ppxscal/embedding_network huggingface dataset:
Annealing effect on physical and electrical characteristics of thin HfO2, HfSixOy and HfOyNz films on Si
Authors: Joo-Hyung Kim, Velislava A. Ignatova, Martin Weisheit
Venue: Microelectronic Engineering (2009)

We report the effect of annealing on electrical and physical characteristics of HfO"2, HfSi"xO"y and HfO"yN"z gate oxide films on Si. Having the largest thickness change of 0.3nm after post deposition annealing (PDA), HfO"yN"z shows the lowest leakage current. It was found for both as-grown and annealed structures that Poole-Frenkel conduction is dominant at low field while Fowler-Nordheim tunneling in high field. Spectroscopic ellipsometry measurement revealed that the PDA process decreases the bandgap of the dielectric layers. We found that a decreasing of peak intensity in the middle HfO"yN"z layer as measured by Tof-SIMS may suggest the movement of N toward the interface region between the HfO"yN"z layer and the Si substrate during the annealing process.
Impact and compensation of correlated process variation on ring oscillator based puf
Authors: Abhranil Maiti, Patrick Schaumont
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

A Physical Unclonable Function in silicon is a die-unique challenge-response function that exploits circuit variations. A PUF has the potential to become an important security solution due to its ability to generate volatile secret keys. Before a PUF can be integrated into a system, its critical quality factors, including uniqueness, reliability and resiliency to different types of attacks, must be ensured. The uniqueness of a PUF is determined by the random inter-die process variations. However, manufacturing process variations have another component, called correlated intra-die variations. This component becomes significant in deep-submicron device technology below 90nm. In this paper, we show that the quality of a ring oscillator (RO) based PUF is affected by correlated intra-die process variation. We present experiments on 90nm FPGA devices and analyze the experimental data to quantify the effect and also propose a method to improve the quality of an RO-PUF by minimizing the effect of correlated intra-die variations.
Generating Worst-Case Stimuli for Accurate Power Grid Analysis
Authors: Pedro Marques Morgado, Paulo F. Flores, José C. Monteiro, L. Miguel Silveira
Venue: Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation: 18th International Workshop, PATMOS 2008, Lisbon, Portugal, September 10-12, 2008. Revised Selected Papers (2009)

Power distribution systems provide the voltages and currents that devices in a circuit need to operate properly and silicon success requires its careful design and verification. However, problems like voltage drop, ground bounce and electromigration, which may cause chip failures, are worsening, as more devices, operating at higher frequencies, are placed closer together. Verification of this type of systems is usually done by simulation, a costly endeavor given the size of current grids, making the determination of the worst-case input setting a crucial task. Current methodologies are based on supposedly safe settings targeting either unrealistic simultaneous switching on all signals or heuristic accounts of the joint switching probability of nearby signals. In this paper we propose a methodology for computation of the worst-case stimuli for power grid analysis. This is accomplished by determining the input vector that maximizes the number of gates, in close proximity to each other, that can switch in a given time window. The addition of these temporal and spatial restrictions makes the solution of the underlying optimization problem feasible. Comparisons with existing alternatives show that only a fraction of the gates change in any given timing window, leading to a more robust and efficient verification methodology.
A Multimodal Constellation Model for Object Category Recognition
Authors: Yasunori Kamiya, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase
Venue: Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling (2009)

Object category recognition in various appearances is one of the most challenging task in the object recognition research fields. The major approach to solve the task is using the Bag of Features (BoF). The constellation model is another approach that has the following advantages: (a) Adding and changing the candidate categories is easy; (b) Its description accuracy is higher than BoF; (c) Position and scale information, which are ignored by BoF, can be used effectively. On the other hand, this model has two weak points: (1) It is essentially an unimodal model that is unsuitable for categories with many types of appearances. (2) The probability function that represents the constellation model takes a long time to calculate. In this paper we propose a "Multimodal Constellation Model" to solve the two weak points of the constellation model. Experimental results showed the effectivity of the proposed model by comparison to methods using BoF.
Color consistency in digital camera color reproduction based on machine learning
Authors: Li Xinwu
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

Digital camera is the one of the main devices in the computer and multimedia technology and its color management model is the key to guarantee the color consistency in the succedent image production and transfers. The paper presents a color conversion model for digital camera based on BP neural network and the analysis of color rendering principle of digital camera. First, digital camera data is pretreated to a unitary field to satisfy the scope requirement of the input and output data of the BP model. Second, the color shade districts are taken to stand for the color space to decrease the calculation of the model. Third, the active item which can adjust BP model step dynamically is used to increase convergence speed of the BP model. Finally, the realization and experiment results show that, compared with some methods which is have relatively high accuracy, the algorithm can improve color conversion accuracy and can satisfy the engineering requirement in digital camera color management.
Data types and program correctness
Authors: Barbara H. Liskov
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

One of the most important current software issues is reliability, and accordingly, a major criterion of programming language design must be that the language contribute to the production of reliable programs. Although there are other important aspects of software reliability (e.g., fault tolerance), the most fundamental is program correctness: does the program do what it is supposed to do? A language can contribute to this goal by enhancing the provability of its programs. This paper discusses the impact of user-defined data types on program provability.
Alternative diagnosis of corporate bankruptcy: A neuro fuzzy approach
Authors: Hsueh-Ju Chen, Shaio Yan Huang, Chin-Shien Lin
Venue: Expert Systems with Applications: An International Journal (2009)

Bankruptcy filings are as high today as ever, calling into question the efficacy of existing bankruptcy prediction models. This paper tries to provide an alternative for bankruptcy prediction by using neuro fuzzy, a hybrid approach combining the functionality of fuzzy logic and the learning ability of neural networks. The empirical results show that neuro fuzzy demonstrates a better accuracy rate, lower misclassification cost and higher detecting power than does logit regression, meaning neuro fuzzy could be a great help in providing warnings of impending bankruptcy. Also, its comprehensive explanation about mapping functions among variables presumably provides a foundation for further development of theory and testing of the membership function shape, the transfer function, the methods to aggregate, the methods to defuzzify, and so on.
Large Deviation Theorems Revisited: Information-Spectrum Approach
Authors: Te-Sun Han
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

In this paper we show some new look at large deviation theorems from the viewpoint of the information-spectrum (IS) methods, which has been first exploited in information theory, and also demonstrate a new basic formula for the large deviation rate function in general, which is expressed as a pair of the lower and upper IS rate functions. In particular, we are interested in establishing the general large deviation rate functions that are derivable as the Fenchel-Legendre transform of the cumulant generating function. The final goal is to show, under some mild condition, a necessary and sufficient condition for the IS rate function to be derivable as the Fenchel-Legendre transform of the cumulant generating function, i.e., to be a rate function of Gärtner-Ellis type.
A Feasible RF Bandpass Sampling Architecture of Single-Channel Software-Defined Radio Receiver
Authors: Xiangyang Wang, Shuyang Yu
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

Software-defined radio (SDR) can support multiple communication standards and provide flexible services. In this paper, a feasible radio frequency (RF) bandpass sampling architecture of single-channel SDR receiver is proposed. The tradeoff between the sampling frequency and resolution of the analog-to-digital converter (ADC) and the selectivity and tunability of the bandpass filter provides a natural way to alleviate the design challenge of RF bandpass filter. The passband of the bandpass filter can be wider than the bandwidth of the desired signal, resulting in increasing the sampling frequency and resolution. The minimum acceptable sampling frequency is based on the bandwidth of the signal and the passband of the bandpass filter. The out-of-band interferences are further attenuated in digital domain. The signal can be decimated by sample rate conversion after it has been converted to baseband to reduce the processing rate.
Performance modeling, real-time dispatching and simulation of wafer fabrication systems using timed extended object-oriented Petri nets
Authors: Huiran Liu, Zhibin Jiang, Richard Y. K. Fung
Venue: Computers and Industrial Engineering (2009)

Semiconductor wafer fabrication system (SWFS) is the most complex and capital-intensive phase in the entire semiconductor manufacturing cycle. With characteristics of re-entrant processing routes, equipment uncertainty, product diversity and improving technologies, great challenges are presented in SWFS's modeling, scheduling and simulation. To implement efficient production control, this paper provides a timed extended object-oriented Petri nets (TEOPNs) approach to performance modeling, real-timed dispatching and simulation of SWFSs. The TEOPNs models are constructed in a hierarchy to accord with the real-world SWFS's organization, and a new type of signal place is added into the TEOPNs to respond the dynamic states of all processing facilities. A novel autonomy and coordination-based real-time dispatching mechanism (A&C-RDM) is developed in this paper, which executes under the support of the TEOPNs-based hybrid real-time dispatching control system (HRDCS). Owning to the ability of gathering dynamic real-time information of all production facilities and WIP products, the HRDCS can make adaptive dispatching decisions according to the local and global real-time processing status. Two sets of key elements of real-time dispatching, i.e. the state thresholds and dispatching rules, are defined in the HRDCS so that the A&C-RDM can integrate different types of dispatching rules. A set of simulation experiments prove the efficiency of the proposed modeling and dispatching algorithm. In summary, the proposed TEOPNs, HRDCS and A&C-RDM form the cornerstones of a real-time dispatching simulation prototype of SWFS, and the work described in this paper carries out an advanced integrated ''modeling-dispatching-simulation'' methodology.
Parallelism-Aware Batch Scheduling: Enabling High-Performance and Fair Shared Memory Controllers
Authors: Onur Mutlu, Thomas Moscibroda
Venue: IEEE Micro (2009)

Uncontrolled interthread interference in main memory can destroy individual threads' memory-level parallelism, effectively serializing the memory requests of a thread whose latencies would otherwise have largely overlapped, thereby reducing single-thread performance. The parallelism-aware batch scheduler preserves each thread's memory-level parallelism, ensures fairness and starvation freedom, and supports system-level thread priorities.
Classification algorithm sensitivity to training data with non representative attribute noise
Authors: Michael Mannino, Yanjuan Yang, Young Ryu
Venue: Decision Support Systems (2009)

We present an empirical comparison of classification algorithms when training data contains attribute noise levels not representative of field data. To study algorithm sensitivity, we develop an innovative experimental design using noise situation, algorithm, noise level, and training set size as factors. Our results contradict conventional wisdom indicating that investments to achieve representative noise levels may not be worthwhile. In general, over representative training noise should be avoided while under representative training noise is less of a concern. However, interactions among algorithm, noise level, and training set size indicate that these general results may not apply to particular practice situations.
A multiexpert collaborative biometric system for people identification
Authors: Maria De Marsico, Michele Nappi, Daniel Riccio, Genny Tortora
Venue: Journal of Visual Languages and Computing (2009)

Present identification through single-biometric systems suffer from a number of limitations, due to the fact that no single bodily or behavioral feature is able to satisfy at the same time acceptability, speed and reliability constraints of authentication in real applications. Multibiometric systems can solve a number of problems of single-biometry approaches. A crucial issue to be investigated relates to how results from different systems should be evaluated and fused, in order to obtain an as reliable as possible global response. A further source of flaws for present systems, both single-biometric and multibiometric, can be found in the lack of dynamic update of parameters, which does not allow them to adapt to changes in the working settings. They are generally calibrated once and for all, so that they are tuned and optimized with respect to specific conditions. In this work, we investigate an architecture where single-biometry subsystems work in parallel, yet exchanging information at fixed points, according to the N-Cross Testing Protocol. In particular, the integrated subsystems work on the same biometric feature, the face in this case, yet exploiting different classifiers. Notice that such specific configuration is interesting to underline how the strengths of one classifier can compensate for flaws of other classifiers, so that the final result is more accurate and reliable. Moreover, parameters of each subsystem are also dynamically optimized according to the behavior of all the others. This is achieved by an additional component, the supervisor module, which analyzes the responses from all subsystems and modifies the degree of reliability required from each of them to accept the respective responses. In this way subsystems collaborate at a twofold level, both for returning a common answer and for tuning to changing operating conditions. The paper explores the combination of these two novel approaches, demonstrating that component collaboration increases system accuracy and allows identifying unstable subsystems.
Electronic structure and optical transitions in Sn and SnGe quantum dots in a Si matrix
Authors: P. Moontragoon, N. Vukmirović, Z. Ikonić, P. Harrison
Venue: Microelectronics Journal (2009)

Self-assembled quantum dots in the Si-Ge-Sn system have attracted research attention as possible direct band gap materials, compatible with Si-based technology, with potential applications in optoelectronics. In this work, the electronic structure near the Γ-point and the interband optical matrix elements of strained Sn and SnGe quantum dots in a Si matrix are calculated using the eight-band k.p method, and the competing L-valley conduction band states were found by the effective mass method. The strain distribution in the dots was found within the continuum mechanical model. The bulk band-structure parameters, required for the k.p or effective mass calculation for Sn were extracted by fitting to the energy band structure calculated by the non-local empirical pseudopotential method (EPM). The calculations show that the self-assembled Sn/Si dots, with sizes between 4 and 12nm, have indirect interband transition energies (from the size-quantized valence band states at Γ to the conduction band states at L) between 0.8 and 0.4eV, and direct interband transitions between 2.5 and 2.0eV, which agrees very well with experimental results. Similar good agreement with experiment was also found for the recently grown SnGe dots on Si substrate, covered by SiO2. However, neither of these is predicted to be direct and gap materials, in contrast to some earlier expectations.
Tabletop concept mapping
Authors: Stefan Oppl, Christian Stary
Venue: Proceedings of the 3rd International Conference on Tangible and Embedded Interaction (2009)

Concept mapping is designed to externalize and represent knowledge. Together with their visual presentation concept maps should support focused and sustainable interaction between students and coaches or members of organizations. Hence, corresponding tool support has not only to empower persons externalizing their mental models but also to enable transparent multi-party interaction based on context-sensitive (re)presentations. We introduce the Tabletop Concept Mapping (TCM) technique and tool which is supposed to meet these requirements. Providing an open space to express individual thoughts and ideas, it maximizes openness with respect to pragmatics, semantics and syntax of modeling, and minimizes intervention through feature-inherent properties of the artifact.
Personalisation in mobile learning
Authors: Dylan Marin, Permanand Mohan
Venue: International Journal of Mobile Learning and Organisation (2009)

This article provides a comprehensive survey of the current state-of-the-art in personalisation in mobile learning (m-learning) systems. The article first highlights the importance of personalisation in m-learning systems and then explains what can be personalised in an m-learning system. This is followed by a discussion of six dimensions of personalisation which are used as a basis for making personalisation decisions. The article also reviews and analyses a wide range of personalisation techniques implemented in current m-learning systems. It concludes with a discussion of research projects in personalisation that can be tackled to harness the potential benefits of personalised m-learning.
A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach
Authors: Ming-Lang Tseng
Venue: Expert Systems with Applications: An International Journal (2009)

This research uses a solution based on a combined grey-fuzzy DEMATEL method to deal with the objective of the study. This study is aimed to present a perception approach to deal with real estate agent service quality expectation ranking with uncertainty. The ranking of best top five real estate agents might be a key strategic direction of other real estate agents prior to service quality expectation. The solving procedure is as follows: (i) the weights of criteria and alternatives are described in triangular fuzzy numbers; (ii) a grey possibility degree is used to result the ranking order for all alternatives; (iii) DEMATEL is used to resolve interdependency relationships among the criteria and (iv) an empirical example of real estate agent service quality ranking problem in customer expectation is used to resolve with this proposed method approach indicating that real estate agent R"1 (CY real estate agent) is the best selection in terms of service quality in customer expectation.
Dynamically de-skewable clock distribution methodology
Authors: Arjun Kapoor, Nikhil Jayakumar, Sunil P. Khatri
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2008)

In a typical clock distribution scheme, a central clock signal is distributed to several sites on the integrated circuit (IC). Local regenerators at these sites buffer the clock signal for the logic in regions close to the regenerator. Minimizing the skew between the clocks at these regeneration sites is critical. In recent times, this is becoming harder due to increasing intra-die processing variations. In this paper, we describe a novel technique to distribute a clock signal from a central location to several sites on a VLSI IC. Our technique uses a buffered H-tree and includes circuitry to dynamically remove any skew that may result due to intra-die processing variations. While existing approaches to deskewing a clock tree have utilized several phase detection circuits (number of phase detectors dependent on the number of clock regenerators), our method requires only one phase detector. Also, in our approach, the resolution of the phase detector is inconsequential unlike existing techniques. Our deskewing technique can be applied dynamically, either at boot time or periodically during the operation of the IC. Using a six-level H-tree clock distribution network with process variations deliberately included, we demonstrate that our technique can reduce skews as high as 300 ps down to just 3 ps. We compare our clock tree with traditional buffered and unbuffered H-tree networks.
Mixed Gases Recognition Based on Feedforward Neural Network
Authors: Zhou Tao, Wang Lei
Venue: Proceedings of the 2009 Second International Symposium on Intelligent Information Technology and Security Informatics (2009)

The three gas sensors array was developed in this paper, and it was encapsulated through the Micro-Electro-Mechanical Systems (MEMS) technique. The gas sensors applied the heating unit to improve the sensitivity. The gas sensor which was sensitive to the special gas could be selected in the different application fields. The sampling experiments showed that the gas sensors have the higher sensitivity and better repeatability and cross sensitivity. Moreover, the pattern recognition algorithms based on a feedforward neural network were studied in the paper. They have the higher pattern recognition capacity, the convergence rate and simpler training method. The intelligent recognition system which adopted the gas sensor array and feedforward neural network was design. The recognition experiments showed the system has better identification effect and higher accuracy.
Face Quality Assessment System in Video Sequences
Authors: Kamal Nasrollahi, Thomas B. Moeslund
Venue: Biometrics and Identity Management: First European Workshop, BIOID 2008, Roskilde, Denmark, May 7-9, 2008. Revised Selected Papers (2008)

When a person passes by a surveillance camera a sequence of image is obtained. Before performing any analysis on the face of a person, the face first needs to be detected and secondary the quality of the different face images needs to be evaluated. In this paper we present a system based on four simple features including out-of-plan rotation, sharpness, brightness and resolution, to assess the face quality in a video sequence. These features are combined using both a local scoring system and weights. The system is evaluated on two databases and the results show a general agreement between the system output and quality assessment by a human.