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This paper describes a transmission expansion planning method based on multi-objective optimization (MOOP). The method starts with constructing a candidate pool of feasible expansion plans, followed by selection of the best candidates through MOOP, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in the market environment. Subsequently, reliability assessment is performed to evaluate and reinforce the resultant expansion plan from MOOP. The proposed method has been tested with the IEEE 14-bus system and analyses and discussions have been presented.

The map is more important than ever, but what it can represent and how it is delivered is changing radically as new geospatial technologies emerge. In the field of geology, paper maps have always aimed to represent the complex threedimensional world beneath our feet and make it understandable to us at the surface. However, new smart phone mapping applications enable us to take the map with us more easily and to ask questions of it wherever we are, and to add our own observations on to it. Digital survey and modelling technologies will enable geologists to communicate geology in 3D for us, rather than having to translate it to 2D; everyone will then see the geology as the geologist does as we take visualisation from the lab to the street. As an interactive tool the geological map of the future will be very different.

The map is more important than ever, but what it can represent and how it is delivered is changing radically as new geospatial technologies emerge. In the field of geology, paper maps have always aimed to represent the complex threedimensional world beneath our feet and make it understandable to us at the surface. However, new smart phone mapping applications enable us to take the map with us more easily and to ask questions of it wherever we are, and to add our own observations on to it. Digital survey and modelling technologies will enable geologists to communicate geology in 3D for us, rather than having to translate it to 2D; everyone will then see the geology as the geologist does as we take visualisation from the lab to the street. As an interactive tool the geological map of the future will be very different.

As online social networks are becoming part of both social and work life, preserving privacy of their users is becoming tremendously difficult. While these social networks are promising privacy through privacy agreements, everyday new privacy leakages are emerging. Ideally, online social networks should be able to manage and maintain their agreements through well-founded methods. However, the dynamic nature of the online social networks is making it difficult to keep private information contained. We have developed PROTOSS, a run time tool for detecting privacy leakages in online social networks. PROTOSS captures relations among users, their privacy agreements with an online social network operator, and domain-based inference rules. It then uses model checking to detect if an online social network will leak private information.

As online social networks are becoming part of both social and work life, preserving privacy of their users is becoming tremendously difficult. While these social networks are promising privacy through privacy agreements, everyday new privacy leakages are emerging. Ideally, online social networks should be able to manage and maintain their agreements through well-founded methods. However, the dynamic nature of the online social networks is making it difficult to keep private information contained. We have developed PROTOSS, a run time tool for detecting privacy leakages in online social networks. PROTOSS captures relations among users, their privacy agreements with an online social network operator, and domain-based inference rules. It then uses model checking to detect if an online social network will leak private information.

As online social networks are becoming part of both social and work life, preserving privacy of their users is becoming tremendously difficult. While these social networks are promising privacy through privacy agreements, everyday new privacy leakages are emerging. Ideally, online social networks should be able to manage and maintain their agreements through well-founded methods. However, the dynamic nature of the online social networks is making it difficult to keep private information contained. We have developed PROTOSS, a run time tool for detecting privacy leakages in online social networks. PROTOSS captures relations among users, their privacy agreements with an online social network operator, and domain-based inference rules. It then uses model checking to detect if an online social network will leak private information.

The bidirectional broadcast channel denotes a broadcast channel with two receivers where each receiver knows the message intended for the other. We consider streaming sources where messages of each user arrive as bit-stream to the encoder. Thus our main quantity of interest is the bit error probability. By extending Sahai's argument to bidirectional broadcast channel, we show that under maximum-likelihood decoding the bit error probability decays exponentially in delay with positive exponent for all the rate pairs inside the capacity region. We also show existence of deterministic codes which achieve exponentially decaying bit error probability with delay., QC 20111216

The single-mode properties and design issues of three vertical-cavity surface-emitting laser (VCSEL) structures incorporating nano structures are rigorously investigated. Nano structuring enables to deliver selective pumping or loss to the fundamental mode as well as stabilizing the output polarization state. Comparison of three vectorial simulation methods reveals that the modal expansion method is suitable for treating the nano structured VCSEL designs.

We demonstrate ROX, a run-time optimizer of XQueries, that focuses on finding the best execution order of XPath steps and relational joins in an XQuery. The problem of join ordering has been extensively researched, but the proposed techniques are still unsatisfying. These either rely on a cost model which might result in inaccurate estimations, or explore only a restrictive number of plans from the search space. ROX is developed to tackle these problems. ROX does not need any cost model, and defers query optimization to run-time intertwining optimization and execution steps. In every optimization step, sampling techniques are used to estimate the cardinality of unexecuted steps and joins to make a decision which sequence of operators to process next. Consequently, each execution step will provide updated and accurate knowledge about intermediate results, which will be used during the next optimization round. This demonstration will focus on: (i) illustrating the steps that ROX follows and the decisions it makes to choose a good join order, (ii) showing ROX’s robustness in the face of data with different degree of correlation, (iii) comparing the performance of the plan chosen by ROX to different plans picked from the search space, (iv) proving that the run-time overhead needed by ROX is restricted to a small fraction of the execution time.

With the advances in Information Technology (IT) there has been an increase in threats to the communication systems and its assets. One of the most important issues of all IP networks that integrate wireless and wired technologies is the applicability and performance of the electronic identification and authentication methods. These schemes employ a variety of technologies of different degrees of security. Biometrics technology nowadays is typically considered a security necessity, tightly coupled with the foundation of highly secure identification and authentication solutions. This article provides a short survey on different types of authentication and identity management systems. It attempts to describe a summary of related works including some of the latest schemes in face and fingerprint recognition. With a better understanding of electronic authentication techniques any organization can properly select and utilize the technologies which meet its needs.

With the advances in Information Technology (IT) there has been an increase in threats to the communication systems and its assets. One of the most important issues of all IP networks that integrate wireless and wired technologies is the applicability and performance of the electronic identification and authentication methods. These schemes employ a variety of technologies of different degrees of security. Biometrics technology nowadays is typically considered a security necessity, tightly coupled with the foundation of highly secure identification and authentication solutions. This article provides a short survey on different types of authentication and identity management systems. It attempts to describe a summary of related works including some of the latest schemes in face and fingerprint recognition. With a better understanding of electronic authentication techniques any organization can properly select and utilize the technologies which meet its needs.

A numerical method for the solution of scattering of the H-and E-plane waveguide junctions is described. The approach is a combination of the boundary-element method and the analytical method. A general computer programs has been developed using the quadratic elements (higher order boundary elements). To show the validity and usefulness of this formulation, computed results are given for a right-angle corner bend, a T-junction, an inductive strip-planar circuit mounted in a waveguide, a waveguide-type dielectric filter, and an inhomogeneous waveguide junction, and a linear taper. Comparison of the present results with the results of the finite-element method shows good agreement.

A numerical method for the solution of scattering of the H-and E-plane waveguide junctions is described. The approach is a combination of the boundary-element method and the analytical method. A general computer programs has been developed using the quadratic elements (higher order boundary elements). To show the validity and usefulness of this formulation, computed results are given for a right-angle corner bend, a T-junction, an inductive strip-planar circuit mounted in a waveguide, a waveguide-type dielectric filter, and an inhomogeneous waveguide junction, and a linear taper. Comparison of the present results with the results of the finite-element method shows good agreement.

A numerical method for the solution of scattering of the H-and E-plane waveguide junctions is described. The approach is a combination of the boundary-element method and the analytical method. A general computer programs has been developed using the quadratic elements (higher order boundary elements). To show the validity and usefulness of this formulation, computed results are given for a right-angle corner bend, a T-junction, an inductive strip-planar circuit mounted in a waveguide, a waveguide-type dielectric filter, and an inhomogeneous waveguide junction, and a linear taper. Comparison of the present results with the results of the finite-element method shows good agreement.

In this paper, we study path planning algorithms of resource constrained mobile agents in unknown cluttered environments, which include but are not limited to various terrestrial missions e.g., search and rescue missions by drones in jungles, and space missions e.g., navigation of rovers on the Moon. In particular, we focus our attention on artificial potential field (APF) based methods, in which the target is attractive while the obstacles are repulsive to the mobile agent. In this paper, we propose two major updates to the classical APF algorithm which significantly improve the performance of path planning using APF. First, we propose to improve an existing classical method that replaces the gradient descent optimization of the potential field cost function on a continuous domain with a combinatorial optimization on a set of predefined points (called bacteria points) around the agent's current location. Our proposition includes an adaptive hyperparameter that changes the value of the potential function associated to each bacteria point based on the current environmental measurements. Our proposed solution improves the navigation performance in terms of convergence to the target at the expense of minimal increase in computational complexity. Second, we propose an improved potential field cost function of the bacteria points by introducing a new branching cost function which further improves the navigation performance. The algorithms were tested on a set of Monte Carlo simulation trials where the environment changes for each trial. Our simulation results show 25% lower navigation time and around 300% higher success rate compared to the conventional potential field method, and we present future directions for research., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

IEEE SA White Paper, The security aspects of V2V communications in UAS addressed by IEEE P1920.2 are delineated in this paper. Those include the architecture of communication interfaces, authentication of V2V parties, cryptographic key management, and zero trust architecture.

The 2nd workshop on Datasets for Developing Intelligent XR Applications (DATA4XR) aims to address the challenges of public datasets and reproducibility in Extended Reality, also known as XR (Augmented Reality, Virtual Reality, and Mixed Reality) research. The workshop brings together experts to discuss the availability, privacy concerns, and ethics related to open-sourcing the datasets used in XR research for algorithm training and user behavior analysis. By examining the ethical, moral, and privacy concerns and categorizing open-source datasets for XR, the workshop expects to advance XR research by incorporating artificial intelligence and defining a research agenda for XR in open science. In addition, the workshop focuses on involving the Human-Computer Interaction (HCI) community in exploring its role in the future of XR research. We invite submissions of technical papers, position papers, and research papers on topics related to XR and open science.

So far, the relationship between open science and software engineering expertise has largely focused on the open release of software engineering research insights and reproducible artifacts, in the form of open-access papers, open data, and open-source tools and libraries. In this position paper, we draw attention to another perspective: scientific insight itself is a complex and collaborative artifact under continuous development and in need of continuous quality assurance, and as such, has many parallels to software artifacts. Considering current calls for more open, collaborative and reproducible science; increasing demands for public accountability on matters of scientific integrity and credibility; methodological challenges coming with transdisciplinary science; political and communication tensions when scientific insight on societally relevant topics is to be translated to policy; and struggles to incentivize and reward academics who truly want to move into these directions beyond traditional publishing habits and cultures, we make the parallels between the emerging open science requirements and concepts already well-known in (open-source) software engineering research more explicit. We argue that the societal impact of software engineering expertise can reach far beyond the software engineering research community, and call upon the community members to proactively help driving the necessary systems and cultural changes towards more open and accountable research., Multimedia Computing

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

Stock investment is a low barrier but high-risk approach of investing, which requires lots of knowledge and experience for investors in order to earn money. The work in this paper enables investors who do not meet the above conditions to still make accurate investment actions with the predicted output given by the model. In this paper, ten years of historical data of Amazon was used to train the LSTM model, then different candidates of model architecture were attempted to test out the optimal one for predicting the stock close price of Amazon and evaluated. It was observed in the result that the model with more neurons in each hidden layers and less LSTM layers and Dense layers showed a higher accuracy and a more stable forecast. In the other hand, the numbers of historical data memorized did matter. The less memory days could result in a smaller mean absolute percentage error. © 2023 IEEE.

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

We propose a new blind watermarking algorithm for three-dimensional (3D) printed objects that has applications in metadata embedding, robotic grasping, counterfeit prevention, and crime investigation. Our method can be used on fused deposition modeling (FDM) 3D printers and works by modifying the printed layer thickness on small patches of the surface of an object. These patches can be applied to multiple regions of the object, thereby making it resistant to various attacks such as cropping, local deformation, local surface degradation, or printing errors. The novelties of our method are the use of the thickness of printed layers as a one-dimensional carrier signal to embed data, the minimization of distortion by only modifying the layers locally, and one-shot detection using a common paper scanner. To correct encoding or decoding errors, our method combines multiple patches and uses a two-dimensional (2D) parity check to estimate the error probability of each bit to obtain a higher correction rate than a naive majority vote. The parity bits included in the patches have a double purpose because, in addition to error detection, they are also used to identify the orientation of the patches. In our experiments, we successfully embedded a watermark into flat surfaces of 3D objects with various filament colors using a standard FDM 3D printer, extracted it using a common 2D paper scanner and evaluated the sensitivity to surface degradation and signal amplitude.

This paper proposes a novel method for generating arbitrary stereoscopic view from multiple omni directional image sequences. Although conventional methods for arbitrary view generation with an image-based rendering approach can create binocular views, positions and directions of viewpoints for stereoscopic vision are limited to a small range. In this research, we attempt to generate arbitrary stereoscopic views from omni directional image sequences that are captured in various multiple paths. To generate a high-quality stereoscopic view from a number of images captured at various viewpoints, appropriate ray information needs to be selected. In this paper, appropriate ray information is selected from a number of omni directional images using a penalty function expressed as ray similarity. In experiments, we show the validity of this penalty function by generating stereoscopic view from multiple real image sequences., ICPR 2010 : 20th International Conference on Pattern Recognition , Aug 23-26, 2010 , Istanbul, Turkey

In this paper, a barge-in free spoken dialogue system using sound field control and microphone array is proposed. In the conventional spoken dialogue system using an acoustic echo canceller, it is indispensable to estimate and update the room transfer function, especially when the transfer function is changed by various interferences. However the estimation process for the transfer function prevents the user from speaking freely and simultaneously with speech responses from the system. In order to resolve the problem, we have already proposed a barge-in free spoken dialogue system that controls a sound field using multiple loudspeakers. In this paper, a microphone array for acquisition of user's speech is newly introduced in the previously proposed system. By introducing the microphone array, we can reduce the number of loudspeakers to be required in the system, and make the interface for spoken dialogue system more robust against the change of room transfer functions., ICASSP2003: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 6-10, 2003, Hong Kong, China.

This paper describes a new blind signal separation method using the directivity patterns of a microphone array. In this method, to deal with the arriving lags among each microphone, the inverses of the mixing matrices are calculated in the frequency domain so that the separated signals are mutually independent. Since the calculations are carried out in each frequency independently, the following problems arise: (1) permutation of each sound source, (2) arbitrariness of each source gain. In this paper, we propose a new solution that directivity patterns are explicitly used to estimate each sound source direction. As the results of signal separation experiments, it is shown that the proposed method improves the SNR of degraded speech by about 16 dB under non-reverberant condition. Also, the proposed method improves the SNR by 8.7 dB when the reverberation time is 184 ms, and by 5.1 dB when the reverberation time is 322 ms, ICASSP2000: IEEE International Conference on Acoustics, Speech, and Signal Processing, June 5-9, 2000, Istanbul, Turkey.

Deals with the recognition of distant talking speech and, particularly, with the simultaneous recognition of multiple sound sources. A problem that must be solved in the recognition of distant talking speech is talker localization. In some approaches, the talker is localized by using short- and long-term power. The 3-D Viterbi search based method proposed by Yamada et al.(1998), integrates talker localization and speech recognition. This method provides high recognition rates but its application is restricted to the presence of one talker. In order to deal with multiple talkers, we extended the 3-D Viterbi search method to a 3-D N-best search method enabling the recognition of multiple sound sources. The paper describes our baseline 3-D N-best search-based system and two additional techniques, namely, a likelihood normalization technique and a path distance-based clustering technique. The paper also describes experiments carried out in order to evaluate the performance of the system, ICASSP2001: IEEE International Conference on Acoustics, Speech and Signal Processing, May 7-11, 2001, Salt Lake City, Utah, US.

This paper describes a method for determining the vocal tract spectrum from articulatory movements using an hidden Markov models (HMMs). In the proposed system, articulatory parameters are generated from a TTS system and converted to acoustic features to be synthesized. Comparing with conventional GMM-based systems, the proposed system has two additional properties: 1) phonetic information given input texts is available for the conversion, 2) the use of HMMs allows us to utilize the temporal structure of speech. In this paper, we investigate the optimal structure of HMMs for the conversion. Experimental results show that using phonetic and temporal information can improve the mapping accuracy in a spectral distortion measure, ICASSP2006: IEEE International Conference on Acoustics, Speech, and Signal Processing, May 14-19, 2006, Toulouse, France.

In this paper, we reveal new findings about the generated musical noise in minimum mean-square error short-time spectral amplitude (MMSE STSA) processing. Recently we have proposed a objective metric of musical noise based on kurtosis change ratio on spectral subtraction (SS). Also we found an interesting relationship among the degree of generated musical noise, the shapes of signal-s probability density function, the strength parameter of SS processing. This paper is aimed to automatically evaluate the sound quality of various types of noise reduction methods using kurtosis change ratio. We give a mathematical analysis based on higher-order statistics viewpoint, and lead to a valuable relation in that MMSE STSA has a weakness in speech period distortion rather than noise period, and vice versa in SS., ICASSP2009: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 19-24, 2009, Taipei, Taiwan.

The performance of a speech recognizer is degraded drastically in reverberant environments. The authors propose a novel algorithm which can model an observation signal by composition of HMMs of clean speech, noise and an acoustic transfer function. However, estimating HMM parameters of the acoustic transfer function is still a serious problem. In their previous paper, they measured real impulse responses of training positions in an experiment room. It is inconvenient and unrealistic to measure impulse responses for every possible new experiment room. The paper presents a new method for estimating HMM parameters of the acoustic transfer function from some adaptation data by using an HMM decomposition algorithm which is an inverse process of the HMM composition. Its effectiveness is confirmed by a series of speaker dependent and independent word recognition experiments on simulated distant-talking speech data, ICASSP1997: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 21-24, 1997.

This study is concerned with a large-scale telepresence system based on remote control of mobile robot or aerial vehicle. The proposed system provides a user with not only view of remote site but also related information by AR technique. Such systems are referred to as augmented telepresence in this paper. Aerial imagery can capture a wider area at once than image capturing from the ground. However, it is difficult for a user to change position and direction of viewpoint freely because of the difficulty in remote control and limitation of hardware. To overcome these problems, the proposed system uses an autopilot airship to support changing user's viewpoint and employs an omni-directional camera for changing viewing direction easily. This paper describes hardware configuration for aerial imagery, an approach for overlaying virtual objects, and automatic control of the airship, as well as experimental results using a prototype system., ISMAR 2010 : 9th IEEE International Symposium on Mixed and Augmented Reality , Oct 13-16, 2010 , Seoul, Korea

This paper describes a hands-free speech recognition method based on HMM composition and separation for speech contaminated not only by additive noise but also by an acoustic transfer function. The method realizes an improved user interface such that a user is not encumbered by microphone equipment in noisy and reverberant environments. In this approach, an attempt is made to model acoustic transfer functions by means of an ergodic HMM. The states of this HMM correspond to different positions of the sound source. It can represent the positions of the sound sources, even if the speaker moves. The HMM parameters of the acoustic transfer function are estimated by HMM separation. The method is obtained through the reverse of the process of HMM composition, where the model parameters are estimated by maximizing the likelihood of adaptation data uttered from an unknown position. Therefore, measurement of impulse responses is not required. In this paper, we record the speech of a distant moving speaker in real environments. The results of experiments for the speech of a distant moving speaker clarified the effectiveness of HMM composition and separation, ICASSP2000: IEEE International Conference on Acoustics, Speech, and Signal Processing, June 5-9, 2000, Istanbul, Turkey.

In this paper we propose a new unsupervised training method for nonlinear spatial filter using a new independent component analysis based on kernel infomax. The nonlinearity of the spatial filter used in this paper is equivalent to the integration of beamforming and spectral subtraction, and the whole structure is optimized by independent component analysis in the reproducing kernel Hilbert space. The optimized filter is shown to be capable of achieving better quality output than the conventional method based on time-frequency binary masking., ICASSP2009: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 19-24, 2009, Taipei, Taiwan.

This paper study the blind estimation of the diffuse background noise for the hands-free speech interface. Some recent papers showed that it is possible to use blind signal separation (BSS) to estimate the diffuse background noise by suppressing the speech component after all the components were separated. In particular, the scale indeterminacy of BSS is avoided by using the projection back method. In this paper, we study an alternative to the projection back for the noise estimation and justify the use of blind signal extraction BSE rather than BSS., ICASPP2010: IEEE International Conference on Acoustics, Speech, and Signal Processing, March 14-19, 2010, Dallas, Texas, USA.

This paper presents a novel method for training hidden Markov models (HMMs) for use in HMM-based speech synthesis. The primary goal of HMM parameter optimization is to ensure that parameters generated from the trained models exhibit similar properties to natural speech. In this paper, two major problems in conventional training are addressed: 1) the inconsistency between the training and synthesis optimization criterion; and 2) the over-smoothing caused by the statistical modeling process. The proposed method integrates the global variance (GV) criterion into a trajectory training method to give a unified framework for both training and synthesis which provides both a consistent optimization criterion and a closed form solution for parameter generation. The experimental results demonstrate that the proposed method yields a significant improvement in the naturalness of synthetic speech., ICASSP2009: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 19-24, 2009, Taipei, Taiwan.

One of the common problems in building an effort estimation model is that not all the effort factors are suitable as predictor variables. As a supplement of missing information in estimation models, this paper explores the project manager's knowledge about the target project. We assume that the experts can judge the target project's productivity level based on his/her own expert knowledge about the project. We also assume that this judgment can be further improved, because using the expert's judgment solely could incur subjective perception. This paper proposes a regression model building/selection method to address this challenge. In the proposed method, a fit dataset for model building is divided into two or three subsets by project productivity, and an estimation model is built on each data subset. The expert judges the productivity level of the target project and selects one of the models to be used. In the experiment, we used three datasets to evaluate the produced effort estimation models. In the experiment, we adjusted the error rate of the judgment and analyzed the relationship between the error rate and the estimation accuracy. As a result, the judgment-incorporating models produced significantly higher estimation accuracy than the conventional linear regression model, where the expert's error rate is less than 37%., 2012 19th Asia-Pacific Software Engineering Conference, 4-7 Dec. 2012, Hong Kong, China

The sound data for open evaluation is necessary for studies such as sound source localization, sound retrieval, sound recognition and hands-free speech recognition in real acoustic environments. This paper reports on our project for acoustic data collection. There are many kinds of sound scenes in real environments. The sound scene is specified by sound sources and room acoustics. The number of combinations of the sound sources, source positions and rooms is huge in real acoustic environments. We assumed that the sound in the environments can be simulated by convolution of the isolated sound sources and impulse responses. As an isolated sound source, hundred kinds of environment sounds and speech sounds are collected. The impulse responses are collected in various acoustic environments. Additionally we collected sounds from a moving source. In this paper, progress of our sound scene database collection project and application to environment sound recognition and hands-free speech recognition are described., ICME2002: IEEE International Conference on Multimedia and Expo, August 27-29, 2002, Lusanne, Switzerland.

The paper describes a talking face generation system with natural and communicative reality. If face movements are synthesized well enough for natural communication, a lot of benefits will be brought for the human-machine communication. We have already proposed a speech driven HMM-based lip movement synthesis, and also shown that the quality is drastically improved by considering succeeding visemes. The paper describes extension of our system to full face movement generation, and proposes a method considering both of preceding and succeeding viseme contexts. The experiments show the proposed method generates natural and accurate talking faces from audio speech inputs, ICME2000: IEEE International Conference on Multimedia and Expo, July 30 - August 2, 2000, NewYork, USA.

It is not unreasonable to say that examples are one of the most commonly used knowledge sources when learning the usage and best practices of a new API. That being said, in many cases the examples provided on the APIs' Web site are lacking in quantity or quality, so developers have to resort to other information sources, namely blogs and coding forums. Moreover, there is no good way for API developers to measure anything concerning the examples they are creating. In order to resolve the problem of lacking examples information and feedback in their creation, our goal is to develop metrics for empirical measurement of examples and to offer support during the APIs example creation steps, and this paper represents the starting point towards that aim. We have analyzed the source code examples provided on the API's Web site or GitHub directory for seven popular API libraries written in Java and measured certain metrics, such as example coverage, example code to source code ratio, class coverage percentage, and problems that occur with the compilation and execution of existing examples. The purpose of this paper is to investigate the current situation of examples and provide a starting knowledge base for building an automatic tool for source code example metrics analysis., SANER 2016 : 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering, 14-18 March 2016, Suita, Japan

The Takemaru-kun system is a real world speech-oriented guidance system located at the Ikoma-City North Community Center. The system has been operated daily from November, 2002, to provide visitors a speech interface for information retrieval. This system also aims at the field test of a speech interface and collecting actual utterance data. By analyzing and evaluating the collected utterances, the flexible processing requirements are discovered according to the user's age group. It becomes impossible to disregard the increase of child users when the system is installed in a public place. The paper proposes an automatic approach discriminating speakers between adult and child users, which is based on statistical learning. This proposal realizes a flexible spoken dialogue to both adult and child users. As for parameter vectors in machine learning, acoustic and linguistic properties extracted from speech recognition logarithm likelihood scores are adopted to discriminate a user's age group. Although GMM-based recognition uses only acoustic properties, this method can also consider linguistic properties. In experiments with SVM-based screening, we obtained a 92.4% discrimination rate to the actual users' utterances. The advantage of using linguistic properties is also shown. The paper also describes an overview of the Takemaru-kun system and the data collection status from the field test. Child speech recognition performance is evaluated using the collected utterances., ICASSP2004: IEEE International Conference on Acoustics, Speech, and Signal Processing, May 17-21, 2004, Quebec, Canada.

This paper describes a new method of measuring position of running user for location-based services in wide indoor environments, such as augmented reality navigation system with wearable computer. Conventional localization methods usually employ a hybrid approach in which user's position is estimated bv combining positioning infrastructures and a pedometer. Since the installation cost of infrastructures increases when the area expands, the measurement Figure Illustration summing up step method of user's relative position with high accuracy is required. Although a numder of methods using a pedometer have been developed to improve the estimation accuracy, these methods generally can handle only usual walking behavior of a user. This paper proposes a new real time localization method for both walking and running users by using a wearable electromagnetic tracker and an inertial sensor. The proposed localization method estimates a moving distance in the period when both legs do not ground by estimating a velocity of waist when user's leg leaves. Experiments have been carried out using a prototype system to evaluate the accuracy of user localization with the proposed method., ICAT 2007 : The 17th International Conference on Artificial Reality and Telexistence , Nov 28-30, 2007 , Esbjerg, Denmark