We propose “Ohmic-Sticker”, a novel force-to-motion type input device to extend capacitive touch surfaces. It realizes various types of force-sensitive inputs simply by attaching on commercial capacitive touchpads or touchscreens. A simple force-sensitive-resistor (FSR)-based structure enables thin (less than 2 mm) form factors and battery-less operation. The applied force vector is detected as the leakage current from the corresponding touch surface electrodes by using “Ohmic-Touch” technology. Ohmic-Sticker can be used for adding force-sensitive interactions to touch surfaces, such as analog push buttons, the TrackPoint-like pointing devices, and full 6 DoF controllers for navigating virtual spaces. In this paper, we report a series of investigations for the design requirements of Ohmic-Sticker and some prototypes. We also conducted an experiment to evaluate the performance of Ohmic-Sticker as a pointing device.

We propose a novel interaction technique, called Copernican-Touch, that increases touch-input vocabulary by distinguishing between conventional touch (i.e., moving a finger towards a touch surface) and a touch input involving moving a touch surface towards a finger. Using a device motion and a touch input as delimiters, particular short-cut command can be executed immediately after a touch input. Therefore, it does not require a long waiting time before executing a command such as long press or force touch. We conducted an experiment to verify the feasibility of our technique on the smartphones and smartwatches. The result of machine learning shows recognition accuracy of 87% for smartphones and 88% for smartwatches. In accordance with interview comments, such as that it was a little difficult for users to accurately touch the intended position, we discuss potential applications of our technique.

A case study of checking correctness of the National Pension Law by formalizing it in predicate logic and applying automatic theorem proving tool Z3Py is described. Creation of laws has been done traditionally by hand, but in recent years a large number of laws and ordinances have been made, and in order to maintain their quality, it is considered effective to apply computer science, especially technologies cultivated with software engineering and artificial intelligence. In this paper, description of the national pension law in predicate logic and its verification by a SMT solver Z3Py are reported. We found that, despite the document level complexity of the law, its logical depth is not deep and such methods will be effective in making correct and errorless laws.

In this paper, we propose an association ruleA ⇒ correl(X, Y) that handles a correlation function, where A is the prerequisite and correl(X, Y) is the correlation between variables X and Y. With this extension, we can find conditions whose correlation of arbitrary two variables is high (or low) from a given data set. Furthermore, in order to distinguish statistically significant correlation, we define the rule A ⇒ testcorrel(X, Y) which holds the result of the correlation significance test in the conclusion section, where testcorrel(X, Y) is a p-value of no-correlation test between X and Y. In order to confirm the feasibility of the proposed method, a case study using software development data was conducted. We found that it is possible to distinguish projects that are suitable for predicting development effort and those that are not.

Application-level network traffic analysis and sophisticated analysis techniques, such as machine learningand stream data processing for network traffic, require considerable computationalresources.In addition, developing an application protocol analyzer is a tediousand time-consuming task.Therefore, we propose a scalable and flexible traffic analysis platform (SF-TAP) for the efficientand flexible application-level streamanalysis of high-bandwidth network traffic.By using our flexible modular platform, developers can easilyimplement multicore scalable application-level stream analyzers.Furthermore, as SF-TAP is horizontally scalable, it manageshigh-bandwidth network traffic.To achieve this scalability, we separate the network trafficbased on traffic flows, and forward the separated flows to multipleSF-TAP cells, each comprising a traffic capturer andapplication-level analyzers.This study discusses the design, implementation and detailed evaluation of SF-TAP.