Research has been actively proposed into how to specify requirements in the upper stream of software development. For example, the main research issues regarding Structured Analysis and Object Oriented Analysis methodologies include requirements elicitation, modeling, and validation of specifications to give a starting point for software development. At the same time, another area of research has emerged that recognizes the importance of guaranteeing requirements quality by goals. As the impact of IT penetrates to mobile devices, information appliances and automobiles, goal oriented requirements engineering (GORE) approaches for performance and safety in embedded systems have been proposed. Non-Functional Requirements (NFRs) such as business strategy, security and privacy, are now being formalized by Requirements Engineering (RE) technologies, because enterprise business is now heavily influenced by IT, for example in e-Business. As IT is fast becoming ubiquitous in society, the importance of Goal Orientation will increase as socio-technology enables visualization of the role of software in social systems. In this paper, we discuss the current states and trends of GORE from the viewpoints of both academia and industry.

Object caching is a common feature in the scalable distributed object systems. Fine-grained replication optimizes the performance and resource utilization in object caching by enabling a remote object-oriented application to be partially and incrementally on-demand replicated in units of cluster. Despite these benefits, the lack of common and simple implementation framework makes the fine-grained replication scheme not extensively used. This paper proposes the novel frameworks for dynamic, transparent, partial and automatically incremental replication of distributed Java objects based on three techniques that are lazy-object creation, proxy and hook. One framework enables the fine-grained replication of server-side stateful in-memory application, and the other framework enables the fine-grained replication of server-side stateless in-memory application, client-side program, or standalone application. The experimental evaluation demonstrates that the efficiency in terms of response time of both frameworks are relatively practical to the extent of a local method invocation.

Most commercial Web sites dynamically generate their contents through a three-tier server architecture composed of a Web server, an application server, and a database server. In such an architecture, the database server easily becomes a bottleneck to the overall performance. In this paper, we propose WDBAccel, a high-performance database server accelerator that significantly improves the throughput of database processing. WDBAccel eliminates costly, complex query processing needed to obtain query results by reusing the results from previous queries for subsequent queries. This differentiates WDBAccel from other database cache systems, which employ traditional query processing. WDBAccel further improves its performance by fully utilizing main memory as the primary storage. This paper presents the design and implementation of the WDBAccel as well as the results of performance evaluation with a prototype.

Data mining across different companies, organizations, online shops, or the likes is necessary so as to discover valuable shared patterns, associations, trends, or dependencies in their shared data. Privacy, however, is a concern. In many situations it is required that data mining should be conducted without any privacy being violated. In response to this requirement, in this paper we propose an effective distributed privacy-preserving data mining approach called SDDM. SDDM is characterized by its ability to resist collusion. Unless the number of colluding sites in a distributed system is larger than or equal to 4, privacy cannot be violated. Results of performance study demonstrated the effectiveness of SDDM.

Recently there are various requirements for LSI testing, such as test compaction, test compression, low power dissipation or increase of defect coverage. If test sequences contain lots of don't cares (Xs), then their flexibility can be used to meet the above requirements. In this paper, we propose methods for finding as many Xs as possible in test sequences for sequential circuits. Given a fully specified test sequence generated by a sequential ATPG, the proposed methods produce a test sequence containing Xs without losing stuck-at fault coverage of the original test sequence. The methods apply an approach based on fault simulation, and they introduce some heuristics for reducing the simulation effort. Experimental results for ISCAS'89 benchmark circuits show the effectiveness of the proposed methods.

This paper proposes a new per-test fault diagnosis method based on the X-fault model. The X-fault model can represent all possible faulty behaviors of a physical defect or defects in a gate and/or on its fanout branches by assigning different X symbols assigned to the fanout branches. A partial symbolic fault simulation method is proposed for the X-fault model. Then, a novel technique is proposed for extracting more diagnostic information by analyzing matching details between observed and simulated responses. Furthermore, a unique method is proposed to score the results of fault diagnosis. Experimental results on benchmark circuits demonstrate the superiority of the proposed method over conventional per-test fault diagnosis based on the stuck-at fault model.

A novel pitch-synchronous auditory-based feature extraction method for robust automatic speech recognition (ASR) is proposed. A pitch-synchronous zero-crossing peak-amplitude (PS-ZCPA)-based feature extraction method was proposed previously and it showed improved performances except when modulation enhancement was integrated with Wiener filter (WF)-based noise reduction and auditory masking. However, since zero-crossing is not an auditory event, we propose a new pitch-synchronous peak-amplitude (PS-PA)-based method to render the feature extractor of ASR more auditory-like. We also examine the effects of WF-based noise reduction, modulation enhancement, and auditory masking in the proposed PS-PA method using the Aurora-2J database. The experimental results show superiority of the proposed method over the PS-ZCPA and other conventional methods. Furthermore, the problem due to the reconstruction of zero-crossings from a modulated envelope is eliminated. The experimental results also show the superiority of PS over PA in terms of the robustness of ASR, though PS and PA lead to significant improvement when applied together.

We propose a hybrid voice conversion method which employs a combination of techniques using HMM-based unit selection and spectrum generation. In the proposed method, the HMM-based unit selection selects the most likely unit for the required phoneme context from the target speaker's corpus when candidates of the target unit exist in the corpus. Unit selection is performed based on the sequence of the spectral probability distribution obtained from the adapted HMMs. On the other hand, when a target unit does not exist in a corpus, a target waveform is generated from the adapted HMM sequence by maximizing the spectral likelihood. The proposed method also employs the HMM in which the spectral probability distribution is adjusted to the target prosody using the weight defined by the prosodic probability of each distribution. To show the effectiveness of the proposed method, sound quality and speaker individuality tests were conducted. The results revealed that the proposed method could produce high-quality speech and individuality of the synthesized sound was more similar to the target speaker compared to conventional methods.

This paper introduces a common database, an evaluation framework, and its baseline recognition results for in-car speech recognition, CENSREC-3, as an outcome of the IPSJ-SIG SLP Noisy Speech Recognition Evaluation Working Group. CENSREC-3, which is a sequel to AURORA-2J, has been designed as the evaluation framework of isolated word recognition in real car-driving environments. Speech data were collected using two microphones, a close-talking microphone and a hands-free microphone, under 16 carefully controlled driving conditions, i.e., combinations of three car speeds and six car conditions. CENSREC-3 provides six evaluation environments designed using speech data collected in these conditions.

In this paper, a coefficient-parameter embedding method into Motion-JPEG2000 (MJP2) is proposed for invertible deinterlacing with variable coefficients. Invertible deinterlacing, which the authors have developed before, can be used as a preprocess of frame-based motion picture codec, such as MJP2, for interlaced videos. When the conventional field-interleaving is used instead, comb-tooth artifacts appear around edges of moving objects. On the other hand, the invertible deinterlacing technique allows us to suppress the comb-tooth artifacts and also guaranties recovery of original pictures. As previous works, the authors have developed a variable coefficient scheme with a motion detector, which realizes adaptability to local characteristics of given pictures. However, when this deinterlacing technique is applied to a video codec, coefficient parameters have to be sent to receivers for original picture recovery. This paper proposes a parameter-embedding technique in MJP2 and constructs a standard stream which consists both of picture data and the parameters. The parameters are embedded into the LH₁ component of wavelet transform domain through the ROI (region of interest) function of JPEG2000 without significant loss in the performance of comb-tooth suppression. Some experimental results show the feasibility of our proposed scheme.

We investigated relations between torque and elbow joint angle for constant muscle activations in isovelocity flexion movements of the forearm in three normal subjects. The reference angular velocity was from 0 to 90°/s and the applied torque from 0 to 15% of maximum voluntary contraction. Integrated surface electromyograms (IEMGs) of six muscles, torque, angle and angular velocity of the elbow joint were measured. A mathematical model describing the relationship between these variables was constructed with an artificial neural network. We estimated elbow joint torque by presenting different elbow joint angles, constant IEMGs and constant angular velocity to the model. For elbow joint angles greater than 60°, the slope, which was defined as the rate of torque increase with respect to elbow joint angle, was negative. For elbow joint angles less than 50°, the slope changed from positive to negative when the angular velocity increased. This implied that the flexor muscle-elbow joint system could change from unstable to stable when the angular velocity increased.

This letter proposes a modified Pairwise test case generation algorithm. The proposed algorithm produces additional test cases that may not be covered by Pairwise algorithm due to the dependency between internal modules of software systems. The algorithm produces additional cases utilizing internal module dependencies. The algorithm effectively increases the coverage of testing without significantly increasing the number of test cases.

This paper proposes two efficient rate control algorithms for Motion JPEG2000. Both methods provide accurate visual quality control under buffer constraints. Frames of the same scene usually have the similar rate-distortion (R-D) characters. The proposed methods predict the R-D models of uncoded frames forwardly or bilaterally according to those of coded frames. Experimental results demonstrate that the proposed algorithms offer visual quality improvements over similar competing methods and save a large amount of memory simultaneously.