (2005)

The ACL 2005 Workshop on Feature Engineering for Machine Learning in Natural Language Processing is an opportunity to explore the various dimensions of feature engineering for problems that are of interest to the ACL community. Feature Engineering encompasses feature design, feature selection, feature induction, studies of feature impact (including feature ablation studies), and related topics. In 2003, there was a NIPS workshop on feature engineering ("Feature Extraction and Feature Selection"), but the focus was not on NLP problems specifically. Also, although the various aspects of feature engineering have been dealt with at times in various ACL forums, until now, to our knowledge, the spotlight has never been shone directly on this topic specifically for NLP and language technology problems. We feel that now is the time to look more closely. As experience with machine learning for solving natural language processing tasks accumulates in the field, practitioners are finding that feature engineering is as critical as the choice of machine learning algorithm, if not more so. Feature engineering significantly affects the performance of systems and deserves greater attention. Also, in the wake of the shift in our field away from knowledge engineering and of the successes of data-driven and statistical methods, researchers are likely to make further progress by incorporating additional, sometimes familiar, sources of knowledge as features. Feature design may benefit from expert insight even where the relative merits of features must be assessed through empirical techniques from data. Although some experience in the area of feature engineering is to be found in the theoretical machine learning community, the particular demands of natural language processing leave much to be discovered. In the call for papers, we expressed our intent of bringing together practitioners of NLP, machine learning, information extraction, speech processing, and related fields with the goal of sharing experimental evidence for successful approaches to feature engineering. Judging by the quality and diversity of the submissions received, we believe we have succeeded, and the resulting program should be of great interest to many researchers in the ACL community. We hope that the workshop will contribute to the distillation of best practices and to the discovery of new sources of knowledge and features previously untapped.
Opinion Target Network: A Two-Layer Directed Graph for Opinion Target Extraction
Authors: Yunqing Xia, Boyi Hao
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

Unknown opinion targets lead to a low coverage in opinion mining. To deal with this, the previous opinion target extraction methods consider human-compiled opinion targets as seeds and adopt syntactic/statistic patterns to extract new opinion targets. Three problems are notable. 1) Manually compiled opinion targets are too large to be sound seeds. 2) Array that maintains seeds is less effective to represent relations between seeds. 3) Opinion target extraction can hardly achieve a satisfactory performance in merely one cycle. The opinion target network (OTN) is proposed in this paper to organize atom opinion targets of component and attribute in a two-layer directed graph. With multiple cycles of OTN construction, a higher coverage of opinion target extraction is achieved via generalization and propagation. Experiments on Chinese opinion target extraction show that the OTN is promising in handling the unknown opinion targets.
Boundedness vs. Unboundedness of Lock Chains: Characterizing Decidability of Pairwise CFL-Reachability for Threads Communicating via Locks
Authors: Vineet Kahlon
Venue: Proceedings of the 2009 24th Annual IEEE Symposium on Logic In Computer Science (2009)

The problem of Pairwise CFL-reachability is to decide whether two given program locations in different threads are simultaneously reachable in the presence of recursion in threads and scheduling constraints imposed by synchronization primitives. Pairwise CFL-reachability is the core problem underlying concurrent program analysis especially dataflow analysis. Unfortunately, it is undecidable even for the most commonly used synchronization primitive, i.e., mutex locks. Lock usage in concurrent programs can be characterized in terms of lock chains, where a sequence of mutex locks is said to be chained if the scopes of adjacent (nonnested) mutexes overlap. Although pairwise reachability is known to decidable for threads interacting via nested locks, i.e., chains of length one, these techniques don’t extend to programs with non-nested locks used in crucial applications like databases and device drivers. In this paper, we exploit the fact that lock usage patterns in real life programs do not produce unbounded lock chains. For such programs, we show that pairwise CFL-reachability becomes decidable. Our new results narrow the decidability gap for pairwise CFL-reachability by providing a more refined characterization for it in terms of boundedness of lock chains rather than the current state-of-the-art, i.e., nestedness of locks (chains of length one).
On an Online Traveling Repairman Problem with Flowtimes: Worst-Case and Average-Case Analysis
Authors: Axel Simroth, Alexander Souza
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

We consider an online problem where a server operates on an edge-weighted graph G and an adversarial sequence of requests to vertices is released over time. Each request requires one unit of servicetime. The server is free to choose the ordering of service and intends to minimize the total flowtime of the requests.A natural class of algorithms for this problem are Ignore algorithms. From worst-case perspective we show that Ignore algorithms are not competitive for flowtime minimization. From an average-case point of view, we obtain a more detailed picture. In our model, the adversary may still choose the vertices of the requests arbitrarily. But the arrival times are according to a stochastic process (with some rate ¿> 0), chosen by the adversary out of a natural class of processes. The class contains the Poisson-process and (some) deterministic arrivals as special cases. We then show that there is an Ignore algorithm that is competitive if and only if $\lambda \not = 1$. Specifically, for $\lambda \not = 1$, the expected competitive ratio of the algorithm is within a constant of the length of a shortest cycle that visits all vertices of G. The reason for this is that if $\lambda \not = 1$ the requests either arrive slow enough for our algorithm or too fast even for an offline optimal algorithm. For ¿= 1 the routing-mistakes of the online algorithm accumulate just as in the worst case.As an additional result, we show how Ignore tours are constructed optimally in polynomial time, if the underlying graph G is a line.
Fusion of Multiple Expert Annotations and Overall Score Selection for Medical Image Diagnosis
Authors: Tomi Kauppi, Joni-Kristian Kamarainen, Lasse Lensu, Valentina Kalesnykiene, Iiris Sorri, Heikki Kälviäinen, Hannu Uusitalo, Juhani Pietilä
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Two problems especially important for supervised learning and classification in medical image processing are addressed in this study: i) how to fuse medical annotations collected from several medical experts and ii) how to form an image-wise overall score for accurate and reliable automatic diagnosis. Both of the problems are addressed by applying the same receiver operating characteristic (ROC) framework which is made to correspond to the medical practise. The first problem arises from the typical need to collect the medical ground truth from several experts to understand the underlying phenomenon and to increase robustness. However, it is currently unclear how these expert opinions (annotations) should be combined for classification methods. The second problem is due to the ultimate goal of any automatic diagnosis, a patient-based (image-wise) diagnosis, which consequently must be the ultimate evaluation criterion before transferring any methods into practise. Various image processing methods provide several, e.g., spatially distinct, results, which should be combined into a single image-wise score value. We discuss and investigate these two problems in detail, propose good strategies and report experimental results on a diabetic retinopathy database verifying our findings.
Video viewing preferences for HDR displays under varying ambient illumination
Authors: Allan G. Rempel, Wolfgang Heidrich, Hiroe Li, Rafał Mantiuk
Venue: Proceedings of the 6th Symposium on Applied Perception in Graphics and Visualization (2009)

Recent high dynamic range (HDR) display devices provide significantly greater output brightness and dynamic range compared to conventional display technology. A possible concern for the extended use of HDR displays is the potential to cause visual fatigue. Furthermore, ambient illumination has a significant effect on the perception of the imagery displayed, and its impact on user preferences for brightness and contrast must be understood. In our work we examine these issues by conducting two user studies. In each study, subjects watched video content on an HDR display in several different ambient illumination environments, and were asked to adjust the brightness and black level of the display to their preference. Subjects were also given questionnaires to document their observations and subjective preferences as well as any visual fatigue they may have experienced. We found that subjects experienced minimal visual fatigue, and also found statistically significant differences in preferred display settings under different ambient lighting conditions.
Property Preserving Refinement for Csp-Casl
Authors: Temesghen Kahsai, Markus Roggenbach
Venue: Recent Trends in Algebraic Development Techniques: 19th International Workshop, WADT 2008, Pisa, Italy, June 13-16, 2008, Revised Selected Papers (2009)

In this paper we present various notions of the combined refinement for data and processes within the specification language Csp-Casl. We develop proof support for our refinement notions and demonstrate how to employ them for system development and for system analysis. Finally, we apply our technique to an industrial standard for an electronic payment system.
Using machine learning to refine Category-Partition test specifications and test suites
Authors: Lionel C. Briand, Yvan Labiche, Zaheer Bawar, Nadia Traldi Spido
Venue: Information and Software Technology (2009)

In the context of open source development or software evolution, developers often face test suites which have been developed with no apparent rationale and which may need to be augmented or refined to ensure sufficient dependability, or even reduced to meet tight deadlines. We refer to this process as the re-engineering of test suites. It is important to provide both methodological and tool support to help people understand the limitations of test suites and their possible redundancies, so as to be able to refine them in a cost effective manner. To address this problem in the case of black-box, Category-Partition testing, we propose a methodology and a tool based on machine learning that has shown promising results on a case study involving students as testers.
WCAG 2.0 for Designers: Beyond Screen Readers and Captions
Authors: Loretta Guarino Reid, Andi Snow-Weaver
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

The W3C Web Content Accessibility Guidelines (WCAG) provide guidance on making websites accessible to people with disabilities. WCAG 1.0 focused largely on coding requirements that enable websites to interoperate with assistive technologies used by people with disabilities. WCAG 2.0 addresses an environment where website complexity has increased significantly due to higher network bandwidth and the introduction of new interactive technologies. It places more constraints on the default look and feel of a website. Of the 38 Level A and AA provisions, about 50%, impact the website design. This paper reviews those requirements, examining the user needs that they are intended to support and highlighting example strategies for addressing those needs.
Identifying Structures with Informative Dimensions in Streams
Authors: Vasudha Bhatnagar, Sharanjit Kaur, Neelima Gupta
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Discovering structures in streaming data is an important data mining task and has motivated design of several well known algorithms. However, in some applications, a higher level of analysis is desirable to reveal the set of dimensions which contribute heavily to the structures.In this paper, we propose an algorithm ISID (Identifying Structures with Informative Dimensions), which operates in the streaming environment and delivers clusteres along with dimensions that contribute significantly to these clusters. The algorithm uses a three stage approach andutilizes entropy in an innovative way to achieve the goal in four different ways, depending on the desired guarantees on structural richness or minimal dimension set for a cluster.The experimental results on synthetic and real data sets demonstrate the efficiency and effectiveness of the proposed algorithm.