bluuebunny/crossref_metadata_2025 huggingface dataset:
An Ontology Based Model for the Optimization of the Shutters Cutting Stock for Compressor Valves
Authors: Guizzi Guido  , Romano Elpidio  , Damiani Lorenzo  , Giribone Pietro  , Revetria Roberto  , Toma Matteo
Published: February 2025

This paper describes an application of the cutting stock problem where great part of the complexity of the problem was actively addressed by mean of a definition of a suitable ontology. It deals with the realization of a series of concentric rings starting from a raw circular flange. The goal is to minimize the scrap and satisfy the customers demand, keeping into account all the constraints related to the coupling of rings and flanges. To reach the goal a combinatory optimization approach was employed. The mathematical model is solved by the LINGO software, an interactive tool for the solution of linear, quadratic and integer number programming problems.
A New Code Generation Method for Software Engineering: From Requirements Model to Source Code
Authors: Huang Bo  , Fang Zhijun  , Wu Guoqing  , Sun Xiankun  , Gao Yongbin
Published: February 2025

the existing software engineering techniques for software synthesis from requirements model to source code have many limitations. The synthesis approach shows that these limitations focused on the refinement relationship between the requirements specification and the desired system. We have to propose a new approach for code generation to overcome such limitations, i.e. refining the software behaviors in requirements model to code, distinguishing function information and architecture information from requirements model, among others. Hence, in this thesis we aim at the problems that how to modeling based on software behaviors, how to delimitate the system architecture and so on. And we also will show a sample, ultimately, to demonstrate our approach. Meanwhile, some additional techniques for synthesis to ensure the correctness of the source code will be recommended.
Smart-circular systems: a service business model perspective
Authors: Alcayaga A.  , Hansen E.G.
Published: February 2025

The Internet of Things and the amplified capabilities of smart products can be increasingly utilised for the development of feedback-rich systems and loops throughout the entire product life cycle. By adopting the IoT and collecting data during product utilisation, companies can replace the end-of-life concept with product life extension and circular loops. In this sense, service business models hold the greatest potential to optimise the utilisation of goods over time. These models allow a reduction of the overall life cycle costs and contribute to resource-efficiency and the transition towards a circular economy. This paper introduces the concept of smart-circular systems that reflects the interplay between the Internet of Things, the circular economy and service business models and presents a conceptual framework for further empirical analysis of this phenomenon. The framework focuses on product-service systems and more broadly on services business models that optimise the utilisation of goods over time through the amplification of circular activities by the introduction of smart enablers. It also considers three main business models types and tactics for successful implementation of service business models.
Uniquely for you: the individualised avenue for longer product lifetimes
Authors: Armellini J.  , Ford P.
Published: February 2025

Object customisation has historically been a regular practice as a form of self, or group-identification. A product we can identify ourselves with, is one that we keep for longer, tend to repair when it breaks and dispose of later as a result of an emotional bond with it. Such bond is strengthened when we invest time and effort customising. Consumer involvement when customising is facilitated by new technologies in design and manufacturing. For example, computer algorithms can automate customisation, meaning products are customised for consumers rather than by consumers, (namely individualisation). However, the adequate ‘amount’ of consumer interaction is still debated amongst researchers. This paper questions the consumer benefit and extent of an emotional bond with individualised products. Using a mixed-method approach, 63 participants responded to in-depth interviews while engaging with individualisation exercises. Respondents were profiled as either of two types of consumers depending on their interest in art, design and critical engagement with what they consume, namely Active Consumers (AC) and Passive Consumers (PC). Results suggest individualisation attracts PCs, showing signs of greater engagement in the process and attachment to the product than ACs. PCs welcomed the automated decisions taken by an individualisation toolkit, whilst ACs found it detrimental to the experience. It is claimed that individualisation can strengthen emotional bonds between PCs and the resulting products. The paper concludes that individualisation could offer PCs new experiences, enriching their lives, generating an emotional attachment leading to longer product lifetimes, and potentially changing consuming behaviours otherwise unlikely to be nurtured.
Planned obsolescence: who are those planners?
Authors: Longmuss J.  , Poppe E.
Published: February 2025

There is a controversial discussion on the phenomenon of “planned obsolescence”. However, shrinking product lifetimes and product qualities do not prove that actors in the product development process take conscious decisions toward premature obsolescence.
Circular business model framework: mapping value creation architectures along the product lifecycle
Authors: Nussholz J.
Published: February 2025

Circular business models are foreseen to contribute to enabling prolonged lifetimes of products and components through successive cycles of reuse, repair, remanufacturing and closing material loops. To realize economic viability and resource efficiency savings from a circular business model, early consideration and integrated planning of the product lifecycle and value creation architectures at the relevant points in the lifecycle is pivotal. However, the current frameworks for business model design have not been designed to recognize the specific opportunity points of the product lifecycle to create and capture additional value from cycling resources. They do not acknowledge that it often takes distinct value creation architectures and value propositions to capitalize on the value creation potential. To attend to this gap, this paper develops a circular business model framework that is based on the current understanding of resource efficiency strategies and systematically integrates lifecycle value management with traditional business model design thinking. Through this, the developed framework is intended to serve as guidance for circular business model development to incorporate circular principles and to capitalize on additional value from cycling resources. To explore the usefulness of the framework developed from literature, a comparative case study design with two cases of Swedish companies operating circular business models is employed. The framework proved useful to map the companies' distinct value creation architectures that enable cycling of resources and to point to opportunity spaces for additional value creation. Suggestions for further refinement are made.
The role of product designers in the transition towards the circular economy: a reality check
Authors: Sumter D.X.  , Bakker C.A.  , Balkenende A.R.
Published: February 2025

This paper examines the role of product designers in the transition towards the circular economy. Both scientific and grey literature show remarkable optimism when it comes to role strategic and coordinating role designers could play in this transition process. However, there has been little examination of the actual role and influence designers have in practice. In this paper we review the roles that designers play in the transition towards a circular economy according to literature. Through semi-structured interviews, we uncover the views of designers themselves, which we then use to make a comparison. Our main conclusion is that designers experience a lack of knowledge and/or work in predetermined solution spaces, which prevents them from taking on the role that is expected in literature.
The Reporting Event Ontology Design Pattern and Its Extension to Report News Events
Authors: Kowalczuk Ewa  , Ławrynowicz Agnieszka
Published: February 2025

This article describes an ontology design pattern for modelling events as elements of discourse. Information provided about an event is not treated as universal truth, but rather as a statement of a particular agent, based on defined sources. We demonstrate how this pattern can be used for modelling historical debates. We also propose specialisation of the pattern, which models presentation of the current events in mass media for the purposes of citizen control.
A Trajectory Measuring Method of Multi-Fingers Based on Image Processing
Authors: Dai Yong  , Wu Junbin  , Ji Junhong  , Jia Qi
Published: February 2025

To measure the trajectory of multi-fingers during a gripping process, a method detecting the trajectory of fingers during gripping and calculating the relationship among joint angles is proposed. Some labels are attached on fingers, then the total gripping process is captured using video cameras. The joint angles are obtained and the relationship between finger joint angles are established. Afterwards, fingers' motion trajectory is simulated according to the function. The results show that the proposed method can generate joint trajectories, which would be helpful to analyze and design humanoid robot hands. It will provide the design basis for the size design and mechanical design while designing humanoid manipulator.
Facial Expression Recognition Based on Fuzzy Density Dynamic Adjustment
Authors: Li Yanqiu  , Ren Fuji  , Hu Min  , Cheng Wenjuan
Published: February 2025

In the expression recognition with multi-classifier fusion, fuzzy integral is a more commonly used fusion method. The key to applying fuzzy integral is how to determine the fuzzy density. At present, the methods of determining the fuzzy density are mainly by constructing the confusion matrix by using the prior knowledge of the training samples, without taking into account the dynamic information contained in each classifier when identifying specific target. Aiming at this problem, after obtaining the fuzzy density of each classifier by using the confusion matrix, this paper adjusts it by measuring the consistency of the recognition results of the testing object. The experimental results show that the method can obtain better fusion effect than traditional fuzzy density assignment method when used in facial expression recognition, and improve the accuracy of expression recognition.
An Application of Multispectral Semantic-Image Space for Global Farming Analysis and Crop Condition Comparisons
Authors: Wijitdechakul Jinmika  , Kiyoki Yasushi  , Sasaki Shiori
Published: February 2025

The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This system aims to realize and interpret environmental phenomena and changes occurring that happening in world wide scope. Semantic computing is important and promising approach to multispectral semantic-image analysis for various environmental aspects and contexts in physical world. In the previous study, we proposed a new system of agricultural monitoring and analysis based on semantic computing concept that it realizes the interpretation of agricultural health condition as human-level interpretation. In this paper, we propose a new analytical method for agriculture global comparisons to realize and recognize crop condition with several places in global scale. Multispectral semantic-image space for agricultural analysis can be utilized for global crop health monitoring by comparing crop conditions among different places. Our method applies semantic distance calculation to measure similarity among multispectral image data to realize the crop health condition as a ranking. According to our new proposed analytical method, we demonstrate a prototype implementation in the case of rye farm in Latvia and Finland. This prototype implementation shows an analysis in the case that image data have same crop type and conditions.
Global Sharing Analysis and Visualization of Water Quality by 5DWorld Map: A Case Study at Sichang Island, Thailand
Authors: Chawakitchareon Petchporn  , Ladsavong Khoumkham  , Kiyoki Yasushi  , Sasaki Shiori  , Rungsupa Sompop
Published: February 2025

This paper presents a global sharing analysis and visualization of water quality analysis by 5D World Map (5DWM) system. The data resources in this research collected from Sichang Island, Chonburi province, Thailand during 1990 to 2002 and 2010 to 2017. Six parameters of water quality were selected during 1990 to 2002 i.e. chlorophyll a, ammonia, nitrite, nitrate, phosphate and. The total locations sites were 21 stations which situated around Sichang Island. Otherwise, ten parameters were selected during 2010 to 2016 i.e. temperature, salinity, dissolved oxygen (DO), pH, ammonia, nitrite, nitrate, phosphate, silicate, and alkalinity. On the other hand, eight parameters were selected in February and July 2017 i.e. temperature, pH, oxidation reduction potential (ORP), conductivity, turbidity, dissolved oxygen (DO), TDS (Total Dissolved Solids), and salinity. All parameter of water quality was added and display by 5DWorld Map in order to visualize and sharing the water quality. Our results showed that 5DWorld Map can apply to environmental analysis and semantic computing. We apply the dynamic evaluation and mapping functions of multiple views of temporal-spatial metrics, and integrate the results of semantic evaluation to analyze environmental multimedia information resources. 5D World Map System for world-wide viewing for Global Environmental Analysis for water quality around Sichang Island, Thailand was reported in this study.
SNOMED CT Primitive Concept Similarity Measure by Concept Name Text Similarity Approach
Authors: Htun Htet Htet  , Sornlertlamvanich Virach
Published: February 2025

In the last few years, Concept Similarity Measures (CSMs) become important for the biomedical ontologies in order to find adaptable treatments from the conceptually similar diseases. For the ontology primitive concepts, they are not fully defined in the ontology so taxonomical path-based similarity measure cannot give the correct similarity for primitive concepts. In this paper, we propose a new primitive concept name similarity measure based on natural language processing to get a better result in concept similarity measure in terms of noun phrase construction analysis. We conduct experiments on the standard clinical ontology SNOMED CT and make comparison between taxonomical path-based measure and our proposed similarity measure against human expert results in order to prove our proposed similarity measure can outperform the existing approaches for primitive concept similarity.
A Semantic Multispectral Images Analysis Retrieval Method for Interpreting Deforestation Effects in Soil Degradation
Authors: Rachmawan Irene Erlyn Wina  , Kiyoki Yasushi
Published: February 2025

Deforestation is still a major nature phenomenon in our society. For assessing deforestation effect, satellites remote sensing provides a fundamental data for observation. While new remote-sensing technologies are able to represent high-resolution forest mapping, the application is still limited only for detecting and mapping the deforestation area. In this paper, we proposed a new method for retrieve the information contained on Satellite Multispectral images in order to interpreting deforestation effect in the context of soil degradation. We proposed an idea to interpret reflected “substances (material)” of bare soil in deforested area in spectrum domain into human language. The objectives of this paper are to (1) recognize the deforestation activity automatically. (2) Identify deforestation causes and examines the deforestation effect based on deforestation causes. (3) Scrutinize deforestation effects on soil degradation. (4) Representing nature knowledge of deforestation effect by performing calculation for semantic retrieval, to bring the clear comprehensible knowledge even for people who are not familiar with forestry. Semantic retrieval formed by understanding queries and showing queries result based on semantic calculation. As for experimental study, Riau Tropical Forest has been selected as the study area, where the multispectral data was acquired by using Landsat 8 Satellite between 2013 and 2014; Where forest fire and logging activities are reported, and detected.
Classifying Legal Norms with Active Machine Learning
Authors: Waltl Bernhard  , Muhr Johannes  , Glaser Ingo  , Bonczek Georg  , Scepankova Elena  , Matthes Florian
Published: February 2025

This paper describes an extended machine learning approach to classify legal norms in German statutory texts. We implemented an active machine learning (AML) framework based on open-source software. Within the paper we discuss different query strategies to optimize the selection of instances during the learning phase to decrease the required training data.
A Design for Interchangeable Simulation and Implementation
Authors: Jensen Klaus Birkelund  , Vinter Brian
Published: February 2025

Research on concurrent systems requires modelling, simulation and evaluation in many settings. We describe a design for Interchangeable Simulation and Implementation (ISI, pronounced easy), an approach that enables the simultaneous modelling, simulation and evaluation of highly concurrent process based systems.
Not that Concurrent!
Authors: Teig Øyvind
Published: February 2025

Concurrency is, in the literature, often used as a noun with a range of strengths: there is more or less concurrency; it is more or less limited; it may even be seen described as complete. In trying to discuss multi-threaded programming with programmers who state that they program single-threaded, it is important to communicate that they may program less concurrently, but probably not as non-concurrently as they believe. What are the factors that increase concurrency and which factors are orthogonal to the degree of concurrency? Does a Go language goroutine increase it and is a C++ object orthogonal? Will the CSP paradigm generally enable increased concurrency? Is the CSP paradigm of communication-with-synchronisation itself orthogonal to the degree of concurrency? It is also important to understand the term parallel slackness: does it introduce or enable more concurrency? And what about atomicity?
Communicating Connected Components: Extending Plug and Play to Support Skeletons
Authors: Chalmers Kevin  , Kerridge Jon  , Pedersen Jan Bækgaard
Published: February 2025

For a number of years, the Communicating Process Architecture (CPA) community have developed languages and runtimes supporting message passing con-currency. For these we always provide a set of reusable processes called plug and play. These components provide a rich set of functions to the new CPA programmer, enabling them to develop applications. In this paper, we describe recent work in taking the plug and play ideology and applying it to the area of algorithmic skeletons. We have based our work on the RISC-pb2l specifications of Danelutto et. al. to provide a base set of skeletal components, focusing on the communication behaviours they exhibit.
Building a Sensor System for a Large Scale Arctic Observatory
Authors: Bjørndalen John Markus  , Anshus Otto J.  , Brox-Larsen Tore  , Ha Phuong Hoai  , Ims Rolf Anker  , Jepsen Jane Uhd  , Killengreen Siw Turid  , Kleiven Eivind Flittie  , Soininen Eeva Marjatta  , Yoccoz Nigel Gilles  , Horsch Alexander
Published: February 2025

The Climate-ecological Observatory for Arctic Tundra (COAT) is a long-term research initiative for real time detection, documentation and understanding of climate impacts on terrestrial arctic ecosystems. COAT is a collaboration of several Norwegian research institutions under the umbrella of FRAM - High North Centre for Climate and Environment. The study areas include the bioclimatic extremes of the terrestrial Arctic, low arctic coast of Norway and high arctic Svalbard. An important part of the observatory is sensors placed in the environment to observe wildlife and plants. Current sensor packages are fairly robust and work well for small to medium scale deployment. For larger scales, however, there is a clear demand for better management and control. This paper summarises some current experiences with deploying cameras and some of the challenges that we intend to address in an up-coming project where we aim to increase the capability of scientists to handle a larger number and diversity of sensor types and variation in deployment while minimising human traffic and impact in the monitored environments. To build this type of observatory at increasing scales, we expect to use robust programming architectures, open modular sensor packages, on-line processing, monitoring and configuration management and a range of communication technologies to cope with variations in connectivity.
Mapping CSP Models to Hardware Using CλaSH
Authors: Kuipers Frits P.  , Wester Rinse  , Kuper Jan  , Broenink Jan F.
Published: February 2025

Current robotic systems are becoming more and more complex. This is due to an increase in the number of subsystems that have to be controlled from a central processing unit as well as more stringent requirements on stability, reliability and timing. A possible solution is to offload computationally demanding parts to an FPGA connected to the main processor. The parallel nature of FPGAs makes achieving hard real-time guarantees more easy. Additionally, due its parallel and sequential constructs, CSP matches structurally with an FPGA. In this paper, a CSP to hardware mapping is proposed where key CSP structures are translated to hardware using the functional language CλaSH. The CSP structures can be designed using the TERRA tool chain while CλaSH code is generated for implementing hardware. The functionality of the CSP mapping is illustrated using some producer-consumer examples. In this paper, the design, implementation and tests are presented. Future work is to implement the ALT construct, generate token diagrams for user understanding.
Ontology Design Patterns for Winston's Taxonomy Of Part-Whole Relations
Authors: Shimizu Cogan  , Hitzler Pascal  , Paul Clare
Published: February 2025

While the formal modeling of part-whole relationships has been of interest, and studied, in many fields including ontology modeling, as of yet there has been no dedicated ontology design pattern which goes beyond the modeling of an absolute minimum. We correct this by providing two patterns based on Winston's landmark paper, “A Taxonomy of Part-Whole Relations.”
Space-Time Trade-Off in Decision Analysis Software
Authors: Danielson Mats  , Ekenberg Love
Published: February 2025

In decision analysis, there are several problems with the assignment of precise numbers to decision components, such as probabilities, values and weighs. These can very seldom realistically be estimated. Therefore, various alternative approaches have been suggested over the years, such as interval, capacity and ranking models. The more general of these are however problematical from several computational viewpoints and in this article, we deal with the server-side issues when converting the application from a stand-alone PC program to a server-client decision analytical software. On a server with a large number of users, space requirements become paramount as opposed to a single user on a PC. On a PC, matrices can be explicitly stored in memory, while on a server, to save space, matrices might have to be stored in an implicit (compacted) way, leading to space-time trade-offs.
Software Development Effort Estimation Using Feature Selection Techniques
Authors: Hosni Mohamed  , Idri Ali
Published: February 2025

Context: Software Development Effort Estimation (SDEE) remains as the most important activity in software project management. Providing accurate estimates at early stages of software life cycle was the subject of a large number of studies for more than four decades. Therefore, different SDEE techniques have been proposed and evaluated. In order to improve the accuracy of the proposed estimation techniques, many researchers investigated different data preprocessing tasks in combination with SDEE techniques, especially Feature Selection (FS).
Editing with Search and Exploration for Controlled Languages
Authors: Angelov Krasimir  , Měchura Michal Boleslav
Published: February 2025

We present an editor for controlled languages which is a combination of a syntax editor and a predictive editor. It shows a bird's-eye view which lets the user to explore what is possible in the language. Still, unlike the syntax editors the user is not expected to understand the underlying abstract syntax or ontology behind the language. It also lets the user to enter arbitrary phrases from which the editor finds the phrases which are the closest match.
Representing Representing: The Ontology of Aboutness
Authors: Simons Peter
Published: February 2025

Perceptions, thoughts, pictures and expressions are all typically about something. In mental cases the relation is called intentionality, in pictures depiction, in expressions denotation. The nature of this aboutness has long been a topic for philosophical puzzlement and controversy. Whether it requires the existence of a kind of thing, quality or relation not found in inanimate nature, whether it is analysable, whether it comes in one or many forms, are all matters of dispute. The ontology of aboutness has to be at least plausibly conjectured if its features are to be represented within information systems that are sophisticated and capable enough to themselves represent representation. It falls therefore to the ontologist to investigate the entities and factors required and suitable to capture the form and matter of representation. This is no straightforward task, and there are many pitfalls. But it is a task that must be taken up if ontologies and the information systems that employ them are to advance to a stage where conjecture, diversity of opinion, (mis)information, uncertainty, falsehood, error, revision, contradiction and correction are to be smoothly represented and reconciled, and linked, as they must be, to action and decision, whether natural or artificial. Looking for help past and present, this paper sets about addressing that difficult task.
CuisineNet: Food Attributes Classification Using Multi-Scale Convolution Network
Authors: Sarker Md. Mostafa Kamal  , Jabreel Mohammed  , Rashwan Hatem A.  , Banu Syeda Furruka  , Singh Vivek Kumar  , Moreno Antonio  , Radeva Petia  , Puig Domenec
Published: February 2025

Diversity of food and its attributes represents the culinary habits of peoples from different countries. Thus, this paper addresses the problem of identifying food culture of people around the world and its flavor by classifying two main food attributes, cuisine and flavor. A deep learning model based on multi-scale convotuional networks is proposed for extracting more accurate features from input images. The aggregation of multi-scale convolution layers with different kernel size is also used for weighting the features results from different scales. In addition, a joint loss function based on Negative Log Likelihood (NLL) is used to fit the model probability to multi labeled classes for multi-modal classification task. Furthermore, this work provides a new dataset for food attributes, so-called Yummly48K, extracted from the popular food website, Yummly. Our model is assessed on the constructed Yummly48K dataset. The experimental results show that our proposed method yields 65% and 62% average F1score on validation and test set which outperforming the state-of-the-art models.
A Novel Model for POI Recommendation in Indoor Space
Authors: Ni Sheng  , Lin Chen  , Weng Yuyou
Published: February 2025

In recent years, with the rapid development of location based services (LBS) and the improvement of indoor localization technology, a large amount of valuable trajectory data can be collected in an effective manner. In this article, a probabilistic model for Point-Of-Interest (POI) recommendation in indoor space is proposed, which can automatically discover the category of stores and the interest of users, and then recommend the stores that users may be interested in. It facilitates local business. Comprehensive experiments on a real shopping mall trajectory data set is conducted. The result demonstrates that the recommendation system proposed achieves better performance than the state-of-the-art method.
Patent Domain Terminology Extraction Based on Multi-Feature Fusion and BiLSTM-CRF Model
Authors: Lyu Xiangru  , Lyu Xueqiang  , Sun Fanshu  , Dong Zhian
Published: February 2025

In order to improve the accuracy and recall rate of term extraction results in the Chinese patent domain, approaching from the perspective of deep learning, with part-of-speech and dependency relationships as features, a patent domain term extration model (Bi-LSTM-CRF) was proposed by combining Conditional Random Fields (CRF) and bi-directional long short-term memory (Bi-LSTM) based on a multi-feature fusion. Based on the two explicit characteristics of part of speech and dependency, the double-layer bidirectional LSTM neural network was used to mine the temporal and semantic information in the data, which overcame the disadvantages of the traditional methods, such as weak generality and inability to capture the implicit information in the context as well as addressing the dependency relationship among the output tags through the CRF layer. Experimental results show that this deep learning method is effective in terms of domain term extraction.
Research on the Construction of Applied MPA Education Quality Evaluation System
Authors: Li Xiaoyan  , Jiang Min
Published: February 2025

To solve MPA education problems such as out of touch with the actual practice and lack of applicability, the author carries out a survey with a self-made questionnaire and find out the four main factors affecting the quality of MPA education with the use of exploratory factor analysis: The corresponding MPA education quality assessment index system is built according to these four dimensions: education environment, teacher and enrollment, process management and educational effect.
Internet of Things, Blockchain and Intelligent Systems: The Primary Role of Data Protection
Authors: Fabiano Nicola
Published: February 2025

The IoT is innovative and important phenomenon prone to several services and applications such as the blockchain, but it should consider the legal issues related to the data protection law. We should be taken into account the legal issues related to the data protection and privacy law. Technological solutions are welcome, but it is necessary, before developing applications, to consider the risks which we cannot dismiss. Personal data is a value. It is important to evaluate the European Regulation n. 679/2016, European General Data Protection Regulation (GDPR) that will enter into force on 25 May 2018. The GDPR introduces Data Protection by Design and by Default, Data Protection Impact Assessment (DPIA), data breach notification and significant administrative fines in respect of infringements of the Regulation. It is fundamental to evaluate the legal issues and prevent them, adopting in each project the Data Protection by Design approach. Regarding the data protection and security risks, there are some issues with potential consequences for data and liability. A correct law analysis allows evaluating risks preventing the wrong use of personal data. The contribution describes the main legal issues related to privacy and data protection focusing on the Privacy by Design approach, according to the GDPR.
Robot-Teachers and Phronēsis: Designing Signature Pedagogy with Robots
Authors: Toft Nørgård Rikke  , Ess Charles Melvin  , Ni Bhroin Niamh
Published: February 2025

The world's first robot teacher, Saya, was introduced to a classroom in Japan in 2009. Saya had the appearance of a young female teacher. She could express six basic emotions, take the register and shout orders like ‘be quiet’ [1]. Since 2009, humanoid robot technologies have developed. It is now suggested that robot teachers may become regular features in educational settings and may even ‘take over’ from human teachers in ten to fifteen years [2, 3]. Designed to look and act like a particular kind of human; robot teachers mediate human existence and roles, while also aiming to support education through sophisticated, automated, human-like interaction. Focusing on the role of virtue, and in particular phronēsis, in educational contexts, our paper explores the design and implications of robots such as Saya or ARTIE, a robot teacher at Oxford Brookes University [4]. Drawing on an initial empirical exploration of such robots as teachers we propose a model for signature pedagogy to support the future design of robots in education, in an effort to enhance learners' flourishing and pedagogical formation in educational contexts.
Lessons from Implementing Factors with Magnitude
Authors: Bench-Capon Trevor  , Atkinson Katie
Published: February 2025

We discuss the lessons learned from implementing a CATO style system using factors with magnitude. In particular we identify that giving factors magnitudes enables a diversity of reasoning styles and arguments. We distinguish a variety of ways in which factors combine to determine abstract factors. We discuss several different roles for values. Finally we identify the additional value related information required to produce a working program: thresholds and weights as well as a simple preference ordering.
Working Concurrently: Applying Ideas from Concurrency to a Working Life
Authors: Chalmers Kevin
Published: February 2025

Everyone is busy. No matter how much work you do, there always seems like there is more to do. Sometimes, we even seem to do nothing, spinning while we wait for someone else, or simply making no progress on our tasks. This presentation will show how we can take inspiration from computer science in general, and concurrency specifically, to help us organise our work. Concepts such as scheduling, context-switching, prioritisation, dependencies, logging, and time-slicing shall all be examined through the lens of personal effectiveness. The talk is a light-hearted one meant to inspire people into analysing their work practices, and is inspired by the book “Algorithms to Live By: The Computer Science of Human Decisions” by Brian Christian, but with a particular take from concurrency concepts.
A Transparent Thread and Fiber Framework in C++CSP
Authors: Chalmers Kevin
Published: February 2025

There are multiple low-level concurrency primitives supported today, but these often require the programmer to be explicit in their implementation decisions at design time. This work illustrates how a process-oriented model written in C++CSP can hide the underlying primitives from the programmer to allow M:N style thread support. The objective is to provide integrated kernel-level and user-level thread support in C++CSP without major changes to the process interface. To illustrate that kernel-level and user-level threads are working together two experiments have been undertaken. The first executes a stressed select to determine the cost of process-count scaling. The second experiment executes a scaling number of processes syncing across hardware to illustrate the sync-time cost as the number of user-level threads increases in each context. The results illustrate that it is possible to build M:N style thread support transparently for process design, and that doing so provides a significant increase in the number of active processes in library supported CSP while still taking advantage of multicore hardware.
CSP at the Cyber-Physical Edge
Authors: Michalik Lukasz Sergiusz  , Murphy Michael J.  , Bjørndalen John Markus  , Anshus Otto J.
Published: February 2025

Today, to do ground-based in-situ observations of the arctic tundra, researchers carry wild life cameras and other observation units into the field, manually configure the devices while on the arctic tundra, and fetch the collected data several months later. This approach does not scale. Instead, observing and reporting of data must be automated using a distributed wireless network of autonomous observation units.
Towards Automatic Program Specification Using SME Models
Authors: Thegler Alberte  , Larsen Mads Ohm  , Skovhede Kenneth  , Vinter Brian
Published: February 2025

This paper introduces a method to simplify hardware modeling and verification thereof in order for software programmers to, more easily, meet the demands of the growing embedded device industry. We describe a simple method for transpiling from the new SME Implementation Language into CSPMand using formal verification to verify properties within the generated program. We present a small example consisting of a seven segment display clock network and introduce how to verify the widths of the channels in the network.
Evaluating CSP as a Programming Model to Build Distributed Systems
Authors: Skovhede Kenneth  , Vinter Brian
Published: February 2025

In this paper we investigate the use of the CSP programming model for implementing distributed systems in an educational setting. For a practical example we choose a well-studied classic distributed system: a distributed hash table. We describe our implementation and compare it to a number of existing open-source implementations. We discuss a number of parameters for the example implementation, such as amount of code, potential for errors, and similar parameters.
Verifying Mobile Systems: Take Two
Authors: Peschanski Frédéric
Published: February 2025

This papers relates the design and development of two “proof of concept” analysis tools for the pi-calculus. The main functionality of the first tool, named PiExplorer, is to construct the state-space of a finitary pi-calculus process as a directed graph akin to a finite-state automaton. As counterintuitive as it may seem, this is a rather complex objective. The second tool is an implementation of the main pi-calculus features (especially name-passing) in the Promela language. This enables the use of the Spin model checker for the verification task. Although very different, these two prototypes share a common foundation: a notion of a stateful observer for pi-calculus processes. This is the central idea discussed in the paper.
Java, JCSP and Crew (The Strange Case of the Spurious Spurious)
Authors: Welch Peter  , Pedersen Jan Bækgaard  , Ewer Matthew  , Martin Jeremy M.R.
Published: February 2025

In this fringe presentation we prestent the current implementation of the CREW lock in JCSP and illustrate why the code added to hadle spurious wakeups is incorrect. We also propose a fix to correctly handle spurious wakeups.
Digital transformation and visual knowledge map analysis of intelligent factory for sensor information of Internet of Things
Authors: Wang Honglv , Shi Dingke , Zhang Chengting , Ding Nanzhe , Cheng Chao
Published: February 2025

Industry 4.0 is reshaping conventional factories into “smart factories” via the widespread use of IoT-enabled networks of linked devices, sensors, and software for process optimization and monitoring. Intelligent manufacturing facilities may employ IoT-based predictive maintenance to reduce downtime, increase equipment longevity, and avoid machine problems. Manufacturers may get real-time insights into energy consumption patterns, which is a major concern in the business. The primary objective is to optimize energy use during part manufacturing. Hence, this paper proposes the Internet of Things- Low-Power Wide-Area Network Model (IoT-LPWM) to monitor manufacturing and reduce energy consumption. The proposed method’s production status component uses visual Knowledge Map Analysis loaded with data from the edge device. A Low-power wide-area network (LPWAN) is the fundamental component of the suggested approach to industrial wireless communication. Using edge computing technology in LPWAN helps reduce computational complexity by shifting high-intensity processing to the periphery, where devices with computing resources are more readily available. Both the energy needed to process and store massive data and the likelihood of cyberattacks may be decreased with this method. The experimental results show that the IoT-LPWM provides useful information to help them make decisions and reduce energy consumption. The experimental results show that our proposed method IoT-LPWM achieves a high performance ratio of 97%, attack prevention ratio of 96.3%, energy management ratio of 93.8%, and data transmission ratio of 98.1% compared to other methods.
Application of automatic structured pruning method based on YOLO in power operation scenarios
Authors: Lin Shuang , Huang Jianye , Lin Chenxiang , Zheng Zhou , He Deming , Ma Teng , Wu Xinxin
Published: February 2025

The multi-scale object detection algorithm based on deep learning is a common method for safety monitoring in current power operation scenarios, which is of great significance to ensuring the safety of power operations. For certain power applications with high real-time requirements, the computational complexity of deep learning models may become a bottleneck. Deploying deep learning models requires high-performance hardware support, such as GPUs, which might not be easily achievable in some power field environments. According to the characteristics of common safety monitoring tasks in power operation scenarios, this paper proposes an automatic structured pruning method for multi-scale object detection algorithms. This method is designed for the safety monitoring of single and fixed-scale targets, effectively reducing the complexity of inference calculations and improving the frames per second (FPS) of real-time object detection without compromising accuracy. Furthermore, the proposed method can adaptively perform automatic structured pruning for targets of different scales. Experiments conducted using the YOLOv5 model demonstrate that the proposed method improves inference speed by approximately 20% for safety monitoring tasks without reducing detection accuracy.
Korelasi Pengetahuan, Sikap, dan Motivasi terhadap Perilaku Pengelolaan Sampah Berbasis Sekolah di Yogyakarta
Authors: Wijayanti Nor , Amyati Amyati
Published: February 2025

Latar Belakang: SMA Muhammadiyah 4 merupakan salah satu sekolah yang berada di kota Yogyakarta. Setiap hari terlihat pemandangan siswa yang suka membuang sampah tidak pada tempatnya. Hal ini mengganggu kebersihan lingkungan di sekolah. Kondisi ini seakan tidak menjadi masalah bagi warga sekolah, khususnya siswa. Hal ini terjadi karena belum optimalnya pengelolaan sampah di SMA Muhammadiyah 4 Yogyakarta. Penelitian ini dilakukan untuk mengetahui hubungan antara pengetahuan, sikap dan motivasi siswa dengan perilaku pengelolaan sampah berbasis sekolah di SMA Muhammadiyah 4 Yogyakarta.Metode: Penelitian ini dilakukan pada bulan Januari hingga Juni 2024 di SMA Muhammadiyah 4 Yogyakarta. Jenis penelitian ini adalah deskriptif kuantitatif. Teknik pengambilan sampel menggunakan total sampling. Sampel dalam penelitian ini adalah 55 siswi kelas XI IPS. Analisis kuantitatif menggunakan uji chi square.Hasil: Berdasarkan uji Chi-Square diperoleh korelasi antara pengetahuan dengan perilaku pengelolaan sampah (? value = 0,372 > 0,05). Hubungan antara sikap dengan perilaku pengelolaan sampah diperoleh (? value = 0,001 < 0,05). Hubungan antara motivasi dengan perilaku pengelolaan sampah diperoleh (? value = 0,000 < 0,05).Kesimpulan: Tidak ada hubungan antara pengetahuan dengan perilaku siswa dalam pengelolaan sampah berbasis sekolah di SMA Muhammadiyah 4 Yogyakarta, namun ada hubungan antara sikap dan motivasi dengan perilaku siswa dalam pengelolaan sampah berbasis sekolah di SMA Muhammadiyah 4 Yogyakarta.
Convergence of Computer Vision, AR, and Generative AI: A Novel Framework for Hyperscale Data Center Management
Authors: Venkata Sampath Kumar Mutharaju
Published: February 2025

This article presents an innovative framework integrating computer vision, augmented reality (AR), and generative AI technologies to revolutionize hyperscale Data Center management. The proposed system employs machine learning-based computer vision for automated asset identification and tracking, while AR overlays provide real-time maintenance guidance to non-technical personnel. Generative AI enhances the framework by enabling interactive troubleshooting and predictive analysis capabilities. The article demonstrates significant improvements in operational efficiency, reduced response times, and enhanced maintenance accuracy through this integrated approach. The article also explores implementation challenges and provides insights into scalability considerations for large-scale deployment. This article contributes to the growing body of knowledge in intelligent Data Center management systems and presents a novel approach to combining emerging technologies for improved infrastructure maintenance and operational reliability. The framework's ability to empower non-technical staff while maintaining high operational standards suggests promising applications across various scales of Data Center operations.
Dual Air-Conditioner Optimization : Intelligent Power Management Via Microcontroller
Authors: R. Thangasankaran  , Dr. S. Parthasarathy  , R. Hari Krishna  , M. Jai Philbert  , A. Dhanabalan
Published: February 2025

This proposed paper presents an innovative IoT-based solution for automating dual air conditioner operation, leveraging ESP32 microcontrollers, temperature sensors, and Wi-Fi communication. The system continuously monitors room temperature and automatically switches the air conditioner on or off based on predefined thresholds. This real-time temperature monitoring and automation enhance comfort, save energy, increase system reliability, and reduce maintenance. The system optimizes AC operation, detects anomalies, and prevents power overloads, making it an efficient and safe solution for dual AC units. By employing inrush current testing, the system can accurately detect anomalies and prevent power overloads, enhancing both safety and energy efficiency. The proposed system is a compact, low-cost, and user-friendly solution that can be easily integrated into existing air conditioning systems. This project demonstrates the potential of IoT technology in improving energy efficiency and automation in various applications. The system's effectiveness is validated through experimental results, which show significant energy savings and improved system reliability. The project's findings have important implications for the development of smart buildings and cities.