Reviewerly/exHarmony huggingface dataset:
Cybernetic Lenses for Designing and Living in a Complex World

Cybernetics has an exciting history that profoundly influenced HCI theory and practice. However, today, designers, engineers, and researchers are often unaware of how to engage with this powerful approach to inform technology design. We believe a cybernetic lens is vital to investigating and designing technologies for today's complex environments. In this in person, half-day workshop called "Cybernetic Lenses for Designing and Living in a Complex World", we present three cybernetic lenses demonstrated in two case studies: "From mundane objects to systems - asking better questions for technology design", and "Transportation networks, from human-computer interaction to socio-cultural consequences". Our goal is to offer an inclusive environment to provide theory and practical exercises for participants to gain and incorporate a cybernetics lens into their practice.
An Immersive Fold Instruction Module for Training Undergraduate Geologists

Representation of 3D structures in rocks is inherent to the study of geology. However, these are rarely visible in nature. This poses a significant challenge for undergraduate students as it affects their understanding of how to measure, analyse, and interpret complex 3D structures. Geoscience education currently relies on the use of two-dimensional media to represent 3D structures within rock. This demonstrates a gap which could be addressed using Virtual Reality (VR). This paper presents a novel tool for the visualisation of geological folds; wave-like undulations of layered rock. With the help of a preliminary interview study, contextual inquiries, and the continued involvement of a subject-matter expert, we have begun development of an instructional module on geological folds using our novel fold visualisation tool. We conducted usability testing with naïve users, undergraduate geology students, and the subject-matter expert. Future iterations of the tool and module will involve a plethora of working examples that students can use to learn terminology, practice measurements, and develop their interpretive skills of complex 3D-geometries.
Designing for Personas That Don’t Have a Voice

This case study paper situates insights from designing a mobile application within academic literature advocating for the consideration of non-human stakeholders in the design process. The application, FrogID, was developed as part of a citizen science project to support frog conservation in Australia. FrogID crowdsources the collection of frog calls to build up a national database, which in turn can inform conservation strategies. The paper discusses the use of personas and other design tools to ensure the design solution considers the perspectives of frogs as a non-human stakeholder group and to facilitate interdisciplinary team collaboration. As a broader contribution to the field of interaction design, the paper discusses the responsibility of designers to advocate on behalf of stakeholders that don’t have a voice.
Research Advanced in the Object Detection Based on Deep Learning

Object detection is one of the most basic tasks in the field of Computer vision, which targets to localize and allocate a wide range of predefined substances from images to their corresponding classification. Thanks to the rapid progress of deep learning, object detection algorithms based on convolutional neural networks have been applied in different fields, and have achieved breakthroughs both in accuracy and efficiency compared to traditional detection schemes. In this paper, based on detailed literature research and analysis, a comprehensive evaluation of object detection research advances are provided and specifically, we divide existing representative algorithms into three main frameworks, including traditional detection algorithms, anchor-based and anchor-free detection algorithms. We then conduct a series of experiments to analyze the achievement of different detection algorithms on some common datasets. Finally, we summarize the main challenges and provide an outlook on the future research directions of object detection.
Research Advanced in the Image Segmentation

Due to the progress of computer technology, image processing-based applications become more and more important not only in advanced research fields but also in our daily life. For example, biomedical image processing, autonomous vehicles, video surveillance, computer vision, augmented reality, and many more are some hotspots in research as well as the applications. The technology of image segmentation is the basis of all these applications. In this review, we summarize the traditional image segmentation methods and algorithms including segmentation based on thresholding, segmentation based on graph theory, and segmentation based on region. Also, due to the exceptional performance of the CNN model, a series of CNN-based segmentation algorithms were proposed. Along with the invention of these new approaches, segmentation task has been pushed to a higher accuracy and efficiency level. Thus, we also summarize the major CNN-based model, such as the FCN model, the Encoder-Decoder designed architectures, the Multi-scale and Pyramid-based architectures, and Deeplab Family. Moreover, we provide some information on some popular datasets and metrics to rigorously evaluate a model, and we provide tables that contain the quantitative information on each model's performance. Even though the outcomes of current models have reached a significant level, there are still many problems that need to be tackled. At last, we provide our opinion regarding the current situation in image segmentation field.
Aggregation of Masked Outputs for Improving Accuracy–Cost Trade-Off in Semantic Segmentation

Downsampling layers are essential for convolutional neural network-based semantic segmentation methods to widen their receptive fields. However, as fine-grained information is lost in the layers, the accuracy of these methods becomes limited. The need for downsampling layers can be eliminated by using a transformer encoder. Nevertheless, removing downsampling layers inevitably increases the computational cost of the network. In this paper, we present a mask transformer layer that reduces computational cost in any transformer-based networks by substituting a vanilla transformer layer. Additionally, we introduce an aggregation scheme to merge masked outputs, which enhances the accuracy of predictions. Our method aggregates intermediate outputs to generate a final output where the number of intermediate outputs depends on the importance of an area. With this strategy, we achieve different computational cost levels by modulating the threshold used to determine the importance. Our method comprises the following steps. First, we split the transformer encoder into several blocks and attach a segmentation decoder to each block to estimate the intermediate segmentation output. On the basis of the intermediate outputs and predefined thresholds, we classify unnecessary image patches and remove them in subsequent blocks. By progressively masking unnecessary patches, we obtain multiple intermediate outputs for important areas; aggregating them yields better segmentation accuracy with a lower computational burden. In addition, we determine the most effective training scheme and devise a threshold-search algorithm to optimally determine threshold hyperparameters. Extensive experiments on the ADE20K, Cityscapes, and Pascal-Context datasets verify the efficacy of our design, which surpasses the accuracy of the baseline method with lower computational cost.
An Efficient Diverse-Branch Convolution Scheme for Sensor-Based Human Activity Recognition

Deep convolutional networks have recently achieved significant success in sensor-based human activity recognition (HAR). Existing works are mainly devoted to extracting multiscale activity features from sensor time series by increasing network depth or width, which are not friendly to mobile devices with limited computing resources. It still remains a challenging issue to strike an ideal trade-off between activity recognition performance and inference-time costs <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g</i> ., the latency and memory footprint. To address this issue, we propose a diverse-branch convolution (DBC) scheme, which could strengthen the representation capacity of vanilla convolution via exploiting diverse branches of different scales and complexities to enrich activity feature space. Then DBC could be equivalently transformed into a single convolution layer after training for HAR deployment. In such manner, DBC only complicates training-time microstructure while preserving inference-time macrostructure, where the model performance can be boosted to a higher level and then converted back to its original inference-time structure for activity recognition. Extensive experiments are conducted on three publicly available benchmark datasets, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> ., OPPORTUNITY, UniMiB-SHAR, WISDM, and a self-collected Weakly Labeled HAR dataset, which verify that our method can give a lift in performance while maintaining the same number of parameters and FLOPs as baselines. Finally, actual inference-time cost is evaluated for HAR deployment on a Raspberry Pi platform.
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training

A resource-adaptive supernet adjusts its subnets for inference to fit the dynamically available resources. In this paper, we propose prioritized subnet sampling to train a resource-adaptive supernet, termed PSS-Net. We maintain multiple subnet pools, each of which stores the information of substantial subnets with similar resource consumption. Considering a resource constraint, subnets conditioned on this resource constraint are sampled from a pre-defined subnet structure space and high-quality ones will be inserted into the corresponding subnet pool. Then, the sampling will gradually be prone to sampling subnets from the subnet pools. Moreover, the one with a better performance metric is assigned with higher priority to train our PSS-Net, if sampling is from a subnet pool. At the end of training, our PSS-Net retains the best subnet in each pool to entitle a fast switch of high-quality subnets for inference when the available resources vary. Experiments on ImageNet using MobileNet-V1/V2 and ResNet-50 show that our PSS-Net can well outperform state-of-the-art resource-adaptive supernets. Our project is publicly available at https://github.com/chenbong/PSS-Net.
INFOGRAPHICS USED IN NEWS TEXTS (BASED ON THE BBC AND CNN ONLINE NEWS)

The article highlights the use of infographics to effectively present the news material at BBC and CNN web pages. Infographic is a visual representation of information, data and knowledge. The infographic types that are widely used in news texts include maps, different kinds of graphs and charts such as bar/line/pie/column/bubble/gauge/stock/waterfall/flow charts; area/ hierarchy/circuit/tree diagrams; pictographs, timelines. Also, the symbiosis of infographic resources and additional graphic components (images, icons, geometric shapes, colour, numbers, and headers) was taken into account within the scopes of the current research. All of these allow controlling the infographics flow. Both verbal and nonverbal elements are considered to be crucially significant in creating the eye-catching and attention-grabbing infographic picture. Besides, the digital mode and colour play a significant role in presenting the information infographically. Numbers convey large amounts of information briefly and accurately and colour denotes emotionally valuable metaphorical meaning, stylistic and associative properties. The visual and the verbal can be integrated into a single syntagmatic unit. Verbal elements elucidate and decipher the nonverbal symbols, restate the message of the infographic image in a more precise way, distilling just one from the many possible meanings the image might have. Verbal items are represented by means of a single lexeme, a word combination or a simple sentence. Nonverbal components provide the verbal ones with the essential and highly informative visuals by showing the data, presenting many numbers in a small space, making large data sets coherent. They serve a reasonably clear purpose of description, exploration, tabulation and decoration. The visual elements serve as syntax identifying the participants by nonverbal means. Infographic is an effective and powerful tool to explain complex issues in a way that can quickly lead to insight and better understanding by making information easy to digest, educational, and engaging.
Research on the Management Mechanism of BALIS Projects

Beijing Academic Library & Information System (BALIS), a nonprofit organization and the largest Regional Alliance of University Library (RAOUL) in Beijing, is the representative of Chinese RAOULs.BALIS founded in 2007 has 100 member libraries and covers almost all university libraries in Beijing.BALIS has achieved the aim of literature resources between member libraries, which define the life of BALIS and what it does well.BALIS Management Committee (BMCE) organizes the application of Subprojects (SPS) every year and ensures opportunity for every BALIS Member Library.After the SPS is approved, the BALIS Management Center (BMC) is responsible for monitoring and controlling the SPS.This article mainly adopts the method of case analysis to study BALIS's management of SPS, funds, and performance, and its purpose is to explain the management mechanism of Chinese RAOULs.
Field Test Summary of Two Kinds of Electronic Detonator for Seismic Exploration

Electronic detonators are widely used because of their advantages in real-time supervision of the whole life cycle (Zang, 2022).Due to the high requirements of the time difference synchronization between the electronic initiation system and the seismic wave recording system, the Electronic detonator has not been widely used for Seismic exploration (Yang, 2020).This paper expounds the systematic and scientific test method from the aspects of the comprehensive performance of electronic detonators for exploration, the compatibility between the electronic detonator initiation system and the geophysical blasting machine system, the constraints of the geophysical explosion-related collaborative Danling management cloud platform, and the quality of data collected by electronic detonator blasting in wells., and based on the analysis of the test results, the problems that need to be improved in the application of electronic detonators and detonation systems in the large-scale production of geophysical prospecting industry are put forward.
Features of the Organization of the Educational Process in the Conditions of Distance Learning

Currently, among the many existing types and forms of education, distance learning is becoming one of the priority areas of pedagogical and educational-methodical activities of many universities, colleges, and general educational institutions. Therefore, the main existing traditional and modern types, methods and forms of education are analyzed in the article from the angle of suitability for use in remote form. Special attention is paid to the advantages, psychological and pedagogical features and problematic aspects of distance learning. The comparative characteristics of synchronous and asynchronous modes of distance learning were considered and carried out, the positive and negative aspects of each mode were determined. A general methodology for evaluating the effectiveness of methods, organizational forms, and types of training has been developed, which is based on theoretical and empirical methods of scientific research and makes it possible to objectively evaluate the effectiveness of training for a wide range of educational programs. To evaluate the effectiveness of methods and forms of distance learning, modern methods of scientific research were used. An analysis of teaching methods was carried out, namely methods for acquiring knowledge (motivational-learning, problem-searching, visual, game, reproductive) and methods for improving knowledge, skills and abilities (practical, interactive, creative, control and self-control methods). The results of the study showed that effective types of training are: distance learning, modular learning, interactive learning, dual education, problem-based learning and programmed learning. The most effective and relevant methods of distance learning have been determined: practical, problem-solving, visual, creative, interactive, motivational-learning methods and methods of control and self-control. According to the results of qualitative and quantitative analysis, the most effective forms of distance learning were identified, namely: individual, video conferences, Google applications, independent work, correspondence, free schedule, video training, game training, online chat. The results of the analysis enable teachers to make a qualified choice of the most effective methods and forms for both traditional and distance learning, and also indicate directions for improving the most effective approaches to learning. The intended prospects for further research consist in the improvement of the proposed approaches to increase the effectiveness of the forms and methods of training in order to raise the level of the quality of training.
Designing a Distance Course for Developing the Art Teachers’ Media and Information Literacy

Currently, media literacy is a necessary component of the general information culture of a person, which becomes absolutely crucial in the conditions of Russia’s military aggression and the harsh realities of the Ukrainian information space with numerous examples of spreading untrue, unverified, and “fake” information. In recent years, the concept of “media information literacy” (MIL) has become normalized in scientific circulation. It implies recognition of the leading role of information and media in everyday life, enables citizens to understand the functions of mass media and other information providers, critically evaluate their content and make informed decisions. In the documents of UNESCO and the European Commission, the concept of MIL is used as a universal term that denotes a set of knowledge, attitudes, abilities, and skills that allow access to information and knowledge, analyse, evaluate, use, create and disseminate them with maximum productivity in accordance with legislative and ethical standards and with respect for human rights. The article highlights the process of designing the distance course “Media Literacy in Art Classes” for teachers of general secondary education institutions that teach the courses of the art cycle, in particular, the integrated course “Art”. Scientific sources and legal documents were analysed to clarify the essence and modern interpretation of the concept of “media information literacy”; a number of mass open online courses on media literacy were considered; a survey of art teachers was conducted. According to the results of the survey, 6 topics, which were the most interesting to the respondents, were selected and the structure of the distance course, designed for 30 hours, 1 ECTS credit, was formed. The content of the course includes the study of the peculiarities of perception and critical evaluation of visual and audiovisual arts, as well as various aspects of the impact of media arts on the content of media messages. The course can be offered to teachers, especially teachers of primary school and courses in the educational field “Art”, as a certification programme in the system of advanced training.
Physical Quality Duck Jerky with Liquid Smoke Sonication

This study aims to determine the effect of adding coconut liquid smoke sonication on pH, Water Holding Capacity (WHC), tenderness, L*a*b* color, and duck jerky aroma.The jerky is made from ground duck meat with additional spices such as salt, brown sugar, garlic, ginger, galangal, and coriander.The concentration of liquid smoke used is 1.5%.This research method used a completely randomized design (CRD) with 6 treatments and 3 replications consisting of P0: without adding liquid smoke, P1: liquid smoke without sonication, P2: liquid smoke sonication for 5 min, P3: liquid smoke sonication for 10 min, P4: liquid smoke sonication for 15 min, and P5: liquid smoke sonication for 20 min.Parameters observed included pH, WHC, tenderness, L*a*b* color, and aroma.Data were analyzed using Analysis of Variance (ANOVA).If the data shows a significant difference, proceed with the Duncan Multiple Range Test (DMRT).The average value of pH was 5.66-6.12,WHC was 70.67%-79.67%,tenderness was 3.27-4.93,lightness (L*) was 42.62%-44.86%,redness (a*) was 11.12%-12.86%,yellowness (b*) was 12.03%-12.49%,the aroma was 1.67-3.87.The results showed that sonication liquid smoke had no significant effect (P > 0.05) on pH, WHC, L*a*b color, and aroma but had a very significant effect (P < 0.01) on tenderness.Liquid smoke with sonication for 10 min is the duck jerky that panelists must accept because it has the right aroma of smoke and meat taste.
Post-quantum Security for the Extended Access Control Protocol

The Extended Access Control (EAC) protocol for authenticated key agreement is mainly used to secure connections between machine-readable travel documents (MRTDs) and inspection terminals, but it can also be adopted as a universal solution for attribute-based access control with smart cards. The security of EAC is currently based on the Diffie-Hellman problem, which may not be hard when considering quantum computers. In this work we present PQ-EAC, a quantum-resistant version of the EAC protocol. We show how to achieve post-quantum confidentiality and authentication without sacrificing real-world usability on smart cards. To ease adoption, we present two main versions of PQ-EAC: One that uses signatures for authentication and one where authentication is facilitated using long-term KEM keys. Both versions can be adapted to achieve forward secrecy and to reduce round complexity. To ensure backwards-compatibility, PQ-EAC can be implemented using only Application Protocol Data Units (APDUs) specified for EAC in standard BSI TR-03110. Merely the protocol messages needed to achieve forward secrecy require an additional APDU not specified in TR-03110. We prove security of all versions in the real-or-random model of Bellare and Rogaway. To show real-world practicality of PQ-EAC we have implemented a version using signatures on an ARM SC300 security controller, which is typically deployed in MRTDs. We also implemented PQ-EAC on a VISOCORE® terminal for border control. We then conducted several experiments to evaluate the performance of PQ-EAC executed between chip and terminal under various real-world conditions. Our results strongly suggest that PQ-EAC is efficient enough for use in border control.