bluuebunny/crossref_metadata_2025 huggingface dataset:
Visualizations for Software Development Process Management
Authors: Lehtonen Timo  , Aho Timo  , Kuusinen Kati  , Mikkonen Tommi
Published: February 2025

Software development projects have increasingly been adopting new practices, such as continuous delivery and deployment to enable rapid delivery of new features to end users. Tools that are commonly utilized with these practices generate a vast amount of data concerning various development events. Analysis of the data provides a lightweight data driven view on the software process. We present an efficient way of visualizing software process data to provide a good overall view on the features and potential problems of the process. We use the visualization in a case project that has become more agile by applying continuous integration and delivery together with development and infrastructure automation. We compare data visualizations with information gathered from the development team and describe how the evolution can be understood through our visualizations. The case project is a good example of how a change from a traditional long cycle development to a rapid cycle DevOps culture can actually be made in a few years. However, the results show that the team has to focus on the process improvement continuously in order to maintain continuous delivery all the time. As the main contribution, we present a lightweight way to software process visualization. Moreover, we discuss how such a heuristic can be used to track the characteristics of the target process.
Laws Describing Artificial Learning
Authors: Brumen Boštjan  , Rozman Ivan  , Černezel Aleš
Published: February 2025

The power law is predominantly describing the ways humans learn, especially in psychophysics, in skill acquisition, and in retention. Yet a few researchers claim that this law is applicable only on the aggregate level and that exponential law should be considered when describing a single learning process. The question which law should be used on aggregate or single learner level has not yet been answered in the artificial learning community. This work is shedding some light towards the answers. We conducted an experiment with three artificial learners using 109 training cases. The statistical tests have shown that power law and exponential law are describing the learning curves equally well. However, in quite many cases neither of laws is applicable. Additionally, there are significant differences among artificial learners.
Exploring the Non-Trivial Knowledge Implicit in Test Instance to Fully Represent Unrestricted Bayesian Classifier
Authors: Li Mei-Hui  , Wang Li-Min
Published: February 2025

Restricted Bayesian classifiers have demonstrated remarkable classification performance for data mining. However, the restricted network structure makes it impossible to represent the Markov blanket of class variable, which corresponds to the optimal classifier. And the test instances are not fully utilized, the final decision thus may be biased. In this paper, a novel unrestricted k-dependence classifier is proposed based on identifying the Markov blanket of the class variable. Furthermore, the algorithm also adopts local learning to build local structure, which can represent the evidence introduced by test instance. 15 datasets are selected from the UCI machine learning repository for zero-one loss comparison. The experimental results indicate that the unrestricted Bayesian classifier can achieve good trade-off between structure complexity and prediction performance.
A Collaborative Filtering Recommendation Model Based on Fusion of Correlation-Weighted and Item Optimal-Weighted
Authors: Wen Shi-Qi  , Wang Cheng  , Wang Jian-Ying  , Zheng Guo-Qi  , Chi Hai-Xiao  , Liu Ji-Feng
Published: February 2025

Traditional collaborative filtering algorithm has a shortcoming—it assigns all items with equal importance, which can result in excessive frequency in recommending hot items and reduced novelty and accuracy. Thus, we propose a collaborative filtering recommendation model based on fusion of item correlation-weighted and optimal-weighted. First we use correlation-weighted method to find the best threshold which could ensure the stability of algorithm under the sparse condition. Then, we fusion the correlation-weighted method with item optimal-weighed strategy on the condition of selecting the optimal threshold. Targeting final mean absolute error (MAE) of collaborative filtering, we introduce the weight value in the prediction process to enhance the performance of mining items in which users are really interested. Theoretically, fusion model can effectively overcome the problem in traditional collaborative filtering algorithm, and combine the advantage of correlation-weighted and item optimal-weighted. Experiment results in MovieLens-100K data set show that MAE of the a collaborative filtering recommendation model based on fusion of item correlation-weighted and optimal-weighted is lower than traditional collaborative algorithm, item optimal-weight collaborative algorithm, correlation-weight collaborative algorithm and variance-weight collaborative algorithm. The model we proposed reduces the item average popularity, increases the coverage and improves the recall rate and more novelty is achieved.
Extending Full Text Search for Legal Document Collections Using Word Embeddings
Authors: Landthaler Jörg  , Waltl Bernhard  , Holl Patrick  , Matthes Florian
Published: February 2025

Traditional full text search allows fast search for exact matches. However, full text search is not optimal to deal with synonyms or semantically related terms and phrases. In this paper we explore a novel method that provides the ability to find not only exact matches, but also semantically similar parts for arbitrary length search queries. We achieve this without the application of ontologies, but base our approach on Word Embeddings. Recently, Word Embeddings have been applied successfully for many natural language processing tasks. We argue that our method is well suited for legal document collections and examine its applicability for two different use cases: We conduct a case study on a stand-alone law, in particular the EU Data Protection Directive 94/46/EC (EU-DPD) in order to extract obligations. Secondly, from a collection of publicly available templates for German rental contracts we retrieve similar provisions.
Scholarly Digital Libraries as a Platform for Malware Distribution
Authors: Nissim Nir  , Cohen Aviad  , Wu Jian  , Lanzi Andrea  , Rokach Lior  , Elovici Yuval  , Giles Lee
Published: February 2025

Researchers from academic institutions and the corporate sector rely heavily on scholarly digital libraries for accessing journal articles and conference proceedings. Primarily downloaded in the form of PDF files, there is a risk that these documents may be compromised by attackers. PDF files have many capabilities that have been widely used for malicious operations. Attackers increasingly take advantage of innocent users who open PDF files with little or no concern, mistakenly considering these files safe and relatively non-threatening. Researchers also consider scholarly digital libraries reliable and home to a trusted corpus of papers and untainted by malicious files. For these reasons, scholarly digital libraries are an attractive target for cyber-attacks launched via PDF files. In this study, we present several vulnerabilities and practical distribution attack approaches tailored for scholarly digital libraries. To support our claim regarding the attractiveness of scholarly digital libraries as an attack platform, we evaluated more than two million scholarly papers in the CiteSeerX library that were collected over 8 years and found it to be contaminated with a surprisingly large number (0.3%–2%) of malicious scholarly PDF documents, the origin of which is 46 different countries spread worldwide. More than 55% of the malicious papers in CiteSeerX were crawled from IP's belonging to USA universities, followed by those belonging to Europe (33.6%). We show how existing scholarly digital libraries can be easily leveraged as a distribution platform both for a targeted attack and in a worldwide manner. On average, a certain malicious paper caused high impact damage as it was downloaded 167 times in 5 years by researchers from different countries worldwide. In general, the USA and Asia downloaded the most malicious scholarly papers, 40.15% and 27.9%, respectively. The top malicious scholarly document downloaded is a malicious version of a popular paper in the computer forensics domain, with 2213 downloads in a worldwide coverage of 108 different countries. Finally, we suggest several concrete solutions for mitigating such attacks, including simple deterministic solutions and also advanced machine learning-based frameworks.
A Deep Convolutional Neural Network for Anomalous Online Forum Incident Classification
Authors: Pomponiu Victor  , Thing Vrizlynn L.L.
Published: February 2025

Web forums are a frequent way of sharing useful information among people. They are becoming the main source of up-to-date information and marketplaces pertaining to different domains, including criminal content and zero-day security exploits. Analyzing the web forums of the existing discussion threads is an alternative method to understand the exploits and fraud modalities a law breaker will most likely make use and how to defend against them. However, in many cases, it is hard to capture all the relevant context of the forums which is needed for classification. In this paper, we introduce a data-driven technique to mine the web forums and provide policy recommendations to the defender. A neural network (NN) is used to learn the set of features for forum classification. Furthermore, we present the evaluation and results from employing our method, with various system configurations, on real-world datasets collected form the web.
Review on Higher-Order Neural Units to Monitor Cardiac Arrhythmia Patterns
Authors: Martinez Molina A.  , Rodriguez Jorge R.  , Villa-Angulo R.  , Bila J.  , Mizera-Pietraszko J.  , Torres Arguelles S.
Published: February 2025

An electrocardiogram (ECG) is a non-invasive technique that checks for problems with the electrical activity of a patient's heart. ECG is economical and extremely versatile. Some of its characteristics make it a very useful tool to detect cardiac pathologies. The ECG records a series of characteristic waves called PQRST; however, the QRS complex analysis enables the detection of a type of arrhythmia in an ECG. Technological developments enable the storage of a large amount of data, from which knowledge extraction is impossible without a powerful data processing tool; in particular, an adequate signal processing tool, whose output provides reliable parameters as a basis to make a precise clinical diagnosis. Thus, ECG signal processing creates an opportunity to analyze and recognize possible arrhythmia patterns. This paper reviews the use of artificial neural networks (ANNs) to detect and recognize cardiac arrhythmia patterns. Recurrent neural networks (RNNs) and higher-order neural units are inspected. In addition, the potentials of using higher-order neural units such as the quadratic dynamic neural unit (D-QNU) and dynamic cubic neural unit (D-CNU) for cardiac arrhythmia detection are analyzed.
Objects Detection Based on Multi-BING Feature Model
Authors: Su Yue  , Chen Mianshu  , Sang Aijun  , Li Xiaoni  , Li Mengying
Published: February 2025

Objects detection is not only an important research direction in computer vision, but also the basis of object tracking and behavior detection. In this paper, we analyze the characteristics and principles of Binarized normed gradients (BING) algorithm, and propose an objects detection algorithm based on multi-BING feature model. At first, the proposed algorithm uses K-means clustering algorithm to cluster the training data, and then trains each category of images to establish the corresponding BING feature model. At the detection stage, multiple BING feature models are respectively used for testing. We collected all the detected results from all models as the final detection results. Experimental results demonstrate that the proposed algorithm effectively improves the object detection rate (DR) under various overlaps at the expense of a small amount of time by generating a small set of high-quality proposals.
The Influence of Using XBRL on Quoted Company's Information Quality
Authors: Yang Yu-chen  , Chen Yan-li  , Wang Lei  , Tang Chen
Published: February 2025

Due to the Extensible Business Reporting Language (XBRL) have high compatibility and other features, it is widely used in finance field, as an information disclosure and retrieval tool in the Shanghai and Shenzhen Stock Exchange at present. This article mainly uses normative research and empirical research to discuss the influence of XBRL on quoted accounting information quality. Firstly, this article theoretically discusses the positive effect on the relevance and reliability of quoted company's accounting information, which based on XBRL standard. This article brings into the concept of earnings response coefficient in the process of empirical research, and uses event study method to research the reaction degree of market excess return on unexpected factors of company's financial report. This article uses stratified sampling to select annual report disclosure information of 501 quoted companies in the Shanghai stock market from 2012 to 2015 and uses these samples to do empirical research. The results are as follows, unexpected accounting surplus has positive correlation with earnings response coefficient; the persistence of company surplus has positive correlation with earnings response coefficient; the growth rate of company has positive correlation with earnings response coefficient; the risk variation of company has positive correlation with earnings response coefficient. From the western accounting theory perspective, the earnings response coefficient is larger and the higher of accounting information quality. From the empirical research, to some extent, the implementation of XBRL made a positive effect on our country's quoted company's accounting information quality.
Implementation and Adoption of E-HRM in Small and Medium Enterprises of Pakistan
Authors: Waheed Abdul  , Waheed Salma  , Karamat Jawad  , Ahmad Naveed  , Majeed Abdul
Published: February 2025

The purpose of this study is to investigate the predictors of e-HRM implementation in Small medium enterprise (SMEs) in manufacturing sector. Three main predictors including conventional HRM practices, availability of resources and employees attitude towards e-HRM were analyzed. Data was collected through a questionnaire survey and 500 employees participated in this survey. Results reveal that e-HRM heavily depends on employee attitude towards e-HRM and availability of resources. Conventional HRM practices including training and development, compensation and benefits, and performance appraisal also have an important role. The readiness of implementing e-HRM practices in small and medium enterprises heavily dependent on expertise, financial and technical resources. This study will help managers to develop strategy for effective implementation of e-HRM in Small medium enterprises (SMEs) in manufacturing sector.
Automated Extraction and Modeling of Calcifications and Blood Stream Volumetric Parameters
Authors: Kubicek Jan  , Penhaker Marek  , Ondraczka Tomas  , Machacek Zdenek  , Cerny Martin  , Augustynek Martin  , Maresova Petra
Published: February 2025

Paper deals with a complex analysis of the blood vessels system. Clinical examination of blood vessels is usually carried out by imaging systems. Unfortunately, clinical software tools often do not offer further image post-processing allowing for the modeling blood vessels structures. Parameters bringing an objectification of the blood vessels state would significantly contribute to proper assessment. Firstly, we propose a system intended for the modeling and extraction of calcification spots on the base of the fuzzy thresholding method with consequent incorporating the spatial information. Blood vessel model, in result, offers a differentiation of the calcification spot from physiological blood vessel. Second part of the analysis deals with the segmentation method estimating volumetric parameters of the blood vessels. This model is intended for estimation of blood flowing in the blood vessels. This approach is intended for a verification of the blood flowing quantification before/after stent application.
Automated Characterization of Breast Cancer Using Steerable Filters
Authors: Fujita Hamido  , Raghavendra U.  , Gudigar Anjan  , Vadakkepat Vinoy Vishnu  , Acharya U. Rajendra
Published: February 2025

Breast cancer is one of the highly researched topic in medical image analysis. Digital mammogram analysis is one of the techniques which helps in determining severity of breast cancer within the context of medical image analysis. In this work, a novel technique using steerable co-occurrence features and the independent component analysis (ICA) is proposed. Our method is evaluated using 1000 mammogram images and can efficiently classify normal, benign and malignant classes with a promising performance of 88.60% accuracy, using only ten features. The proposed method is completely automatic and it does not require any segmentation technique in the breast region.
Introduction to SinJAR (a New Tool for Reverse Engineering Java Applications) and Tracing Its Malicious Actions Using Hidden Markov Models
Authors: Fattahi Jaouhar  , Mejri Mohamed  , Ziadia Marwa  , Pricop Emil  , Samoud Ouejdene
Published: February 2025

In this paper, we are proposing a new tool for reversing Java applications called SinJAR. SinJAR is a lightweight software written in Java aiming at inspecting bytecode at compile time and producing the structure tree of a targeted application. Besides, it is able to detect vulnerabilities and security weaknesses inside the Java code. SinJAR can be used for two purposes. The first one is sane and consists in using it to verify whether or not an application is safe and compliant with its specification. The second one is malicious and consists in spying applications through their bytecode and exploiting vulnerabilities that they may enclose. In this paper, we will show how to detect SinJAR malicious actions after showing the capabilities of the tool through few ad hoc attack scenarios conducted in a real military context.
Towards a Formal Verification Approach for Service Component Architecture
Authors: Chargui Wael  , Sakka Rouis Taoufik  , Kmimech Mourad  , Bhiri Mohamed Tahar  , Sliman Layth  , Raddaoui Badran
Published: February 2025

Service Component Architectures (SCA) is widely used for the integration of heterogeneous applications. This heterogeneity, added to the distributed aspect of SCA, can be a source of behavioral mismatches. In this paper, we present a new approach for behavioral verification of SCA software architectures. More precisely, we propose a translation of a SCA source model to a Wright ADL configuration. In order to facilitate this translation, a guiding script and translation rules are introduced. Then, by using the wr2fdr tool, the translation of this wright configuration to a CSP specification is done. Finally, the FDR2 model-checker simulates and checks the obtained specification.
Towards a Formal Verification Approach for Cloud Software Architecture
Authors: Ayach Amal  , Sliman Layth  , Kmimech Mourad  , Bhiri Mohamed Tahar  , Raddaoui Badran
Published: February 2025

Behavioral consistency of cloud architectures is one of the pivotal challenges in cloud computing. In this paper, we propose a new approach for checking the behavioral consistency of the topology and orchestration of cloud computing. To do so, we choose TOSCA language in order to describe the cloud application. Then, we exploit the Wright ADL that encompasses the CSP language to check the consistency of cloud architectures using FDR2 model-checker.
Facial Expression Recogntion in Unconstrained Environment
Authors: Hernandez-Matamoros Andres  , Nagai Takayuki  , Attamimi Muhammad  , Nakano Mariko  , Perez-Meana Hector
Published: February 2025

The facial expression recognition has been a topic of active researches given a result the proposal of several efficient algorithms; however, in most cases they remain limited to controlled conditions situations. In this study, we tackle the challenge of recognizing emotions through the facial expression into activities in-the-wild adding the accuracy rate for each expression. To this end we an algorithm that allows accurate face expression recognition in an uncontrolled environment, that means different kind of illumination, backgrounds, occlusions, face's profiles, etc. Proposed system firstly detects different profile of face (left, frontal and right), Then it uses only the frames in which the face profile is frontal, in the next step the face regions of interest (ROI) are segmented automatically to carry out the feature extraction. We use a classifier based on clustering, it has the advantage that if a new class (emotion) is added, it is not necessary to train this completely. Proposed system was evaluated using short video clips of several pictures together with description sentences describing the main activity in the video. The evaluation results show that the proposed scheme is able to recognize the face's profiles with the recognition rate to approximately 93% and principal emotions in unconstrained video sequences.
Comparing Qualitative Descriptors with Different Granularities and Reference Systems
Authors: Falomir Zoe  , Museros Lledo  , Sanz Ismael  , Luque Amalia  , Gonzalez-Abril Luis
Published: February 2025

How set theory and interval distances can be combined to compare qualitative concepts defined on reference systems at different levels of granularity is studied in this paper. A measure of similarity to compare qualitative concepts and reference systems is presented and implemented using first order logics. A case study with different angle descriptors is used for testing and promising results are obtained.
Social Sensorimotor Contingencies: Towards Theory of Mind in Synthetic Agents
Authors: Sánchez-Fibla Martí  , Moulin-Frier Clément  , Arsiwalla Xerxes  , Verschure Paul
Published: February 2025

A first step to reach Theory of Mind (ToM) abilities (attribution of beliefs to others) in synthetic agents through sensorimotor interactions, would be to tag sensory data with agent typology and action intentions: autonomous agent X moved an object under the box. We propose a dual arm robotic setup in which ToM could be probed. We then discuss what measures can be extracted from sensorimotor interaction data (based on a correlation analysis) in the proposed setup that allow to distinguish self than other and other/inanimate from other/active with intentions.
Iterative AWC for Distributed SAT
Authors: Giráldez-Cru Jesús  , Lee Jimmy H.M.  , Meseguer Pedro
Published: February 2025

Traversing large search spaces can be done more efficiently by exploiting the dead-ends –in formal terms nogoods– discovered during search. If a previously found nogood appears again, the search process can avoid it, saving some search effort. Storing all found nogoods may require exponential memory, which is unaffordable. However, current memories allow to store a large set of nogoods, to be maintained during the solving process. In many cases, a solution is found before memory is exhausted. In the context of Distributed Constraint Satisfaction, the AWC algorithm allows to compute a solution quickly but, to guarantee completeness, it requires storing all found nogoods. Trading space per time, we develop a new iterative version of the algorithm that delays the exponential effects. We present this new version in the context of distributed SAT, where agents hold several Boolean variables. Taking advantage of existing SAT technology, this version perform calls to external MaxSAT solver. Experimentally, we confirm the benefits of the proposed approach on several benchmarks.
Consumer perspectives on product lifetimes: a national study of lifetime satisfaction and purchasing factors
Authors: Gnanapragasam A.  , Cooper T.  , Cole C.  , Oguchi M.
Published: February 2025

The extension of product lifetimes of consumer goods has the potential to encourage sustainable consumption, reduce carbon emissions and facilitate a transition to a circular economy. However, current understandings of consumer perspectives on product lifetimes are limited. This paper presents the findings of the first national study of consumer satisfaction with product lifetimes across an exhaustive range of consumer durables. The research was undertaken in the United Kingdom where consumer satisfaction and purchasing factors were studied across eighteen product categories. These product categories were devised from academic and market research undertaken at Nottingham Trent University. In total, 2,207 participants completed the survey and the sample profile was similar to the United Kingdom's population with respect to age and gender. The results indicate that consumers appear generally satisfied with the lifetimes of their products and suggest that efforts to extend product lifetimes should focus on developing business and policy options. However, participants also emphasised that longevity, reliability and guarantee length were important factors in their purchasing decisions. Consumer interest in these factors could indicate that lifetime labelling and the promotion of longer guarantees by manufacturers and retailers may offer pathways to reduce energy and material consumption associated with short-lived products, facilitating movement towards a low carbon circular economy.
Intelligent disassembly of components from printed circuit boards to enable re-use and more efficient recovery of critical metals
Authors: Kopacek B.
Published: February 2025

Based on previous experiences in intelligent disassembly of components from printed circuit boards our goal was to develop an economic solution for reducing the amount of material for the later hydrometallurgical recovery process and to recognize reusable parts on printed circuit boards. Usually the hydrometallurgical recovery process is very time consuming and therefore the recovery rate still relatively low. Therefore, it is beneficial to enrich the content of critical metals in the input fraction by extracting only those components from printed circuit boards that are rich in the target metals (e.g. tantalum, rare earth, platinum group metals).
Use phase of wool apparel: a literature review for improving LCA
Authors: Laitala K.  , Klepp I.G.  , Henry B.
Published: February 2025

This paper presents results from a literature review on use phase of clothing with focus on wool. The aim of the review is to study if there is empirical grounding for assuming that the use phase is different for clothes made of different fibres, and if this information could be used in modelling the use phase. We will answer this question based on studies on wool, and see if use of woollen garments gives different environmental impact than use of garments made of other fibres.
Operationalizing contextmapping as a means for increment of product durability in kitchen utensils design
Authors: Mahmoudi A.  , Azhdari A.
Published: February 2025

Increasing products lifespan is a strategy for a greener and more sustainable future. From a societal vantage point, disposing or discarding products results into consumerism with mountains of waste. Kitchen utensils, regarding their high frequency of usage, are not exceptions of this matter and their design, alongside with their material quality, specify their longevity factor. User-product interaction plays a major role for the design of products which would last longer, whether emotionally or functionally. There are many products which due to poor physical interaction design, destined to breakage, disposal or discardment. In this study, one of the popular tools in participatory design was used to elicit firstly, deep layers of user-product interaction in an authentic environment (like daily routine life), and secondly evaluate the possibility of engaging users in the design process for this rubric. Contextmapping is originally developed to discover latent needs and tacit knowledge of users and in this study, with minor modifications derived from semiotics, context mapping with the goals of product durability was used to find its viability in user-product interaction and glean design principles on product longevity from an actual product-user.
Implementing “preparation for re-use” in WEEE management: an analysis of the European experience & recommendations for Ireland
Authors: McMahon K.  , Fitzpatrick C.  , Johnson M.
Published: February 2025

Proper treatment of waste plays an important role in global concerns regarding resource efficiency and climate change. Waste electrical and electronic equipment (WEEE) is of particular importance due to high use of critical resources and production/recycling energy as well as the potential for toxic pollution when improperly disposed of. Preparation for re-use plays an important role in alleviating these issues.
Towards a typology of waste in fashion practice: an Australian perspective
Authors: Payne A.  , Binotto C.
Published: February 2025

Waste in fashion is a material problem as well as a cultural condition. In this paper we offer a cultural perspective on waste transformation in fashion practices: what happens to waste, rather than where it goes. We propose states of transformation of waste: disguise, elevation and enchantment. These states are not a hierarchy but rather a typology to consider the kinds of material and cultural transformations that waste undergoes when revalorised through fashion practice. The study centres on the Australian context, and seeks to examine the ways in which Australian fashion retailers, designers, and community groups are engaging with clothing and textile waste. We identified forty-seven initiatives and explored their approaches to waste transformation. Through selected vignettes, this paper examines both the material processes and symbolic meaning behind the approach and its messaging, and offers reflections on the ideas of waste that emerge. Selected examples include large fashion retailers, independent and experimental fashion practitioners, and grassroots campaigns by local charities. Looking beyond the practical approaches to waste management, such ‘reduce, reuse, recycle,’ or the waste hierarchy, we explore ways in which these practices may ‘disguise’ waste, ‘elevate’ waste, or ‘enchant’ waste. Through this analysis, we argue for a perception of waste beyond that of inevitable by-product of the industry, towards waste recast as a potent force of loss and renewal.
Product policy and material scarcity challenges: the essential role of government in the past and lessons for today
Authors: Peck D.P.  , Bakker C.A.  , Kandachar P.V.  , de Rijk T.
Published: February 2025

Materials are important in economies, business, innovation activity and products, and they have quickly become essential to maintain and improve our quality of life. The world faces problems concerning material supply, but these concerns are not translated into product design activity, even though history shows that product design policy can play an important role in finding solutions to materials problems. This paper has a focus on the role of governmental policy in ensuring material availability to the state.
Do ecolabels extend product service times? An analysis of the product group specific criteria of the European Union and Nordic ecolabels
Authors: Suikkanen J.  , Nissinen A.
Published: February 2025

Ecolabels are an established means of guiding consumer choices towards product and service options with better environmental performance. The life cycle approach based award criteria of ISO Type I product-specific ecolabels aim to steer the product into the market in an environmentally less harmful direction. In this paper, we present an analysis of Product Group Specific Criteria Documents of two ISO Type I Ecolabelling Schemes: the Nordic Ecolabel and the EU Ecolabel. The examination of the product group specific criteria documents indicates that requirements on durability, upgradability and reparability can well be set, and are already included in ecolabel requirements. While durability is already present the criteria for a variety of different product groups, upgradability and reparability are currently required for fewer products, such as computers and televisions mentioned above. Future revisions of product-specific criteria set present an opportunity to apply circular economy relevant requirements on upgradability and reparability in a broader suite of product groups. Further research on product life spans of ecolabelled products is needed.
Over the hill? Exploring the other side of the Rogers innovation diffusion model from a consumer and business model perspective
Authors: Wells P.  , Nieuwenhuis P.
Published: February 2025

The Rogers model of innovation diffusion has long featured in accounts of the penetration of new product technologies into society (Rogers, 2003). The contention in this paper is that this model is in fact only half complete, for it deals exclusively with the uptake of new technologies rather than their retention or abandonment. Taking the Rogers model as a point of departure, this paper seeks to characterize consumers who retain technologies, then identify business models designed for those consumers.
Classifying circular business models: a practice-based review
Authors: Whalen K.
Published: February 2025

Business models have a crucial role to play in the transition to a circular economy. Circular business model innovation provides an arena for studying the creation of such circular business models and enables companies the possibility to identify new value creation opportunities, such as capitalizing on embedded value of products over multiple lifecycles. In comparison with the trajectory of traditional business model innovation literature, circular business model innovation is underdeveloped, and this paper aims to make a contribution to the ongoing theoretical discussion. Through review and categorization of 140 circular business model case examples, this paper makes a first attempt to verify previous literature and unify academic and industry understanding of circular business models. The findings are expected to be useful in advancing the field of circular business model innovation and assisting practitioners in the design and development of new circular business models. While the results suggest convergence around three circular business model types: ‘Access/Performance Model’, ‘Extending Product Value’, and ‘Extending Resource Value’, other previously identified circular business model types should not be discounted.
Impact on resource intensity from consumer disposition: Relationship with product lifetime and disposal
Authors: Yamamoto H.  , Murakami S.
Published: February 2025

Sustainable resource use is a key challenge for our global society, and consumers are certainly responsible for making our resource use more efficient, e.g. by longer use of products and handing their End-of-Life products (EoLs) in to appropriate recyclers. Product lifetime can be one essential sustainable consumption intensity indicator to measure how much value the consumer extracts from a product. We have investigated the relationship between lifetime of electrical and electronic equipment (EEE) as well as EoLs destinations and consumer dispositions through a quantitative survey questionnaire amongst consumers in Japan. We identified three dispositions; well-organized, trend-conscious and community participation. All of these dispositions had non-negligible influences on both lifetime and EoLs destinations. The consumer groups with bigger potentials to improve resource intensity in terms of lifetime and of EoLs destinations were different. Policy makers can set two different policies to two different groups, and both policies will have positive impacts independently.
Preserving objects, preserving memories: repair professionals and object owners on the relation between memories and traces on personal possessions
Authors: Zijlema A.  , Van den Hoven E.  , Eggen B.
Published: February 2025

Traces of ageing and use on the material of products, and memories associated with products, have been found to contribute to product attachment and can stimulate product longevity. We present findings of a qualitative study that focused on the relation between traces of ageing and use on personal possessions and memories and the effects of repair on objects. With this research, we intended to increase our understanding of the role of traces on personal possessions and memories. We interviewed five professionals at their workplace who worked as a restorer or did repairs of personal possessions, and five owners of a repaired or restored possession. The motivations for bringing an object for repair were not only related to the deteriorating condition of the object but were also triggered by situational events or circumstances, such as passing on ownership or knowing someone who could repair the object. We found five different categories of traces among the possessions of the interviewed object owners: Traces of use, traces of ageing, traces of repair, traces of accidents and alterations. We found that objects gained meaning after the repair. When object owners or repair professionals decided not to repair traces, it was often for aesthetical and reminding reasons, but also because it may be how the owner remembered the object. Traces can cue associations to their use in the past, and also to the (imagined) history of the objects. These findings indicate that repair can enhance the cueing of memories and that preservation of meaningful traces may contribute to attachment.
Assessing the sharing economy: analyzing ecologies of business models
Authors: Boons F.  , Bocken N.
Published: February 2025

Current attempts to improve the ecological and social impact of production and consumption practices build on the recognized relevance of business models. Business models are distinct ways of coordinating the provision of goods and services, and they affect the ecological impact and social sustainability of the technologies underlying that provision. This is especially true for so-called sharing business models focused on peer-to-peer-based activities of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services.
Repair vs. replacement: what is the best alternative for household small electric and electronic equipment?
Authors: Bovea M.D.  , Ibáñez-Forés V.  , Pérez-Belis V.
Published: February 2025

This study presents a methodology designed for selecting, from an environmental point of view, the best end-of-life strategy for electric and electronic equipment which breaks before the end of its life span. For that, the environmental impact of the life cycle of the equipment is evaluated considering two alternative end-of-life strategies: repair & reuse or replacement. The Life Cycle Assessment methodology is applied to evaluate the environmental performance of each scenario, taking ReCiPe as end-point impact assessment method. The methodology is applied to a representative sample of nine categories of small household electrical and electronic equipment, considering different types of repair for each category and the replacement of the equipment in different years of its lifespan. For all the analyzed categories, the repair & reuse strategy generally proved environmentally better performance than replacement. However, for some types of repairs, e.g., those related to engines or printed circuit boards, if they occur in later product life cycle stages, it is better to replace equipment as the environmental impact from their repair operations is so high than it does not compensate prolonging the years of useful life obtained.
New product development and testing strategies for clothing longevity: an overview of a UK research study
Authors: Cooper T.  , Oxborrow L.  , Claxton S.  , Goworek H.  , Hill H.  , McLaren A.
Published: February 2025

Many garments have short life-spans, contributing to excessive carbon emissions, water consumption and waste. This paper reports on a research project which aimed to identify expectations of clothing longevity, examine the NPD process within the supply chain and identify opportunities for change, evaluate the potential for innovative technologies and improved product testing, and explore business practices aimed at more sustainable approaches to NPD. The paper provides an overview of the two-year project, presenting key findings from data collection that included interviews with 31 industry practitioners, three consumer focus groups, three industry and consumer round tables, an expert workshop, and four pilot actions undertaken with UK clothing retailers to evaluate key issues. The research identified and explored themes relating to NPD that could enable increased garment lifetimes, which were consolidated into six areas: the adoption of advanced textile processes and finishing techniques, action to overcome constraints on appropriate product testing, the potential for retailers to influence consumer behaviour, a loss of technical expertise and lack of multi-disciplinary collaboration, failure to embed good practice early in the NPD process, and evidence to encourage retailers and brands to adopt new business models. Industry and government policy recommendations were proposed to improve knowledge-sharing, strengthen the business case and influence consumer behaviour, while further research may be needed on the adoption of new garment and textile technologies, the business case and the global context of the clothing industry.
LoSe ODP – An Ontology Design Pattern for Logistics Services
Authors: Glöckner Michael  , Ludwig André
Published: February 2025

Logistics is a service-oriented industry. Trends like outsourcing and concentration on core competencies require logistics service providers to collaborate with each other and compose their services in order to fulfill complex customer demands. The idea of generic logistics service building blocks helps to make composition of logistics services more easy in general. The composition of logistics services from different providers is a challenging task due to the semantic gap of differing wordings, descriptions and IT-systems. With a central ontology design pattern for such logistics service building blocks, the semantic gap can be closed. Data and information (of services) from different providers can be made available, linked and interchanged easily within the network. Virtualized resources and digitalized collaboration are supported and the disruptive paradigm of cloud logistics is enabled.
A Spatiotemporal Extent Pattern based on Semantic Trajectories
Authors: Krisnadhi Adila  , Hitzler Pascal  , Janowicz Krzysztof
Published: February 2025

While the concept is certainly not new to ontology modeling, we have not been able to identify a published pattern on the fundamental notion of spatiotemporal extent, which captures the dimensions of things as they move through space and time. We present such a pattern, based on an already published pattern for semantic trajectories.
An Ontology Design Pattern for Supporting Behaviour Arbitration in Cognitive Agents
Authors: Asprino Luigi  , Nuzzolese Andrea Giovanni  , Russo Alessandro  , Gangemi Aldo  , Presutti Valentina  , Nolfi Stefano
Published: February 2025

In this chapter we present an Ontology Design Pattern for the definition of situation-driven behaviour selection and arbitration models for cognitive agents. The proposed pattern relies on the descriptions and situations ontology pattern, combined with a frame-based representation scheme. Inspired by the affordance theory and behaviour-based robotics principles, our reference model enables the definition of weighted relationships, or affordances, between situations (representing agent's perception of the environmental and social context) and agent's functional and behavioral abilities. These weighted links serve as a basis for supporting runtime task selection and arbitration policies, to dynamically and contextually select agent's behaviour. The pattern is at the heart of the behaviour-based cognitive approach adopted in the EU H2020 MARIO project for the design of an autonomous service robot (i.e., the cognitive agent) to support elderly people with cognitive impairments.
A Fuzzy Logic-Based Model for Heterogeneous Pedestrian Dynamical Behaviors
Authors: Xue Zhuxin  , Fan Xiangtao  , Jin Qingwen  , Jian Hongdeng  , Liu Jian
Published: February 2025

A number of approaches have been presented to simulate heterogeneous pedestrian dynamical behaviors. However, most of the existing models are developed based on the assumption that the perception and decision-making of human in real time can be described using precise values. In this paper, a new approach which incorporates personality trait model with fuzzy logic theory to generate heterogeneous crowd behaviors is proposed. To reveal the influence of individual personality traits in crowd behaviors, we establish a model based on multi-agent system in which each virtual human is referred to as an agent. Then, we derive a fuzzy logic-based mapping between behavior parameters and personality descriptors corresponding to the well-established OCEAN personality model. Finally, a variety of simulation experiments were implemented. Experimental results show that the proposed approach can exhibit more reasonable and heterogeneous behaviors in various scenarios, which can improve the believability of simulation and analysis how different personalities influence the crowd phenomena.
Research on Curriculum Vitae (CV) Mining
Authors: Wang Xuefang
Published: February 2025

The information in the CV can be considered as a chronological sequence of events. Given this sequential features of the staff resume information, we develop CV mining to find out the regular patterns among the behavior patterns of the employees and the events in their CV data to provide decisions for supporting the human resource management and service
Photo Sharing Service for Recommending Sightseeing Places
Authors: Takano Kosuke  , Hussaya Saengaroon  , Nanyakorn Im-oep  , Shibamoto Eriko  , Chen Xing
Published: February 2025

In a world where taking photos has become a daily behavior to most people, it is deemed that a photo sharing service has the strong potential to recommend desirable sightseeing places for the majority of travelers. There is much research on location recommendations and route suggestions for sightseeing based on check-in frequency to extract the popularity of a location, which is used to infer a user's interest in a place. However, the popularity of a location is not sufficient for the location recommendation, and user's preferences in a place cannot be extracted using only the check-in frequency. In this study, we propose a recommendation system for sightseeing places based on user's photo-taking behavior, where a large amount of photo data can be classified into five genres: scenery, architecture, nature, activity, and food. These data are leveraged to recommend popular sightseeing places according to a user's preference that is extracted from the user's photo-taking behavior. In the experiment, we test the classification capability of CNN (Convolutional Neural Network) in deep learning for five genres of photo data that we collected using smartphones. The proposed system could be realized by incorporating CNN as a photo classifier into our photo sharing service to recommend sightseeing places.