In 2005, Nandi introduced a class of double-block-length compression functions hπ(x) := (h(x), h(π(x))), where h is a random oracle with an n-bit output and π is a non-cryptographic public permutation. Nandi demonstrated that the collision resistance of hπ is optimal if π has no fixed point in the classical setting. Our study explores the collision resistance of hπ and the Merkle-Damgård hash function using hπ in the quantum random oracle model. Firstly, we reveal that the quantum collision resistance of hπ may not be optimal even if π has no fixed point. If π is an involution, then a colliding pair of inputs can be found for hπ with only O(2n/2) queries by the Grover search. Secondly, we present a sufficient condition on π for the optimal quantum collision resistance of hπ. This condition states that any collision attack needs Ω(22n/3) queries to find a colliding pair of inputs. The proof uses the recent technique of Zhandry’s compressed oracle. Thirdly, we show that the quantum collision resistance of the Merkle-Damgård hash function using hπ can be optimal even if π is an involution. Finally, we discuss the quantum collision resistance of double-block-length compression functions using a block cipher.

As a multi-receiver variant of public key encryption with keyword search (PEKS), broadcast encryption with keyword search (BEKS) has been proposed (Attrapadung et al. at ASIACRYPT 2006/Chatterjee-Mukherjee at INDOCRYPT 2018). Unlike broadcast encryption, no receiver anonymity is considered because the test algorithm takes a set of receivers as input and thus a set of receivers needs to be contained in a ciphertext. In this paper, we propose a generic construction of BEKS from anonymous and weakly robust 3-level hierarchical identity-based encryption (HIBE). The proposed generic construction provides outsider anonymity, where an adversary is allowed to obtain secret keys of outsiders who do not belong to the challenge sets, and provides sublinear-size ciphertext in terms of the number of receivers. Moreover, the proposed construction considers security against chosen-ciphertext attack (CCA) where an adversary is allowed to access a test oracle in the searchable encryption context. The proposed generic construction can be seen as an extension to the Fazio-Perera generic construction of anonymous broadcast encryption (PKC 2012) from anonymous and weakly robust identity-based encryption (IBE) and the Boneh et al. generic construction of PEKS (EUROCRYPT 2004) from anonymous IBE. We run the Fazio-Perera construction employs on the first-level identity and run the Boneh et al. generic construction on the second-level identity, i.e., a keyword is regarded as a second-level identity. The third-level identity is used for providing CCA security by employing one-time signatures. We also introduce weak robustness in the HIBE setting, and demonstrate that the Abdalla et al. generic transformation (TCC 2010/JoC 2018) for providing weak robustness to IBE works for HIBE with an appropriate parameter setting. We also explicitly introduce attractive concrete instantiations of the proposed generic construction from pairings and lattices, respectively.

Diagnosis at an early stage is clinically important for the cure of skin cancer. However, since some skin cancers have similar intuitive characteristics, and dermatologists rely on subjective experience to distinguish skin cancer types, the accuracy is often suboptimal. Recently, the introduction of computer methods in the medical field has better assisted physicians to improve the recognition rate but some challenges still exist. In the face of massive dermoscopic image data, residual network (ResNet) is more suitable for learning feature relationships inside big data because of its deeper network depth. Aiming at the deficiency of ResNet, this paper proposes a multi-region feature extraction and raising dimension matching method, which further improves the utilization rate of medical image features. This method firstly extracted rich and diverse features from multiple regions of the feature map, avoiding the deficiency of traditional residual modules repeatedly extracting features in a few fixed regions. Then, the fused features are strengthened by up-dimensioning the branch path information and stacking it with the main path, which solves the problem that the information of two paths is not ideal after fusion due to different dimensionality. The proposed method is experimented on the International Skin Imaging Collaboration (ISIC) Archive dataset, which contains more than 40,000 images. The results of this work on this dataset and other datasets are evaluated to be improved over networks containing traditional residual modules and some popular networks.

This article reviews the author’s group research achievements in analog/mixed-signal circuit and system area with introduction of how they came up with the ideas. Analog/mixed-signal circuits and systems have to be designed as well-balanced in many aspects, and coming up ideas needs some experiences and discussions with researchers. It is also heavily dependent on researchers. Here, the author’s group own experiences are presented as well as their research motivations.

Despite the increasing use of conversational artificial intelligence (AI) in online discussion environments, few studies explore the application of AI as a facilitator in forming problem-solving debates and influencing opinions in cross-venue scenarios, particularly in diverse and war-ravaged countries. This study aims to investigate the impact of AI on enhancing participant engagement and collaborative problem-solving in online-mediated discussion environments, especially in diverse and heterogeneous discussion settings, such as the five cities in Afghanistan. We seek to assess the extent to which AI participation in online conversations succeeds by examining the depth of discussions and participants' contributions, comparing discussions facilitated by AI with those not facilitated by AI across different venues. The results are discussed with respect to forming and changing opinions with and without AI-mediated communication. The findings indicate that the number of opinions generated in AI-facilitated discussions significantly differs from discussions without AI support. Additionally, statistical analyses reveal quantitative disparities in online discourse sentiments when conversational AI is present compared to when it is absent. These findings contribute to a better understanding of the role of AI-mediated discussions and offer several practical and social implications, paving the way for future developments and improvements.

Public key authenticated encryption with keyword search (PAEKS) has been proposed, where a sender's secret key is required for encryption, and a trapdoor is associated with not only a keyword but also the sender. This setting allows us to prevent information leakage of keyword from trapdoors. Liu et al. (ASIACCS 2022) proposed a generic construction of PAEKS based on word-independent smooth projective hash functions (SPHFs) and PEKS. In this paper, we propose a new generic construction of PAEKS, which is more efficient than Liu et al.'s in the sense that we only use one SPHF, but Liu et al. used two SPHFs. In addition, for consistency we considered a security model that is stronger than Liu et al.'s. Briefly, Liu et al. considered only keywords even though a trapdoor is associated with not only a keyword but also a sender. Thus, a trapdoor associated with a sender should not work against ciphertexts generated by the secret key of another sender, even if the same keyword is associated. That is, in the previous definitions, there is room for a ciphertext to be searchable even though the sender was not specified when the trapdoor is generated, that violates the authenticity of PAKES. Our consistency definition considers a multi-sender setting and captures this case. In addition, for indistinguishability against chosen keyword attack (IND-CKA) and indistinguishability against inside keyword guessing attack (IND-IKGA), we use a stronger security model defined by Qin et al. (ProvSec 2021), where an adversary is allowed to query challenge keywords to the encryption and trapdoor oracles. We also highlight several issues associated with the Liu et al. construction in terms of hash functions, e.g., their construction does not satisfy the consistency that they claimed to hold.

Code search is a task to retrieve the most relevant code given a natural language query. Several recent studies proposed deep learning based methods use multi-encoder model to parse code into multi-field to represent code. These methods enhance the performance of the model by distinguish between similar codes and utilizing a relation matrix to bridge the code and query. However, these models require more computational resources and parameters than single-encoder models. Furthermore, utilizing the relation matrix that solely relies on max-pooling disregards the delivery of word alignment information. To alleviate these problems, we propose a combined alignment model for code search. We concatenate the multi-code fields into one sequence to represent code and use one encoding model to encode code features. Moreover, we transform the relation matrix using trainable vectors to avoid information losses. Then, we combine intra-modal and cross-modal attention to assign the salient words while matching the corresponding code and query. Finally, we apply the attention weight to code/query embedding and compute the cosine similarity. To evaluate the performance of our model, we compare our model with six previous models on two popular datasets. The results show that our model achieves 0.614 and 0.687 Top@1 performance, outperforming the best comparison models by 12.2% and 9.3%, respectively.

Cross-domain data fusion is becoming a key driver in the growth of numerous and diverse applications in the Internet of Things (IoT) era. We have proposed the concept of a new information platform, Geo-Centric Information Platform (GCIP), that enables IoT data fusion based on geolocation, i.e., produces spatio-temporal content (STC), and then provides the STC to users. In this environment, users cannot know in advance “when,” “where,” or “what type” of STC is being generated because the type and timing of STC generation vary dynamically with the diversity of IoT data generated in each geographical area. This makes it difficult to directly search for a specific STC requested by the user using the content identifier (domain name of URI or content name). To solve this problem, a new content discovery method that does not directly specify content identifiers is needed while taking into account (1) spatial and (2) temporal constraints. In our previous study, we proposed a content discovery method that considers only spatial constraints and did not consider temporal constraints. This paper proposes a new content discovery method that matches user requests with content metadata (topic) characteristics while taking into account spatial and temporal constraints. Simulation results show that the proposed method successfully discovers appropriate STC in response to a user request.

This letter introduces a prime-factor Galois field Fourier transform (PF-GFFT) architecture to frequency domain decoding (FDD) of cyclic codes. Firstly, a fast FDD scheme is designed which converts the original single longer Fourier transform to a multi-dimensional smaller transform. Furthermore, a ladder-shift architecture for PF-GFFT is explored to solve the rearrangement problem of input and output data. In this regard, PF-GFFT is considered as a lower order spectral calculation scheme, which has sufficient preponderance in reducing the computational complexity. Simulation results show that PF-GFFT compares favorably with the current general GFFT, simplified-GFFT (S-GFFT), and circular shifts-GFFT (CS-GFFT) algorithms in time-consuming cost, and is nearly an order of magnitude or smaller than them. The superiority is a benefit to improving the decoding speed and has potential application value in decoding cyclic codes with longer code lengths.

In this paper, we investigate the evolution of an optical network architecture and discuss the future direction of research on optical network design and control. We review existing research on optical network design and control and present some open challenges. One of the important open challenges lies in multilayer resource optimization including IT and optical network resources. We propose an adaptive joint optimization method of IT resources and optical spectrum under time-varying traffic demand in optical networks while avoiding an increase in operation cost. We formulate the problem as mixed integer linear programming and then quantitatively evaluate the trade-off relationship between the optimality of reconfiguration and operation cost. We demonstrate that we can achieve sufficient network performance through the adaptive joint optimization while suppressing an increase in operation cost.

The novel optical path routing architecture named flexible waveband routing networks is reviewed in this paper. The nodes adopt a two-stage path routing scheme where wavelength selective switches (WSSs) bundle optical paths and form a small number of path groups and then optical switches without wavelength selectivity route these groups to desired outputs. Substantial hardware scale reduction can be achieved as the scheme enables us to use small scale WSSs, and even more, share a WSS by multiple input cores/fibers through the use of spatially-joint-switching. Furthermore, path groups distributed over multiple bands can be switched by these optical switches and thus the adaptation to multi-band transmission is straightforward. Network-wide numerical simulations and transmission experiments that assume multi-band transmission demonstrate the validity of flexible waveband routing.

Mobility as a Service (MaaS) is a smart mobility model that integrates mobility services to deliver transportation needs through a single interface, offering users flexible and personalizd mobility. This paper presents a structural approach for developing a MaaS system architecture under Autonomous Transportation Systems (ATS), which is a new transition from the Intelligent Transportation Systems (ITS) with emerging technologies. Five primary components, including system elements, user needs, services, functions, and technologies, are defined to represent the system architecture. Based on the components, we introduce three architecture elements: functional architecture, logical architecture and physical architecture. Furthermore, this paper presents an evaluation process, links the architecture elements during the process and develops a three-layer structure for system performance evaluation. The proposed MaaS system architecture design can help the administration make services planning and implement planned services in an organized way, and support further technical deployment of mobility services.

Similarity search for data streams has attracted much attention for information recommendation. In this context, recent leading works regard the latest W items in a data stream as an evolving set and reduce similarity search for data streams to set similarity search. Whereas they consider standard sets composed of items, this paper uniquely studies similarity search for text streams and treats evolving sets whose elements are texts. Specifically, we formulate a new continuous range search problem named the CTS problem (Continuous similarity search for Text Sets). The task of the CTS problem is to find all the text streams from the database whose similarity to the query becomes larger than a threshold ε. It abstracts a scenario in which a user-based recommendation system searches similar users from social networking services. The CTS is important because it allows both the query and the database to change dynamically. We develop a fast pruning-based algorithm for the CTS. Moreover, we discuss how to speed up it with the inverted index.

This paper describes the architectural design, services, and operation and monitoring functions of Science Information NETwork 6 (SINET6), a 400-Gigabit Ethernet-based academic backbone network launched on a nationwide scale in April 2022. In response to the requirements from universities and research institutions, SINET upgraded its world-class network speed, improved its accessibility, enhanced services and security, incorporated 5G mobile functions, and strengthened international connectivity. With fully-meshed connectivity and fast rerouting, it attains nationwide high performance and high reliability. The evaluation results of network performance are also reported.

Beyond 5G is the next generation mobile communication system expected to be used from around 2030. Services in the 2030s will be composed of multiple systems provided by not only the conventional networking industry but also a wide range of industries. However, the current mobile communication system architecture is designed with a focus on networking performance and not oriented to accommodate and optimize potential systems including service management and applications, though total resource optimizations and service level performance enhancement among the systems are required. In this paper, a new concept of the Beyond 5G cross-industry service platform (B5G-XISP) is presented on which multiple systems from different industries are appropriately organized and optimized for service providers. Then, an architecture of the B5G-XISP is proposed based on requirements revealed from issues of current mobile communication systems. The proposed architecture is compared with other architectures along with use cases of an assumed future supply chain business.

In this paper, multi-input multi-output (MIMO) signal detection with random walk along a gradient descent direction using an intermediate search point is presented. As a low complexity MIMO signal detection schemes, a gradient descent algorithm with Metropolis-Hastings (MH) methods has been proposed. Random walk along a gradient descent direction speeds up the MH based search using the gradient of a least-squares cost function. However, the gradient vector may be discarded through QAM constellation quantization in some cases. For further performance improvement, this paper proposes an improved search scheme in which the gradient vector is stored for the next search iteration to generate an intermediate search point. The performance of the proposed scheme improves with higher order modulation symbols as compared with that of a conventional scheme. Numerical results obtained through computer simulation show that a bit error rate (BER) performance improves by 5dB at a BER of 10-3 for 64QAM symbols in a 16×16 MIMO system.

We are given a set S of n points in the Euclidean plane. We assume that S is in general position. A simple polygon P is an empty polygon of S if each vertex of P is a point in S and every point in S is either outside P or a vertex of P. In this paper, we consider the problem of enumerating all the empty polygons of a given point set. To design an efficient enumeration algorithm, we use a reverse search by Avis and Fukuda with child lists. We propose an algorithm that enumerates all the empty polygons of S in O(n2|ε(S)|)-time, where ε(S) is the set of empty polygons of S. Moreover, by applying the same idea to the problem of enumerating surrounding polygons of a given point set S, we propose an enumeration algorithm that enumerates them in O(n2)-delay, while the known algorithm enumerates in O(n2 log n)-delay, where a surroundingpolygon of S is a polygon such that each vertex of the polygon is a point in S and every point in S is either inside the polygon or a vertex of the polygon.

6G research has been extensively conducted by individual organizations as well as pre-competitive joint research initiatives. One of the joint initiatives is the Hexa-X European 6G flagship project. This paper shares the up-to-date deliverables through which Hexa-X is envisioning the 6G era. The Hexa-X deliverables presented in this paper encompass the overall 6G vision, use cases and technical enablers. The latest deliverables on tenets of 6G architectural design and central pillars of technical enablers are presented. In conclusion, the authors encourage joint research and PoC collaboration with Japanese industry, academia and research initiatives for the potential technical enablers presented in this paper, aimed at global harmonization towards 6G standards.

This paper proposes a multiple code block transmission scheme using hierarchical modulation (HM) for a broadcast channel in the orthogonal frequency division multiplexing (OFDM) downlink. We investigate the average bit error rate (BER) performance of two-layer HM using 16 quadrature amplitude modulation (QAM) and three-layer HM using 64QAM in multipath Rayleigh fading channels. In multiple code block transmission using HM, the basic information bits are demodulated and decoded to all users within a cell that satisfy the bit error rate (BER) requirement. Hence, we investigate non-uniform QAM constellations to find one that suppresses the loss in the average BER of the basic information bits for HM to a low level compared to that using the original constellation in which only the basic information bits are transmitted while simultaneously minimizing the loss in the average BER of the secondary and tertiary information bits from the original constellations in which the information bits of the respective layers are transmitted alone. Based on the path loss equations in the Urban Macro and Rural Macro scenarios, we also investigate the maximum distance from a base station (BS) for the information bits of each layer to attain the required average received signal-to-noise power ratio (SNR) that achieves the average BER of 10-3.

Recently, many AI-aided layout design systems are developed to reduce tedious manual intervention based on deep learning. However, most methods focus on a specific generation task. This paper explores a challenging problem to obtain multiple layout design generation (LDG), which generates floor plan or urban plan from a boundary input under a unified framework. One of the main challenges of multiple LDG is to obtain reasonable topological structures of layout generation with irregular boundaries and layout elements for different types of design. This paper formulates the multiple LDG task as an image-to-image translation problem, and proposes a conditional generative adversarial network (GAN), called LDGAN, with adaptive modules. The framework of LDGAN is based on a generator-discriminator architecture, where the generator is integrated with conditional convolution constrained by the boundary input and the attention module with channel and spatial features. Qualitative and quantitative experiments were conducted on the SCUT-AutoALP and RPLAN datasets, and the comparison with the state-of-the-art methods illustrate the effectiveness and superiority of the proposed LDGAN.