Socially-enabled digital technologies have attracted academic interest for decades, with recent commercial examples of Siri and Alexa, capturing public attention. However, despite ubiquitous visions of a robotic future, very few fully-fledged social robots are currently available to consumers. To improve their designs, studies of their long-term use are particularly valuable, but are currently unavailable. To address this gap, we report on interviews with four long-term users of Pepper - a social robot introduced in 2014. Our thematic analysis elicited insights across three kinds of value Pepper brought to its users: utilitarian functionality; the community that formed around Pepper; and a personal value of affection. We focus on two contributions those values bring to social robot design: social robots as social proxies, alleviating disabilities or acting akin to social media profiles; and robot nurturing as a design construct, going beyond purely utilitarian or hedonistic perspectives on robots.

This paper addresses a multi-lingual enhanced Rapid Serial Visual Presentation (RSVP) system “MulLinR”, which clears up language-specific problems of previous RSVP tools, which do not support language which are written continuously (non-spaced) and spelled with non-alphabetic characters. We develop a prototype system, which currently supports Japanese and Chinese, and experiment with variation of presentation time intervals. We have experiments as a feasibility study and discuss usability.

The process of performance tuning is time consuming and costly even if it is carried out automatically. It is crucial to learn from the experience of experts. Our long-term goal is to construct a database of facts extracted from specific performance tuning histories of computation-intensive applications such that we can search the database for promising optimization patterns that fit a given kernel.

Modern concurrent copying garbage collection (GC), in particular, real-time GC, uses fine-grained synchronizations with a mutator, which is the application program that mutates memory, when it moves objects in its copy phase. It resolves a data race using a concurrent copying protocol, which is implemented as interactions between the collector threads and the read and write barriers that the mutator threads execute. The behavioral effects of the concurrent copying protocol rely on the memory model of the CPUs and the programming languages in which the GC is implemented. It is difficult, however, to formally investigate the behavioral properties of concurrent copying protocols against various memory models. To address this problem, we studied the feasibility of the bounded model checking of concurrent copying protocols with memory models. We investigated a correctness-related behavioral property of copying protocols of various concurrent copying GC algorithms, including real-time GC Stopless, Clover, Chicken, Staccato, and Schism against six memory models, total store ordering (TSO), partial store ordering (PSO), relaxed memory ordering (RMO), and their variants, in addition to sequential consistency (SC) using bounded model checking. For each combination of a protocol and memory model, we conducted model checking with a model of a mutator. In this wide range of case studies, we found faults in two GC algorithms, one of which is relevant to the memory model. We fixed these faults with the great help of counterexamples. We also modified some protocols so that they work under some memory models weaker than those for which the original protocols were designed, and checked them using model checking. We believe that bounded model checking is a feasible approach to investigate behavioral properties of concurrent copying protocols under weak memory models.

Not only knowledge such as the grammar but also practical programming experiences are important to the learning of the programming language. In this paper, we classify programming exercises into the following two types: 1) syntax practices for understanding the grammar and 2) semantics practices for understanding the flow of a program, and then we develop a web-base application that automatically generates programming exercises by using templates and PHP language.We also confirm the effectiveness of the system by our preliminary experiments.

This paper presents a text mining analysis as a part of evaluation for healthcare support system, which is designed and developed from view of previous research results and problems. The system is an e-mail text-based communication system independent with sorts of terminals, based on mailing-list system and approved various communications by one-stop account. The system offers users' availability for checking their own data which is reflected by every day's reply data, and daily mails have many variation because they are not automatically sent but nurses writes and sends every day, which let e-mails not routinely but humane and improved. We have validated the system by the operation test, where we have evaluated and discussed the results.

We present a personal sport skill identification using time series motion picture data, focused on volleyball. We do not use body nor skeleton model, but use only hi-speed motion pictures, from which time series data are obtained and analyzed using data mining methods such as Naive Bayes Tree or C4.5 decision-tree learning algorithm. We identify internal models for technical skills as evaluation skillfulness for volleyball attacks, and discuss mono and meta-functional skills for improving skills.

To improve performance of large-scale scientific applications, scientists or tuning experts make various empirical attempts to change compiler options, program parameters or even the syntactic structure of programs. Those attempts followed by performance evaluation are repeated until satisfactory results are obtained. The task of performance tuning requires a great deal of time and effort. On account of combinatorial explosion of possible attempts, scientists/tuning experts have a tendency to make decisions on what to be explored just based on their intuition or good sense of tuning. We advocate evidence-based performance tuning (EBT) that facilitates the use of database of facts extracted from tuning histories of applications to guide the exploration of the search space. However, in general, performance tuning is conducted as transient tasks without version control systems. Tuning histories may lack explicit facts about what kind of program transformation contributed to the better performance or even about the chronological order of the source code snapshots. For reconstructing the missing information, we employ a state-of-the-art fine-grained change pattern identification tool for inferring applied transformation patterns only from an unordered set of source code snapshots. The extracted facts are intended to be stored and queried for further data mining. This paper reports on experiments of tuning pattern identification followed by predictive model construction conducted for a few scientific applications tuned for the K supercomputer.

It is not easy to acquire nursing techniques from lectures only, but research on transforming a tacit knowledge of nursing techniques into a formal knowledge has started recently. In this paper, we analyze the coordinate information of hand motion data in an intravenous injection, and discuss on the possibility of formulating information.

We present a sport skill classification using time series motion picture data, focused on table tennis. We do not use body nor skeleton model, but use only hi-speed motion pictures, from which time series data are obtained and analyzed using data mining methods such as C4.5 and so on. We identify internal models for technical skills as evaluation skillfulness for forehand stroke of table tennis, and discuss mono and meta-functional skills for improving skills.

This paper addresses an e-health support system based on mobile communication in universities, which is designed and developed from view of previous research results and problems. The system is a text-based mail communication system independent with the types of terminals, based on mailing-list system and approved various communications by one-stop account. The system offers users' availability for checking their own data which is reflected by every day's reply data, and daily mails have many variation because they are not automatically sent but nurses writes and sends every day, which let mails not routinely but humane and improved. We have validated the system by the field test, where we have got many important data and discussion.

We present a time series data analysis for sport skill using data mining methods from motion pictures, focused on table tennis. We do not use body model, but use only hi-speed motion pictures, from which time series data are obtained and analyzed using data mining methods such as C4.5 and so on. We identify internal models for technical skills as evaluation skillfulness for forehand stroke of table tennis, and discuss mono and meta-functional skills for improving skills.

This paper presents mobile application framework such as Web/mail applications, for health ware education, based on framework known as MVC. In our study, one M and one C are prepared and several Vs are developed for each interface as Web, e-mails, and so on. We show some source codes and discuss the environment.

P-Bus, a new programming interface layer for safe kernel extensions is proposed. P-Bus introduces a new programming interface on top of the Linux kernel in order to give formal specifications to the interface, and to improve portability of extensions. New extensions, called P-Components, are verified with a model checker MKencha to see whether a component is compliant with rules which should be obeyed to implement extensions properly. A network driver has been implemented as a P-Component and verified with MKencha. MKencha has found two bugs in the component.

Virtual machine monitors (VMMs) have emerged as potential tools %% are one of the promising approaches for implementing security mechanisms to enhance the security and/or reliability of software systems. There are two approaches to implementing VMMs. One is a software-based approach that emulates the execution of virtual machines via software. The other is a hardware-based approach that utilizes the hardware virtualization support of CPUs. The software-based approach is preferred for implementing security mechanisms, whereas the hardware-based approach is preferred from the viewpoint of performance. In this paper, we present an approach to implementing a hybrid VMM for flexible and efficient security mechanisms. The hybrid VMM consists of a software-based VMM (QEMU) and hardware-based VMM (KVM), and it dynamically switches between them. Using the hybrid VMM, security- and reliability-critical software can be executed on the software-based VMM, and performance-critical software can be executed on the hardware-based VMM. We also present the results of experiments conducted to evaluate the performance and verify the effectiveness of the hybrid VMM.

In this paper, we discuss sport technique evaluation using motion analysis model by neural networks and data mining methods. For students of university, we recorded the continuous forehand stroke of the table tennis in the video frames, and analyzed the trajectory pattern of nine marking points attached at subject's body with a coach's technique evaluation and the motion analysis model. As a result, we obtained some technique rules classified member of table tennis club, middle level player and beginner as fuzzy rules, and also estimated the movement of the marking points to improve in table tennis technique.

This paper introduces a new dependable operating system project, called DEOS, started in 2006, and scheduled to continue for six years. In this project, a safety extension mechanism called P-Bus is to be designed, and implemented in the Linux kernel so that a future dependability attribute is implemented with P-Bus. A hardware abstraction layer, called SPUMONE, is introduced so that a light-weight operating system, called ArcOS, and a monitoring service on top of ArcOS monitors the Linux kernel to provide a safety-net for the Linux kernel. New dependability metrics are being designed to enable developers and users to decide which hardware or software solution meets their dependability requirements, and thus can be used.

We present an e-mail-based education system using mobile phones. This system consists of: attendance management subsystem, attendance history management subsystem, short examination subsystem, questionnaire subsystem, and assignment delivery subsystem. Both students and teachers mainly use only e-mail functions and it can access the serve. This system can be used regardless of terminal models only if mails that can be sent and received through the Internet. In this paper, the outline of this system is described, and the functions and effects are discussed.

This paper addresses a pet-type welfare robot system for aged people. The robot offers interactivity, which can communicate autonomously and communicate with others using Internet-connectivity, for being a partner. To avoid being satiated with conversation, we propose interactive operatability, especially focused conversation contents. In order to watch over aged people through Internet, we have furthermore developed auto-detection alert system for aged people by checking user logs, which is also reconfigurable. Index Terms-Reconfigurable System, Pet-type Robot, Rehabilitation Engineering, Human Computer Interaction

We propose a dynamic test compaction procedure to generate high-quality test patterns for path delay faults. While the proposed procedure generates a compact two-pattern test set for paths selected by a path selection criterion, the generated test set would detect not only faults on the selected paths but also faults on many unselected paths. Hence both high test quality by detecting untargeted faults and test cost reduction by reducing test patterns can be achieved. Experimental results show that the proposed procedure could generate a compact test set that detect many untargeted path delay faults certainly, compared with the static test compaction method previously proposed (Kajihara et al., 2005).

The progress of design and fabrication technologies has led to an increase in small delay failures in systems-on-a-chip. To evaluate the delay testing quality accurately, the authors have already proposed a statistical approach that calculates actual sensitized path lengths that detect small delay defects in the transition delay test. However, the calculation requires a huge amount of CPU time. This paper presents a much more efficient method to calculate the sensitized longest path lengths and experimental results regarding CPU time and accuracy. The experiments show that this calculation method has high speed and high accuracy

This paper presents a framework of high-quality test generation for transition faults in full scan circuits. This work assumes a restricted broad-side testing as a test application method for two-pattern tests where control of primary inputs and observation of primary outputs are restricted. Because we use a modified time expansion model of a circuit-under-test during ATPG and fault simulation, conventional ATPG and fault simulation programs can work with minor change. The proposed ATPG method consists of two algorithms, which are activation-first and propagation-first, and for each fault it is decided which algorithm should be applied. Test patterns are generated such that transition faults with small delay can be detected, i.e. a path for fault excitation and propagation becomes as long as possible. In experimental results we evaluate test patterns generated by the proposed method using SDQM that calculates delay test quality, and show the effectiveness of the proposed method

This paper addresses a pet-type welfare robot system for aged people. The robot offers interactivity, which can communicate autonomously and communicate with others using Internet-connectivity, for being a partner. To avoid being satiated with conversation, we propose reconfigurability of interactivity, especially focused conversation contents. In order to watch over aged people through Internet, we have furthermore developed auto-detection alert system for aged people by checking user logs, which is also reconfigurable

TAM (topographic attentive mapping) network is a biologically-motivated neural network with receptive fields of Gabor function. However, the receptive field's layer is monotype, and there is a lack of performance for rotating visual images. In this paper, we formulate four TAM networks with multilayer structure of extensive receptive fields. We discuss their performance and show the usefulness of TAM network using some examples of character recognition.

In this paper we introduce a quality model that reflects fabrication process quality, design delay margin, and test timing accuracy. The model provides a measure that can predict the level of chip defects that cause delay failure, including marginal delay. We can therefore use the model to make test vectors that are effective in terms of both testing cost and chip quality. The results of experiments using ISCAS89 benchmark data and some large industrial design data reflect various characteristics of our statistical delay quality model.

In this paper we propose a test compaction method for path delay faults in a logic circuit. The method generates a compact set of two-pattern tests for faults on long paths selected with a criterion. While the proposed method generates each two-pattern test for more than one fault in the target fault list as well as ordinary test compaction methods, secondary target faults are selected from the fault list such that many other faults, which may not be included in the fault list, are detected by the test pattern. Even if faults on long paths in a manufactured circuit are not included in the fault list due to a process variation or noise, the compact test set would detect the longer untargeted faults, i.e., the test set has a noise or variation tolerant nature. Experimental results show that the proposed method can generate a compact test set and it detects longer untargeted path delay faults efficiently.

The quality of delay testing focused on small delay defects is not clear when traditional fault models are used. We therefore evaluated the feasibility of using the statistical delay quality model (SDQM) - which reflects fabrication process quality, design delay quality, test timing accuracy, and test pattern quality - by using a commercial automatic test program generation (ATPG) tool to apply it to a large data set. The SDQM can also provide a measure predicting the defect level of a chip, and by simulating test patterns we show experimentally here that this measure can be calculated within a reasonable CPU time when using a reasonable amount of memory. Because we found when using SDF information to calculate path lengths accurately that the transition test patterns are not good at detecting small delay defects in long paths, a new test algorithm that detects small delay defects should be developed

I/sub DDQ/ testing is an effective method for bridging faults of CMOS circuits. Since the measurement of current in I/sub DDQ/ testing takes a long time, a short test sequence is strongly desirable for reducing test application time. In this paper we present a test compaction method for an I/sub DDQ/ test sequence using a reassignment method for all bridging faults in sequential circuits. Since a large memory space is required to treat all bridging faults, an effective fault list is required. We propose the test compaction method using an assignment list of signal values. The proposed method is realized with small size memory and runs fast for many large sequential circuits. Experimental results on the benchmark circuits show that it is effective in reducing test length for given weighted random sequences.

In this paper we propose a new method to detect resistive bridging faults by logic testing considering fault effects that depend on the gate threshold voltage and gate input vectors. First we show that some bridging faults can be missed to be detected by the traditional test generation method which generates O and 1 at the bridging signal lines, and then propose a novel method to detect resistive bridging faults by logic testing method, which is complete in the sense that the undetectable resistive bridging fault by this algorithm gives correct result in logical operation. A heuristic method using a random pattern has also been proposed for experimental purpose. In order to show the effectiveness of the proposed method some experimental results for benchmark circuits have been shown.

Fuzzy control is an effective method widely employed in the complex control field. However, in the fuzzy control, the adjustment (tuning) of the shape of membership functions and the acquisition of fuzzy rules is still a very active research field. To solve the tuning problem, a number of fusion/union methods using neural networks (NN) or genetic algorithms (GA) have been proposed. By scanning through these methods, we find that these methods are roughly divided into some categories depending on the grade of fusion/union between fuzzy models and NN, GA. In this papers, the fusion/union models are discussed and their applications in the field of control are explained.