For creating presentation slides, in which visual expressions are emphasized, WYSIWYG editors, such as PowerPoint, are preferred because they provide immediate feedback on fine layout adjustments. In contrast, for typesetting documents, typesetting systems that enable us to program object rendering and placement in a high-level manner are more effective. Although programming environments for high-level interactive typesetting are desirable for leveraging their advantages in slide creation, such environments are, unfortunately, not well developed. In this work, we present SATYSFI NOTEBOOK by extending the typesetting system SATYSFI, which is based on a functional programming language, to support incremental evaluation and by integrating it into the interactive programming environment JupyterLab. SATYSFI NOTEBOOK enables the incremental creation of slide decks while interactively typesetting and previewing slides represented as high-level program fragments. In this paper, we provide the design and implementation of SATYSFI NOTEBOOK, along with observations obtained during its development.

Let n and k be positive integers. We define a quadratic digraph G+(-)(2, k, n) over the residue classes of n where the vertex set of G+(-)(2, k, n) is the set of complete residue class of all integers when divided by n, {0, 1, 2,..., n-1} and (u, v) is a directed edge of G+(-)(2, k, n) from a vertex u to a vertex v if u2 ≡ v + (-)k (mod n). G+(-)(2, k, n) is called the k-almost (k-nearly) quadratic digraph. When k=1, G+(-)(2, 1, n) is also called the almost (nearly) quadratic digraph. Let p be an odd prime. We consider the fixed points of a quadratic digraph G+(-)(2, k, p). Depending on the remainder when p is divided by certain prime numbers, we obtain the number of fixed points of k-almost and k-nearly quadratic digraph where k ∈ {1, 2, 3}.

One of the success factors of business process outsourcing (BPO) is a comprehensive and in-depth understanding of the business processes that are outsourced. However, such business processes are often undocumented, and discovering them is difficult and time-consuming for BPO service providers. Previously, we introduced an approach for business process discovery that uses swim lanes to recognize that different parts of the process may be performed by different parts of an organization. It generates the business process from an event log and user information extracted from an existing system. This paper examines whether the approach aids the engineers and consultants of the providers who need to investigate business processes of organizations (i.e., their customers of which they do not have sufficient knowledge) discovering the undocumented business processes of the target organization. To do so, we surveyed an industrial workflow system from which we collected data about 2,000 events and 269 users for a two-year period of the system's operation. We conducted a study on the case through document analysis and expert interviews. Our evaluation showed that 46% of the process patterns were undocumented, and 36% of these were invalid patterns. The approach is a valuable process visualization for identifying knowledge that is not documented nor recognized even by experts in organizations.

Power and energy consumption are becoming the most important restrictions on driving computer systems. Especially, HPC systems still require more performance despite their limited power supply, and it is necessary to explore methodologies to enhance their performance within this limitation. Approximate computing (AC) is a promising technique for optimizing the trade-offs among application execution performance, application output correctness, and power consumption during execution. However, applying AC sometimes causes unexpected effects on the output and performance due to cache behavior, compiler optimization, and so on. This paper discusses dynamic approximate computing methods, which enable changing data precision in applications at runtime, for more flexible and effective approximate computing (AC). This paper also evaluates the benefits and drawbacks of dynamic AC with some high-performance computing (HPC) applications and workloads.

Modeling multiple-choice behavior is an important research topic in the field of social sciences, including consumer behavior research. A model that has been studied for a long time is the multinomial logit model; however, it has been shown to have problems, such as the need to set different parameters for each choice used as the objective variable. Furthermore, the number of parameters increases exponentially as the number of choices considered in the model increases. This results in unstable parameter estimates and makes variable selection difficult. In particular, when using discrete variables consisting of many categories as explanatory variables, it is necessary to set dummy variables for each category, and the effect of multicollinearity may further destabilize parameter estimates. To address these issues, we focused on cases where explanatory variables are composed of discrete variables and converted the categories contained in the discrete variables into numerical variables using the Weight of Evidence. Furthermore, we attempted to reduce the number of parameters in the model. In addition, by including only variables having a strong causal relationship with choice behavior based on the Information Value and correlation coefficients to the variable list, we proposed improvements to the model to simplify variable selection in the multinomial logit model. We then report the results of applying conventional methods and the method proposed in this study to real data, demonstrating the effectiveness of the proposed method.

Multi-signatures are protocols used when multiple signers wish to produce a joint signature on the same message. They are principally used in blockchains. In this paper, we propose a multi-signature by extending the signature Commutative Supersingular Isogeny based Fiat-Shamir (CSI-FiSh) with Sharing-friendly Keys (CSI-SharK) signature scheme to a multi-signature. We use a non-interactive zero-knowledge proof system to make sure the signers make the required computations. Both the Key Aggregation and MultiSigning use a sub-protocol to allow signers to aggregate elliptic curves in a round-robin manner. We prove the resulting multi-signature protocol is actively secure in the random oracle model (ROM) by using the Double Forking Lemma Technique. We compare the resulting scheme to the most efficient isogeny-based threshold protocol and show that while our protocol lacks the robustness property, the multi-signature is more advantageous in a situation where a group of signers would want to recurrently output signatures. We also compare our multi-signature to two state of the art lattice-based multi-signatures, and show that by carefully choosing the parameters, our multi-signature is smaller by a significant factor. Finally, we implement our multi-signature scheme using C.

The global outbreak of COVID-19 has rapidly increased the use of video conferencing systems, highlighting the importance of end-to-end encryption (E2EE) technology for protecting user privacy. This paper analyzes the security of SFrame, an E2EE technology used in Cisco Webex and similar systems. Specifically, we assess the security of SFrame as described in two versions published by the IETF: an older version known as draft-omara-sframe-01 and the latest version at the time of writing this paper, draft-ietf-sframe-enc-03. The draft-omara-sframe-01 had signature vulnerabilities pointed out by Isobe et al., and the draft-ietf-sframe-enc-03 includes updates addressing these issues. First, we analyze the older version of SFrame, draft-omara-sframe-01, and propose new attacks that allows us to manipulate more plaintext than the attacks identified by Isobe et al. Next, we study the latest version, draft-ietf-sframe-enc-03, showing that many of the attacks proposed by Isobe et al. and our new attacks are still effective against this latest version, even when it uses the same signature process as the older version.

Science, technology, engineering and mathematics (STEM) is an emerging field of research within early childhood education and care across the world. It aligns with approaches to support early learning and skill development, given the recognition of the importance of the first five years of life. In this study we explored the framework documents in Australian early childhood education to understand more about STEM in early childhood education and care. Our study is interested in the frequency of STEM, as well as the meanings associated with STEM with regards to child learning. We engage with a content analysis, looking at latent as well as manifest coding. Key themes emerge associated with the absence of some STEM areas, compared to others, as well as the positioning of STEM learning areas. More specifically, digital technologies dominate the other three disciplines of STEM. It is anticipated that by providing policy understanding, conversations can commence to support the implementation of STEM in early childhood education and care.

Parents and guardians were supporting their children's learning prior to Covid-19, but evidence has indicated that many were not prepared for what happened and what was required of them during the Covid-19 period. Uses of digital technologies to ensure continuity of learning was frequently and rapidly used and developed, and pertinent literature often indicated the challenges that parents and guardians found in supporting their children through uses of these media. In moving from the previous practices to those needed in the Covid-19 pandemic time, this paper asks why parents and guardians were not prepared: what features were missing, and how might parents and guardians be better supported during periods of future crisis?

Enterprises have focused much of their attention on consortium blockchains, in which multiple authorized organizations participate to form a consortium, in contrast to public blockchains, which consist of unspecified participants. Since a system using a blockchain is based on participants providing/using resources such as nodes to each other, a mechanism to motivate participants to provide resources is important. Typically, a public blockchain realizes an incentive mechanism for providing nodes by unspecified participants through mining rewards and transaction fees associated with a consensus algorithm such as PoW on the platform layer. On the other hand, a consortium blockchain usually does not have an incentive mechanism in the platform itself. In order to maintain and operate a consortium, it is essential that participating organizations provide resources or pay the costs of providing resources. However, because participating organizations use different percentages of the resources, a uniform fee could create inequalities or unfair situations among organizations. Therefore, it is necessary to manage billing to remove the gap between the costs borne and the actual usage or/and the unfairness among participants in the consortium. This research aims to realize a billing management method for consortium blockchain-based systems. We propose a smart contract-based service billing management mechanism named “BillingOpsSC” to ensure cross-organizational transparency for billing calculation and management. Furthermore, to ensure fairness among participants, we design a billing calculation model based on metering of the “contribution” by each organization such as providing resources, and the system “usage” by each organization, in the consortium. We implement a prototype of the proposed method including the billing management mechanism and calculation model for Hyperledger Fabric, which is one of the major consortium blockchains, and evaluate the method using the prototype. The results show that our proposed method is effective in ensuring transparency and fairness in billing management among multiple organizations, and in terms of performance is practical enough to be used in making monthly billing calculations.