Reviewerly/exHarmony huggingface dataset:
Feeling Through Technology

Abstract This chapter aims to encapsulate the core elements of the keynote presentation on experience and interaction designs, primarily those using augmented reality, virtuality, or a mix of physical and digital elements. My interest is not in creating cutting-edge technology, but rather in seeing how people react, engage, think, move, and feel when they engage with designs by myself and colleagues. The contribution I make is to use performance theories and practices in design, especially design for mixed reality experiences, so that I can bring specific tools to bear on the creation and analysis of those designs. ‘Performance’ can be the kind practiced by professionals. It can also be the behaviours of people who take on the role of audience member or bystander. It can also be ‘performance’ in the ways that people ‘perform’ their everyday lives. Performance often aims to be thought-provoking, but (aside from Bertolt Brecht and those who use his politically minded Verfremdungseffekt ) it virtually always aims for an emotional response through engagement with the aesthetic choices that have been made. This chapter provides a basic theoretical grounding and a specific example of how performance can lay out a richer design space for personally meaningful experiences.
Designer and AR Technology: The Relationships Between the User and Virtual

Abstract A good communication strategy of an artefact must connect a multitude of elements, both in terms of content and shape, and make them become a vehicle between the company and the consumer. The proposed contribution, resulting from the “Meta 4.0” research, suggests an exploration of innovative methodologies, tools and technologies to communicate and sell a product. In the context of the Industry 4.0 aims, the proposal is that technologies associated with the virtualisation of scenarios and products - augmented and virtual reality - can be useful tools and possibilities for achieving the required aim. In fact, the adoption of augmented and virtual reality technology in the context of communication would facilitate cognitive processing on the part of buyers, making them more interested in a product. The contribution explores the practice of vision through transformative technologies as a relational, cognitive and sensory expertise, attributing to the designer the role of interlocutor in the dimension of the visual imaginary in the duality between virtual and real. Therefore, designing the virtual in an incessant desire to find innovative experiential dimensions with the media, to make visible the centrality of the individual in the relationship between subject and transformative technology. The practice of vision refers to the actual conditions of viewing, including the social conditions of perception, which are the subject of anthropological research. The aim is to present the basis of a theorised language that defines possible intervention scenarios for the figure of the designer within the design of the intangible image.
Space as a Narrative Interface. Phygital Interactive Storytelling in the Field of Cultural Heritage

Abstract The paper explores the evolution of interaction design and digital communication – with a focus on the phygital space and the enhancement of people experience – both from the theoretical as well as a design point of view, based on a phenomenological and critical mapping of recent and paradigmatic case studies. In doing that, it introduces, presents, and discuss the possible role played by the phygital space as a narrative device exploring possible combinatons – space, narrationa and technologies – of space-based, multimodal storytelling mediated by blended experiences and devices.
Provocation Through Narratives: New Speculative Design Tools for Human-Non-Human Collaborations

Abstract In a complex and changing world, design is called to act to nurture and provoke critical reflections regarding wicked, complex, and interconnected issues, becoming a sensemaking agent that, exploiting its speculative methods, uses narratives as an inquiry tool, as a co-design tool, and as a provocative tool. Through the presentation and analysis of a provotype designed by the authors, the research aims to define new speculative tools for human-non-human collaborations and highlight how design narratives may be involved within more-than-human discourses.
Envisioning Technological Artefacts Through Anticipatory Scenarios and Diegetic Prototypes

Abstract Facing global challenges and managing technological and scientific development require to imply critical reflection at all levels of transformation to create more thriving societies. This paper addresses the issues behind designing in complex societies. It introduces a novel approach to generate scenarios, envision, and contextualise the not-yet-existing technological artefacts through storytelling and prototyping, to anticipate the possible ethical and societal implications of technological development and mediations in social-human-environment-technology assemblages and interactions. The authors describe the critical approach with the Protocol for designing consciously and an Envisioning tool exploiting the Science Fiction (Sci-Fi) films as a trigger for critical discussion among the design researchers and practitioners. The Protocol and Envisioning tool aim at supporting the design researchers and practitioners adopt pluriversal perspectives and deal with the complexity, to deliver consciously designed artefacts. In this paper, authors show how the critical approach can be implemented in design and research projects and discuss the benefits and purposes of introducing such an approach in the current design research and practice.
Beyond Visualisation Data as Raw Material for Uncoded Experiences

Abstract In the context of our evolving data-driven society, controlling the current abundance of data and the resulting flow of information does not circumscribe actions from disciplinary boundaries. Many recent theories factually underline this fact contributing significantly to the definition of valuable tools, methodologies, and processes. Numerous cross-disciplinary contributions support an ever-expanding field of knowledge in its many applications, the benefits of which are evident from an economic, social and cultural perspective. Furthermore, they seem to reveal the potential of a material transformation of data: re-materialising data, giving it physical shape and staging it in public spaces to create more emphatic relationships. This plastic experience would make people feel the data, not just watch and observe it. The paper proposes an analytical framework, helpful in exploring the opportunities offered by data design: what technological innovations make the development of new data communication languages possible? What spatial dimension does the experience provide? What value, what meaning do they bring? The framework offered here intends to be a thinking tool and inspire renewed data interaction design practices. A better understanding of what interaction in data design is, and how it can enrich the quality of interaction in data-informed product-service systems which empower those who use them. The goal is to open up the dialogue amongst parties interested in making the human explicit in the data ecosystem.
ECONOMICALLY EFFICIENT CACHE FRIENDLY ADJACENCY LIST FOR GRAPH PROCESSING ALGORITHMS

Graphs are a fundamental part of computer science and various scientific fields. They are used in numerous applications, from social networks to electronic design automation. Efficient graph representation is important for modern algorithms, especially in economical contexts, where resource-efficient implementations play a significant role by reducing the resource consumption. This is essential in environments where computing resources are a high priority. There are many representations of graphs as data structure. One of these types is adjacency list: it is collection of linked lists which shows the connection of source and destination vertices. Adjacency lists are more memory-efficient than adjacency matrices because they only allocate memory for vertices with at least one edge in the graph. However, traditional implementations of adjacency lists do not fully use the features provided by modern CPUs, such as the cache line. Our design of Adjacency List is cache friendly and is keeping the main structure of traditional implementation. The main idea is derived from C#’s dictionary implementation for hash tables, which uses one array combining all data that should be in linked lists. Our results show that cache friendly implementation of Adjacency list outperforms it in lookup and insertion operations.
The Critical Forms of Design Futures Scenarios: Introducing Unconventional Ways of Scenarios Making

Abstract This paper discusses the critical forms of design futures scenarios; these forms aim at debating, interrogating, and questioning future visions rather than extrapolating on the status quo. They aim to problematize future issues in order to enact social change and mitigate the consequences and implications of today’s actions and decisions.
Everyday Design: The Aesthetic Dimension of Alternative Use

Abstract The Functional Account of Design Aesthetic Appreciation (FADAA), a recent position on design in analytic aesthetics, attempts to establish a sui generis aesthetic theory of design that is somehow distinct from that of the fine arts. This account recognizes that, in evaluating the aesthetic dimension of design, not only form but also function and use are critical variables. However, FAADA has yet to question the status of being a user—usership—as well as the aesthetic strategies we use in our everyday interactions with designed objects. I will look into the possibility of broadening the FADAA debate on design appreciation by (1) acknowledging the role of the perceiving subject in interacting with design objects and (2) including instances of alternative use as possible critical use practices without diminishing the aesthetic significance of function. To this end, I will introduce the concept of “everyday design,” which refers to an interpretative act by the user that generates an excess of function in relation to the context of use and the user itself.
Human-AI System Co-creativity to Build Interactive Digital Narratives

Abstract The interactive digital narrative (IDN) is an interdisciplinary field connected to narrative studies, design, human-computer interaction, and gaming. In this contribution, IDN is investigated from the designer’s perspective; it deals with the use of prolific artificial intelligence (AI) support systems in this area, highlighting the need to examine their potential. However, the features and essential components of the AI support system are not systematically categorised. This paper fills the aforementioned gap by providing a literature review of twenty academic contributions that make it possible to identify the types and categories of AI support systems, narrative elements, and types of creativity. The study is conducted keeping at the centre the relationship of collaboration between the human and the AI system concerning the production of narratives. As the main contribution to knowledge, the literature review identifies the problems and the gaps and underlines future research directions.
Peningkatan Hasil Belajar IPS Materi Perjuangan Para Tokoh Pejuang Pada Masa Penjajahan Belanda Dan Jepang Melalui Model Jigsaw

Based on the results of studying Social Sciences (IPS) class V SDI An Nuriyah Jagakarsa Concerning the Struggle of Warrior Figures During the Dutch and Japanese Colonial Period who still had not reached the specified KKM, namely 70. Of the 35 students, only 11 people (31.42%) were able to This is why research on improving social studies learning was carried out regarding improving social studies learning outcomes regarding the struggle of warrior figures during the Dutch and Japanese colonial period through jigsaw type cooperative learning. The aim of this assessment is to improve students' social studies learning outcomes regarding the struggle of warrior figures in during the Dutch and Japanese colonial period through jigsaw type cooperative learning. This research uses Classroom Action Research with a cycle system consisting of planning, implementation, observation and reflection. Based on the research results, it shows that students' learning completeness in each cycle has increased, this is shown in the pre-cycle students whose learning completeness was above KKM 70 was only 31.42%, in cycle 1 it increased to 62.86%, in cycle 2 it increased to 94.28%. Thus it can be concluded that the jigsaw type cooperative learning model can improve learning outcomes student.
Guided Image Filtering: A Survey and Evaluation Study

In the past decade, there has been an increasing success of guided image filtering (GIF). Leveraging the guidance image as a prior and transferring the structural details to the target image, GIF has demonstrated its ability in faithfully preserving image edges while maintaining low computational complexity. Additionally, GIF exhibits good capability in extracting and characterizing images from various domains. Researchers have proposed large numbers of GIF-like variants. Nevertheless, limited effort has been devoted to a systematic review and evaluation of these methods. To fill this gap, this paper provides a comprehensive survey of existing GIF-like methods, including model- and deep learning-based approaches. Moreover, extensive experiments are conducted to compare the performance of 18 representative methods. Analysis of the qualitative and quantitative results reveals several observations concerning the current state of this area.
PeaceTech Futures

This chapter assesses ‘where PeaceTech’ is, in terms of hype, disillusionment and a plateau of steady-state use. In conclusion a small manifesto for PeaceTech’s future is offered.
Capturing Performance and Privacy by Assembling Avengers of Online Advertising

This paper presents our solution for the ACM RecSys Challenge ’23 (http://www.recsyschallenge.com/2023/) organized by ShareChat, focusing on the domain of online advertising. The goal was to predict the install probability of advertisements, addressing the problem of deep funnel optimization and user privacy issues. Following the flow of impression → (click, install), the data was composed of subsampled impressions with their click and install results, upon which all feature information was anonymized. Our solution tackles this problem by emphasizing three key aspects: improving feature interaction learning in DNN, modeling relationships between click and install, and integrating diverse models to enhance overall performance. Notably, we designed a model architecture of Deep Cross Attentional Factorization Machine (DCAF) that outperformed other leading deep recommender systems such as DCN and DeepFM. With this approach, our team, Corca, accomplished 7th place on the final leaderboard with an NBCE of 6.015522. The implementation details can be accessed on GitHub at https://github.com/corca-ai/recsys-challenge-2023.
Pessimistic Rescaling and Distribution Shift of Boosting Models for Impression-Aware Online Advertising Recommendation

In this paper, we provide an overview of the approach we used as team Gabibboost for the ACM RecSys Challenge 2023, organized by ShareChat and Moj. The challenge focused on predicting user activity in the online advertising setting based on impression data, in particular, predicting whether a user would install an advertised application using a high-dimensional anonymized feature vector. Our proposed solution is based on an ensemble model that combines the strengths of several machine learning sub-models, including CatBoost, LightGBM, HistGradientBoosting, and two hybrid models. Our proposal is able to harness the strengths of our models through a distribution shift postprocessing and fine-tune the final prediction via a custom build pessimistic rescaling function. The final ensemble model allowed us to rank 1st on the academic leaderboard and 9th overall.
Privacy preservation of inventory management using adaptive key generation with Hyperledger blockchain technology

The blockchain is an emerging and essential technology in offering various services to several applications including the financial industry and information technology. Consequently, recent information methodologies cannot satisfy the constraints. The data management issue may rise complexities including tracking operations with information security and unsatisfactory traceability data quality due to the high increase in inventory management data. To address the challenge, this paper aims to focus on developing new hyperledger blockchain-enabled secure inventory management with an adaptive key management process. Here, the inventory management data processed by different distributors is encrypted using the adaptive key generation by Fitness-derived Predator Presence Probability-based Squirrel Search Algorithm (FPPP-SSA) that ensures data control. The optimal key management in encryption solves the multi-objective function based on the “degree of modification information preservation rate and hiding ratio (Euclidean distance).” Once the data are enciphered, they are saved in the hyperledger blockchain, where the smart contract is the chain code application. While restoring or decrypting data, the authorized distributor should use the same adaptive key for maintaining secured inventory management. The performance is evaluated under diverse test cases, and the results are estimated under certain performance metrics.
Performance Modeling of Hyperledger Fabric 2.0: A Queuing Theory-Based Approach

Hyperledger Fabric (shortened to Fabric) is an open-source, enterprise-level, permissioned distributed ledger technology platform with a highly modular, configurable architecture. It supports writing smart contracts in general-purpose programing languages and has become the preferred choice for enterprise-level blockchain applications. However, the transaction throughput of the Fabric system remains a critical factor that restricts the further application of this technology in various fields. Therefore, it is necessary to evaluate and optimize the performance of the Fabric blockchain platform. Existing performance modeling methods need to be improved in terms of compatibility and effectiveness. To address this, we propose a performance-compatible modeling method for Fabric using queuing theory, which considers the limited transaction pool and the situation where node groups are attacked. Using the Fabric 2.0 version as an example, we have established a model of the transaction process in the Fabric network. By analyzing the model’s continuous 3D time Markov process, we solved the system stationary equation and obtained analytical expressions for performance indicators such as system throughput, system steady-state queue length, and system average response time. We conducted extensive analyses and simulations to verify the models’ and formulations’ accuracy and validity. We believe this approach can be extended to various scenarios in other blockchain systems.
Enhancing Robust Liver Cancer Diagnosis: A Contrastive Multi-Modality Learner with Lightweight Fusion and Effective Data Augmentation

This paper explores the application of self-supervised contrastive learning in the medical domain, focusing on classification of multi-modality Magnetic Resonance (MR) images. To address the challenges of limited and hard-to-annotate medical data, we introduce multi-modality data augmentation (MDA) and cross-modality group convolution (CGC). In the pre-training phase, we leverage Simple Siamese networks to maximize the similarity between two augmented MR images from a patient, without a handcrafted pretext task. Our approach also combines 3D and 2D group convolution with a channel shuffle operation to efficiently incorporate different modalities of image features. Evaluation on liver MR images from a well-known hospital in Taiwan demonstrates a significant improvement over previous methods. This work contributes to advancing multi-modality contrastive learning, particularly in the context of medical imaging, offering enhanced tools for analyzing complex image data.
Quantum Particle-in-a-Sandbox: A Video Game That Explores the Time-Dependent Wave Function for Any Arbitrary One-Dimensional Potential

We present a tool, one that is both a stand-alone web-based video game and a Python package, designed for students to explore a particle’s wave function on one-dimensional potential surfaces. The tool relies on a basis set formalism and can, therefore, explore any one-dimensional potential surface imaginable. This tool also lets students interact with the wave function and is the first of its kind to explore concepts such as the superposition principle and wave function collapse; its time-dependent nature shows how any wave function evolves over time, allowing for exploration of other concepts such as the uncertainty principle. The video game’s ease of use makes these concepts accessible to anyone, without prior chemistry or programming background─though we expect that it would be most useful for undergraduate physical chemistry students and instructors. Preliminary use of QPiaS in a physical chemistry undergraduate course shows encouraging feedback regarding advancements in learning outcomes.
Corruption and Underdevelopment in Africa

Corruption is the misuse and misapplication of public and private power for personal and selfish interests. Corruption manifests through power rooted in the influence and greed for more power; it comes in the form of influence, wealth, and safeguarding of existing management and economic positions. Corruption of procurement is rooted in the purpose of obtaining goods and services that otherwise would not be available. Other forms of corruption include nepotism, favouritism, and collusion. Corruption in Africa has impeded the continent’s development and hinders sustainable development. It impacts the increase in poverty and unemployment; it affects infrastructure development and service delivery. It is a threat to the sustainable growth of Africa; if the threats do not stop, the development of Africa will be a nightmare.
Political Situation in Some African Countries

Writing about the Leadership and Economic Development Challenges in Post-Colonial Africa—Creating Inclusive Economic Growth will only be complete by highlighting some of the enervating issues about development in some African countries. The countries discussed in this chapter are selected because of their strategic position in terms of Africa’s social and economic development, and some are set based on their involvement in conflicts for a long time or because of their high levels of corruption.
Background

The chapter explains the book’s summary and why there are social and economic challenges in Africa. It draws attention to the insight of African underdevelopment and questions what led to them. The chapter pointed to the significant issues of social and economic challenges such as poverty, unemployment, security, infrastructure, and poor health and that Africa has the highest number of poor countries in the world. It questions why some African countries are not developing at the same rate as Asian countries that had independence almost simultaneously with African countries. Finally, the chapter uses the rational theory by Resecher and explained by Osuigwe to highlight the implication of making bad choices by leaders as a significant challenge to the development of Africa.