マカク類における社会性と寄生虫感染の関連性

京都大学新制・課程博士博士(理学)甲第24875号理博第4985号京都大学大学院理学研究科生物科学専攻(主査)准教授 MacIntosh Andrew, 教授 岡本 宗裕, 教授 明里 宏文学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDFA

Directed Test Suite Augmentation

Test suite augmentation techniques are used in regression testing to identify code elements affected by changes and to generate test cases to cover those elements. Whereas methods and techniques to find affected elements have been extensively researched in regression testing, how to generate new test cases to cover these elements cost-effectively has rarely been studied. It is known that generating test cases is very expensive, so we want to focus on this second step. We believe that reusing existing test cases will help us achieve this task. This research intends to provide a framework for test suite augmentation techniques that will reuse existing test cases to automatically generate new test cases to cover as many affected elements as possible cost-effectively

Monitoring Computer Systems: An Intelligent Approach

Monitoring modern computer systems is increasingly difficult due to their peculiar characteristics. To cope with this situation, the dissertation develops an approach to intelligent monitoring. The resulting model consists of three major designs: representing targets, controlling data collection, and autonomously refining monitoring performance. The model explores a more declarative object-oriented model by introducing virtual objects to dynamically compose abstract representations, while it treats conventional hard-wired hierarchies and predefined object classes as primitive structures. Taking the representational framework as a reasoning bed, the design for controlling mechanisms adopts default reasoning backed up with ordered constraints, so that the amount of data collected, levels of details, semantics, and resolution of observation can be appropriately controlled. The refining mechanisms classify invoked knowledge and update the classified knowledge in terms of the feedback from monitoring. The approach is designed first and then formally specified. Applications of the resulting model are examined and an operational prototype is implemented. Thus the dissertation establishes a basis for an approach to intelligent monitoring, one which would be equipped to deal effectively with the difficulties that arise in monitoring modern computer systems

Investment in plant research and development bears fruit in China

Recent rapid progress in plant science and biotechnology in China demonstrates that China’s stronger support for funding in plant research and development (R&D) has borne fruit. Chinese groups have contributed major advances in a range of fields, such as rice biology, plant hormone and developmental biology, genomics and evolution, plant genetics and epigenetics, as well as plant biotechnology. Strigolactone studies including those identifying its receptor and dissecting its complex structure and signaling are representative of the recent researches from China at the forefront of the field. These advances are attributable in large part to interdisciplinary studies among scientists from plant science, chemistry, bioinformatics, structural biology, and agronomy. The platforms provided by national facilities facilitate this collaboration. As well, efficient restructuring of the top–down organization of state programs and free exploration of scientists’ interests have accelerated achievements by Chinese researchers. Here, we provide a general outline of China’s progress in plant R&D to highlight fields in which Chinese research has made significant contributions

The Asymptotic Behavior of Solutions for a Class of Nonlinear Fractional Difference Equations with Damping Term

Based on generalized Riccati transformation and some inequalities, some oscillation results are established for a class of nonlinear fractional difference equations with damping term. An example is given to illustrate the validity of the established results

Improving spam filtering in enterprise email systems with blockchain-based token incentive mechanism

Spam has caused serious problems for email systems. To address this issue, numerous spam filter algorithms have been developed, all of which require extensive training on labeled spam datasets to obtain the desired filter performance. However, users\u27 privacy concerns and apathy make it difficult to acquire personalized spam data in real-world applications. When it comes to enterprise email systems, the problem worsens because enterprises are extremely sensitive to the possible disclosure of confidential information during the reporting of spam to the cloud. Targeting these obstacles, this study proposes a blockchain-based token incentive mechanism, with the aim of encouraging users to report spam while protecting business secrets and ensuring the transparency of reward rules. The proposed mechanism also enables a decentralized ecosystem for token circulation, fully utilizing the advantages of blockchain technologies. We developed a prototype of the proposed system, on which we conducted a user experiment to verify our design. Results indicate that the proposed incentive mechanism is effective and can raise the probability of spam reporting by more than 1.4 times

Addressing Wealth Inequality Problem in Blockchain-Enabled Knowledge Community with Reputation-Based Incentive Mechanism

An increasing number of online knowledge communities have started incorporating the cut-edge FinTech, such as the tokenbased incentive mechanism running on blockchain, into their ecosystems. However, the improper design of incentive mechanisms may result in reward monopoly, which has been observed to harm the ecosystems of exiting communities. This study is aimed to ensure that the key factors involved in users’ reward distribution can truly reflect their contributions to the community so as to increase the equity of wealth distribution. It is one of the first to comprehensively balance a user’s historical and current contributions in reward distribution, which has not received sufficient attention from extant research. The simulation analysis demonstrates that the proposed solution of amending the existing incentive mechanism by incorporating a refined reputation indicator significantly increases the equity of rewards distribution and effectively enlarges the cost of achieving reward monopoly