bluuebunny/crossref_metadata_2025 huggingface dataset:
Music Information Retrieval: From Signals to Meaning; from Classical Music to Flamenco
Authors: Gómez Emilia
Published: February 2025

In this talk I will provide an overview of my research in the field of Music Information Retrieval (MIR), which tries to understand the way humans describe music and emulate these descriptions by computational models dealing with big music data. By integrating knowledge from signal processing, music theory, cognition and artificial intelligence, we have developed methods to automatically describe music audio signals in terms of melody, tonality and rhythm; to measure similarity between pieces and automatically classify music according to style, emotion or culture. Over the last years, we have focused on two different application contexts. On one hand, we try to innovate the way we experience classical music concerts. On the other hand, we research on the computational modeling of flamenco music, improving current techniques for singing voice description and style classification.
Robots and Human Sociality: Normative Expectations, the Need for Recognition, and the Social Bases of Self-Esteem
Authors: Laitinen Arto
Published: February 2025

It has been argued that human sociality has an intrinsically normative grammar: not only do norms guide our own behaviour, we have normative expectations concerning the way others behave, including how they take and treat us. These expectations shape our experiences concerning the social world. This paper explores three theses: 1) The normative grammar need not be a matter of “commitments”. 2) While we need to operate in the “intentional stance” in interaction with robots, to implement a fully “personifying” stance would be a category mistake. Social robots form a new category, new vaguely demarcated “social grammar”, with genuine normative expectations and experiences. Rewarding experiences caused by responses from robots need not be deceptive, although taking a fully “personifying stance” would be deceptive: the dichotomy between full persons and mere things is too coarse. 3) Recognition from others is central in the social basis of self-esteem. Feedback from robots is an interesting combination of objective non-social feedback and some kind of simulated recognition: robots can send real recognitive messages even when they themselves are not recognizers.
Automatic Distribution of Local Testers for Testing Distributed Systems
Authors: Vain Jüri  , Halling Evelin  , Kanter Gert  , Anier Aivo  , Pal Deepak
Published: February 2025

Low-latency systems where reaction time is primary success factor and design consideration, are serious challenge to existing integration and system level testing techniques. Modern cyber physical systems have grown to the scale of global geographic distribution and latency requirements are measured in nanoseconds. While existing tools support prescribed input profiles they seldom provide enough reactivity to run the tests with simultaneous and interdependent input profiles at remote front ends. Additional complexities emerge due to severe timing constraints the tests have to meet when test navigation decision time ranges near the message propagation time. Sufficient timing conditions for remote online testing have been proposed in remote Δ-testing method recently. We extend the Δ-testing by deploying testers on fully distributed test architecture. This approach reduces the test reaction time by almost a factor of two. We validate the method on a distributed oil pumping SCADA system case study.
The Organization of Topics Sequence in Adaptive e-Learning Systems
Authors: Vagale Vija  , Niedrite Laila
Published: February 2025

The research presented in this article is about acquisition opportunities of a personalized topic sequence in terms of some study course in the adaptive e-learning system. The method to organize acquisition of the course topic sequence that helps a learner to organize learning process by creating a sequence for course topic acquisition adapted to personal needs and knowledge is offered in the article. The method can be used in an open-source learning management system with a structure of learning course topics. There are three topic choice opportunities offered for the learning course acquisition: teacher, learner, and optimal one. The teacher-indicated topic acquisition sequence is based on teacher's pedagogical experience. Learner's free choice of topics is based on links that are indicated between topics by the course creator. The optimal topic sequence for a specific course is obtained by using an optimal method for topic sequence acquisition described in the paper. The article covers an experiment where learners have an opportunity to manage their learning process on their own by using a teacher-offered topic sequence, by choosing learning topics on their own, or by using system-offered optimal topic sequence that is created for a specific course. The change of a topic sequence is organized with the help of method to organize acquisition of the course topic sequence offered in the article.
A Needs-Based Personalization Model for Context Aware Applications
Authors: Yahya Manal A.  , Dahanayake Ajantha
Published: February 2025

The concept of context-aware personalization enables implicit detection of user context to achieve personalization of services. Coupled with pervasive technologies such as augmented reality, this concept forms a view into the future of computing. This research argues that it is essential to understand the needs of the human-being using the technology. Hence, the goal of this research is to provide a description of the relationship between human needs and context information, and its role in the personalization of applications. This paper answers the research question: “How to enhance personalization using context awareness in applications for a better pervasive experience?” The research work resulted in the development of a user-centric model that embodies the concepts of context awareness and needs prediction. The proposed model is applicable in pervasive technology aiming to provide information or services with minimum attention from users to attain a high satisfaction level. The pragmatic values of this work is aimed in the fields of ambient assisted living, healthcare, entertainment, and advertisement.
A Text Similarity Approach for Automated Transposition Detection of European Union Directives
Authors: Nanda Rohan  , Di Caro Luigi  , Boella Guido
Published: February 2025

This paper investigates the application of text similarity techniques to automatically detect the transposition of European Union (EU) directives into the national law. Currently, the European Commission (EC) resorts to time-consuming and expensive manual methods like conformity checking studies and legal analysis for identifying national transposition measures. We utilize both lexical and semantic similarity techniques and supplement them with knowledge from EuroVoc to identify transpositions. We then evaluate our approach by comparing the results with the correlation tables (gold standard). Our results indicate that both similarity techniques proved to be effective in detecting transpositions. Such systems could be used to identify the transposed provisions by both EC and legal professionals.
Traffic Incident Severity Detection Model Based on Catastrophe Theory
Authors: Li Hongwei  , Li Sulan  , Zhu Hongwei  , Zhao Xing  , Zhang Xiaoli
Published: February 2025

An expressway traffic incident severity detection model is established in this paper, which can effectively detect the traffic incidents and their severity. By analyzing the relationship between the severity of freeway traffic incidents and the number of lanes, flow, speed and duration of traffic events in the event lane, the following conclusions are drawn: (1) The traffic flow of traffic incident lane and non-traffic incident lane has multi-mode, sudden jump and other abrupt theoretical features When a traffic incident occurs; (2) The severity of traffic accidents controls the degree of sudden and sudden jump of traffic incident lane and non-traffic incident lane. Based on catastrophe theory, this paper proposes a discriminant model of traffic accident severity based on traffic flow velocity and flow rate as independent variables. The measured data of expressway traffic events verifies the effectiveness of the proposed model.
Research on Path Planning of Automatic Handling Robot
Authors: Hou Yuanbin  , He Liu  , Song Chunfeng  , Zhang Yanyan  , Li Dong
Published: February 2025

Aiming at the problem that path planning for automatic handling robot in an environment with obstacles, the working environment model of the handling robot is analyzed. And then a path optimization algorithm based on fusing ant colony and particle swarm optimization algorithm is proposed. First of all, this algorithm uses the global search ability of particle swarm to go on a rough search and quickly plans the starting point to the end of the initial path. Then, the pheromone distribution is performed on the initial path. Finally, the ant colony algorithm is used to search the path carefully to get the optimal path. Experimental verification shows that compared with a single ant colony or particle swarm optimization algorithm, fused algorithm about ant colony and particle swarm optimization has a significant improvement in the number of iterations and path planning.
Statistical Image Analysis Based Automated Leaves Classification
Authors: Al-Otaibi Manar Bati  , Ashour Amira S.  , Dey Nilanjan  , Al Quthami Rahaf Abdullah  , Al-Nufaei Asrar Abdullah  , Shi Fuqian
Published: February 2025

Plants recognition and classification is a challenging process due to the high variability in the plants' features and shapes. Numerous methodologies incorporating image processing were improved to tackle this process for early stage recognition of diseases. Leaf recognition has popular/wide range of agriculture practical applications. Consequently, the current work is interested in the recognition and classification of parsley and basil leaves along with the recognition of their infected parts. An image analysis is used to extract different statistical features from the leaves' dataset. From such statistical features a recognition/classification processes are performed to classify the fresh and infected leaves in each leaf type as well as to classify the two-leave species. The classification process was performed using neural network. The experimental results depicted that the classification accuracies for the three tested cases, namely fresh/infected basil, fresh/infected parsley, and fresh basil/parsley were 80%, 80.0%, and 100.0%; respectively.
The Cooperative Defense System by Team of USVs in Complicated Sea Environment
Authors: Wu Xing  , Liu Yuan  , Guo Yike  , Xie Shaorong  , Pu Huayan  , Peng Yan
Published: February 2025

Based on the multi-agents system control theory and technology, this paper presents the construction of cooperative defense system of multiple unmanned surface vehicles (USVs) operating in complicated sea environment, develops the mathematical formula describing the trajectory equation when the USV intercepts the intruder, and explains the proposed coordination control method used in the corresponding defense system. Then we point out the future development requirement of the cooperative defense system. The cooperative defense system research of USVs in the sea environment has a great significance to the effective promotion of social and military efficiency, and it is the basis of the implement about cooperative strategies.
Design for sharing: libraries of things as a product-service system
Authors: Ameli N.
Published: February 2025

Sharing can be a way to confront ecological and social challenges. Libraries of Things offer the process of sharing in a convenient way that fits into the users' everyday life. These Libraries offer access to a broad range of items to everyone at a low price. The items offered should be of high quality to minimize risks, to enhance the flow of the sharing process and to create as little maintenance effort and cost as possible for the library. The contradiction of offering high quality products for a relatively low price could be solved by a cooperation between manufacturers using Libraries of Things as a distribution platform. The Libraries could thus help the manufacturers to adapt their business to the circular economy. This paper does not present a ready-made solution yet, but rather reflects upon the role of design within this area of product-service system and defines further fields of research since Lending Libraries have not yet been reflected upon from a design-angle.
Will durability be a characteristic of future cars?
Authors: Nieuwenhuis P.
Published: February 2025

The car industry believes it has already done a lot to meet the sustainability agenda. While there has been considerable progress in terms of reductions in toxic emissions, as well as greenhouse gas emissions, they are still very far from being sustainable either as an industry or in terms of the products they make. This point was made by Stuart Hart in 1997 (Hart, 1997), and despite progress since then, the same still holds today. Progress so far has been along an ‘eco-efficiency’ trajectory – i.e. doing the same thing we have been doing, but more efficiently. In reality, we need to stop doing what we have been doing and work out an alternative means of achieving what we are actually trying to achieve – motorised personal mobility with optimum enjoyment, comfort and safety levels. We need to do things differently, in other words.
Management of material cyclicity potential: example of electrical and electronic products
Authors: Shevchenko T.  , Kronenberg J.
Published: February 2025

This study is aimed at justification of the theoretical foundations of management of material cyclicity potential (MCP), including materials used in electrical and electronic products (EEP). In our opinion, the “cyclicity” of material should be studied from the perspective of the potential of materials to be multiply used. Such an approach allows to identify all possible forms of MCP manifestation in space and time. We suppose that the process of increasing of MCP starts with the design of the cycle of material multiple turnover (MMT) by forming an optimal range of products within which certain material sequentially turns, and continuous with the forming of MCP within adjacent product life cycles (located next in the specified range). The priority in the turnover sequence should be given to those products that are characterized by minimum change in the material quality parameters at the output of the turn. So, the focus on “cycle of MMT” rather than “product life cycle” is important for ensuring the maximum number of turns of material because it highlights that one deals with a range of products in which the same material is sequentially used, throughout their lifecycles, rather than only with one product. The suggested approach to closing material cycles is based on the concept of MCP, and unlike existing approaches, it provides the moving of certain material along a specified path – an optimal range of products thereby forming a cycle of MMT with maximum number of turns. This path obviously can be adjusted with each subsequent turn of material because a new products and technologies are being continuously designed. In the context of the circular economy, the proposed theoretically-methodical design of sustainable use of materials is intended for the rational allocation of new and circulating materials in an economic system.
Ever-faster, ever-shorter? Replacement cycles of durable goods in historical perspective
Authors: Wieser H.
Published: February 2025

Predicted by popular theories of acceleration, such as the theory of planned obsolescence and the rise of a throwaway society, the ever-faster replacement of durable goods is widely assumed in the literature. This paper confronts this assumption with long-term empirical evidence from three distinct cases - wheat seeds, automobiles, and mobile phones. The cases show that there is no dominant logic or force underlying historical changes in product durability, lifespans, and replacement cycles. Neither are such changes entirely unpredictable: There are clear patterns where these phenomena go up or down for sustained periods of time. The observed patterns in replacement cycles call for an empirically grounded theory that can explain both periods of acceleration and deceleration and connect durable goods replacement decision-making with developments at the aggregate level.
Investigation on Gate Capacitances Fluctuation Due to Work-Function Variation in Metal-Gate FinFETs
Authors: Lü Wei-Feng  , Lin Mi  , Zhang Hai-peng
Published: February 2025

This paper considers gate capacitance fluctuation due to work-function variation (WFV) in metal-gate Fin-type field-effect-transistors (FinFETs). The study shows that there exist correlations between gate trans-capacitance variations. Also, an analytical statistical model is presented to capture total gate capacitance variation based on the correlations. The model well fits the Monte Carlo simulations data. Our study also indicates, the gate capacitance variation due to WFV is very sensitive to drain-source voltage.
Multi-Granularity Rough Soft Set and Its Application in Decision Making
Authors: Wang Xiaomin  , Guo Chenxi  , Liu Jing  , Li Piyu  , Liu Jianbo
Published: February 2025

The aim of this paper is to introduce a notion of multi-granulation rough soft set. The classical rough soft set is established through a single granulation. This paper extends rough soft set model to a multi-granulation rough soft set model. Basic properties of multi-granularity rough soft set are proposed. Furthermore two algorithms based on multi-granularity rough soft set are proposed. Finally we give an example to illustrate the validity of these methods.
Conjunctive Query for Linked Data Based on Semi-Join
Authors: Jiang Dongyang
Published: February 2025

As the semantic web develops, a large amount of available web data grows rapidly. It is still a hot topic how to query useful information from these Web data more quickly, efficiently and exactly. To approach the issues, we present a conjunctive query method for Linked Data based on semi-join in order to reduce the overhead to transit the intermediate results produced by each data source from the network and when selecting data source, we exploit the query results of the basic graph pattern to precompute the cardinalities of the intermediate results and present a new data source selection algorithm based on “vocabulary of interlinked dataset ( voiD ) ”+“SPARQL ASK” to improve the accuracy of the data source selection. To reduce the query response time, we present a parallel semi-join algorithm. Extensive experiments show that our solution is more efficient and more effective compared to the existing techniques.
Discrete Event-Based Neural Simulation Using the SpiNNaker System
Authors: Brown Andrew  , Reeve Jeff  , Dugan Kier  , Furber Steve
Published: February 2025

SpiNNaker is a computing system composed of over a million ARM cores, embedded in a bespoke asynchronous communication fabric. The physical realization of the system consist of 57600 nodes (a node is a silicon die), each node containing 18 ARM cores and a routing engine. The communication infrastructure allows the cores to communicate via short, fixed-length (40- or 72-bit), hardware-brokered packets. The packets find their way through the network in a sequence of hops, and the specifics of each route are held (distributed) in the route engines, not unlike internet routing. On arrival at a target core, a hardware-triggered interrupt invokes code to handle the incoming packet. Within this computing model, the state of the system-under-simulation is distributed, held in memory local to the cores, and the topology is also distributed, held in the routing engine internal tables. The message passing is non-deterministic and non-transitive, there is no memory coherence between the core local memories, and there is no global synchronization. This paper shows how such a system can be used to simulate large systems of neurons using discrete event-based techniques. More notably, the solution time remains approximately constant with neural system size as long as sufficient hardware cores are available.
Dealing with (Real-)Time in Real-World Hybrid Systems
Authors: van Schaik Pieter  , Verhulst Eric
Published: February 2025

One of the issues that has been bothering embedded systems engineers is how to deal with time. Some approaches have attempted to make time part of the modelling language, other approaches turn it in a partial order of events, while most programmers ignore it completely equating QoS with real-time (most of the time but not guaranteed). While in the discrete domain, time is considered to be progressing as a number of clock cycles, in the continuous domain time has an infinitesimal granularity. If we now want to proof the correctness of a hybrid system, people traditionally use time dependent partial ordinary differential equations in the continuous domain and model checkers or provers for the discrete domain.
Communicating Generators in JavaScript
Authors: Micallef Kurt  , Vella Kevin
Published: February 2025

This paper outlines the design, performance, and use of an application programming interface and library for concurrent programming with CSP in JavaScript. The implementation harnesses ECMAScript 6 Generators to provide co-operative scheduling and channel communication within a single JavaScript engine. External channels lie atop WebSockets, amongst other web technologies, to enable multicore and distributed execution across standard web browsers and Node.js servers. Low-level benchmarks indicate that scheduling and messaging performance is within expectations for this dynamic and diverse execution environment. Sample code snippets highlight the applicability of CSP to contemporary web development in hiding the location of computation and state through the channel abstraction. The “call-back hell” scenario common to many JavaScript applications is alleviated by using channels instead of callbacks, and the possibility of performing parallel and scientific computing is explored with promising results. Finally, the limitations of the present design are discussed, and possible enhancements such as the dynamic migration of state and code are considered.
Modeling Smart Sensors on top of SOSA/SSN and WoT TD with the Semantic Smart Sensor Network (S3N) modular Ontology
Authors: Sagar Samya  , Lefrançois Maxime  , Rebai Issam  , Maha Khemaja  , Garlatti Serge  , Feki Jamel  , Médini Lionel
Published: February 2025

The joint OGC and W3C standard SOSA/SSN ontology describes sensors, observations, sampling, and actuation. The W3C Thing Description ontology under development in the W3C WoT working group describes things and their interaction patterns. In this paper we are interested in combining these two ontologies for modeling Smart-Sensors. Along with basic sensors, a Smart-Sensor contains a micro-controller that can run different algorithms adapted to the context and a communicating system that exposes the Smart-Sensor on some network. For example, a smart accelerometer can be used to measure cycling cadence, step numbers or a variety of other things. The SOSA/SSN ontology is only able to model partially the adaptation capabilities of Smart-Sensors to different contexts. Thus, we design an SOSA/SSN extension, called the Semantic Smart Sensor Network (S3N) ontology. S3N answers several competency questions such as how to adapt the Smart-Sensor to the current context of use, that is to say selecting the algorithms to provide the right sensors outputs and the micro-controller capabilities.
Controlled Natural Languages for Hazard Analysis and Risk Assessment
Authors: Chomicz Paul  , Müller-Lerwe Armin  , Wegner Götz-Philipp  , Busch Rainer  , Kowalewski Stefan
Published: February 2025

The hazard analysis and risk assessment (HARA) is a safety activity, which is performed during the concept phase of the functional safety standard ISO 26262. The results of this activity are usually documented by using a natural language. On the one hand, natural languages are expressive and powerful, but on the other hand, they are also ambiguous and complex. The usage of controlled natural languages (CNLs) is a means to reduce the drawbacks of natural languages. In this paper, we introduce controlled natural languages for the rationales of the three risk parameters: severity, exposure, and controllability to extend our set of CNLs for the HARA. In the first place, the application of controlled languages leads to more harmonized descriptions and rationales. Subsequently, an automatic processing based on these languages shall be implemented to enable the detection of inconsistencies across different HARA documentations.
EDEN: Extensible Discussion Entity Network
Authors: Meter Christian  , Schneider Alexander  , Mauve Martin
Published: February 2025

Enabling the reuse of arguments as entities that can be shared across multiple Internet-based discussion platforms and that can be improved upon while they are being used and reused has many benefits ranging from easier participation in an online discussion to increasing the quality of arguments. In this paper we propose a mechanism that is able to support the large-scale reuse of arguments by providing distributed version control of argument data. Building on that mechanism we have designed and implemented EDEN, a framework which enables platform providers to easily network their discussions. EDEN is designed for real-world use and provides all tools necessary to enable the reuse of arguments and their interrelation for users and providers alike.
On the Expressive Power of Collective Attacks
Authors: Dvořák Wolfgang  , Fandinno Jorge  , Woltran Stefan
Published: February 2025

In this paper, we consider SETAFs due to Nielsen and Parsons, an extension of Dung's abstract argumentation frameworks that allow for collective attacks. We first provide a comprehensive analysis of the expressiveness of SETAFs under conflict-free, naive, stable, complete, admissible and preferred semantics. Our analysis shows that SETAFs are strictly more expressive than Dung AFs. Towards a uniform characterization of SETAFs and Dung AFs we provide general results on expressiveness which take the maximum degree of the collective attacks into account. Our results show that, for each k>0, SETAFs that allow for collective attacks of k+1 arguments are more expressive than SETAFs that only allow for collective attacks of at most k arguments.
Extending Tēzaurs.lv Online Dictionary into a Morphological Lexicon
Authors: Pretkalniņa Lauma  , Paikens Pēteris
Published: February 2025

This paper describes the integration of traditional dictionary data from the Tēzaurs.lv online dictionary with a morphological analysis system, resulting in a structured morphological lexicon that improves coverage of morphological tagging and also enhances the dictionary with automatically generated inflection tables. The main challenge in this integration was the extraction of structured data from textual dictionary information, and classification of dictionary entries into morphological paradigms.
Using Wearable Sensors to Detect Workload on Driving Simulated Scenarios
Authors: Corcoba Víctor  , Falomir Zoe  , Mohamed Nourelhoda
Published: February 2025

This paper aims to measure the workload induced by driving simulators in realistic driving situations (i.e. where driving efficiency and safety play a role), or in unusual circuit situations (i.e. players enjoy crashing). For that, the first step is finding out if a driving simulator impacts/affects on a driver's workload. This workload is measured objectively using biometric sensors (i.e. Empatica E4 and Polar H7 chest strap) and subjectively by a user test. In this study, a pilot test was carried out by three participants with different profiles who tested four different scenarios in BeamNG.drive simulator. The results showed that this simulator causes an increase in the workload in scenarios showing tasks with responsibility, and that the workload is lower in scenarios where the players enjoy car crashing. This workload is higher in participants with experience driving in real environments possibly due to the realism of the BeamNG.drive simulator. Thus, driving simulators can be utilized to study players' reaction to crashes and to improve their behaviour.
Determining Dyslexic Model Membership Using Fuzzy Approach
Authors: Pařilová Tereza
Published: February 2025

Natural language plays a crucial role in many different and very specific scientific issues. It is also the main aspect of studying specific learning disabilities like dyslexia and helps to design adequate technologies aiming at the specific dyslexia needs. Although dyslexia affects up to 20 % of the worldwide population, no apparatus has been designed to build a user model or user categorization. Such individual categorization, describing individual reading problems and changes over time, may, however, be crucial for further psychological and neurological studies of this disorder.
A Pre-Shared Key Pool Scheme for Wireless Sensor Networks Based on Time
Authors: Zhou Meixiu  , Chen Hanying  , Liu Xiaoli
Published: February 2025

Based on the core issues of the wireless sensor network security model, this paper proposes a new design of pre-shared key pool, which is applied in the area-based key management scheme to ensure network security. This scheme designs a pre-allocated shared key pool architecture based on time variables of one-way hash function, adds time parameters to key negotiation, node update, etc., updates the key through the time mechanism and detection mechanism, and effectively guarantees both forward and backward security of the node. For the problem that local nodes are easily captured, this paper designs a key update mechanism based on security events, namely a key pool update mechanism based on a one-way hash key chain. This new one is based on a one-way hash key chain. The key pool satisfies the security requirements for key generation and updating. After theoretical analysis and simulation, it is proved that node connectivity, node storage energy consumption, and anti-capture capability in the proposed improvement scheme are better than the original one.
Key Zone Auto Location of Plantar Pressure Image Using De-Dimensionality and Wavelet Transformation
Authors: Li Zairan
Published: February 2025

The research on the comfort of shoes is a hot-issue in the field of footwear optimization design and intelligent design. To acquire the data-set of plantar pressure imaging, the foot-scan plantar pressure imaging experimental equipment was used to the plantar pressure imaging by collecting the actual test images of plantar pressure. The basic data-set of plantar pressure image is constructed by means of denoising and dimension reduction, which provides the basis for the segmentation of key feature areas and the extraction of key features of plantar pressure. The proposed methods of image de-dimensionality are used in preprocessing of image data-set. And some image filtering technologies are also applied in suppressing the noise of the target image, and subsequently to keep the original image feature details. The effect of some kinds of filtering was directly affect the subsequent image processing and the effectiveness of image fusion analysis by using Gaussian filtering, mean filtering and bilateral filtering which will guide the last surface generation in better ways.
Implementing a MIPS Processor Using SME
Authors: Johnsen Carl-Johannes
Published: February 2025

The Synchronous Message Exchange (SME) model, is a programming model, which closely resembles the CSP model and which is suitable for describing hardware. This paper aims to combine the theory taught in a machine architecture class, with the SME model, by implementing a MIPS processor using SME. I show how to construct the components of a MIPS processor as SME processes, and how to connect them by using SME busses. Furthermore, I show how to extend the processor, by introducing additional instructions and by pipelining the processor.
Challenges When Implementing a Battery-Less Display
Authors: Roebbers Herman
Published: February 2025

Over the years it has become more and more important to reduce energy consumption, especially in the realm of IoT edge devices, which often must operate without a battery change for several years. At Altran we want to design and implement solutions that do not require batteries, but harvest energy from their surroundings. They use this energy to operate a radio for receiving and transmitting information, as well as operate sensors and actuators. This requires careful analysis of contributors to energy consumption in order to minimize the energy requirements. One aspect of this is the collaboration and coordination of hundreds of such nodes on the use of a shared medium, namely the radio frequency on which they operate. A prototype of a demonstrator to create and show understanding of the various technologies involved is under development. The presentation gives an overview of the many challenges and (proposed) solutions for the complete development of such a system and presents the current status of the prototype, capable of running forever on 2 small solar cells and interacting over Bluetooth Low Energy with a server node.
Artificial Intelligence Within the Bounds of Ontological Reason
Authors: Oltramari Alessandro
Published: February 2025

The integration between symbolic knowledge and machine learning is becoming more and more important today, although controversially absent from mainstream data-driven AI. Stemming from my research in academia and industry, this contribution discusses the role that Applied Ontology can play in modern AI approaches. I will claim that, by means of a cognitively-inspired foundational framework, a more effective synergy between the two disciplines can be established.
Software and hardware co-design of AI high-rate chips for parallel training of edge intelligence
Authors: Li Haiqiang , Ling Zhimei , Yang Chaoyi
Published: February 2025

With the digital transformation of information technology and industry, the applicability scenarios of edge intelligent terminals are expanding. AI chips have become one of the mainstream core devices of edge terminals. How to select suitable AI chips according to application scenarios through systematic analysis has become an urgent problem to be solved. This paper first provides a comparative analysis of the technical architecture and advantages and disadvantages of AI chips; then proposes a low implementation complexity, multi-code rate fusion LDPC parallel coding structure, and an encoder chip design scheme using this structure for high-speed digital transmission applications. Based on the TSMC 130 nm CMOS standard cell library, the encoder chip can achieve a throughput rate of 1.6 Gbps at 200 MHz clock and consume only 184.3 m W. Compared with the LDPC encoder chip with the same throughput rate designed in the conventional architecture, this solution can reduce the storage space requirement to 18.52% of the conventional architecture. The proposed encoding chip design solution not only maintains high performance but also significantly reduces the demand for storage space, making it a good choice for resource-constrained environments.
Estimation and improvement of multi-path error of IGS signal based on digital filtering technique
Authors: Zhang Pengcheng , Yu Hao , Wang Wei , Su Tao , Zhu Min , Jin Xin , Huang Ying
Published: February 2025

With the rapid development of global navigation satellite system (GNSS) technology, IGS signals play a crucial role in many fields such as positioning, navigation, and time synchronization. Nevertheless, the multipath error problem seriously affects the performance of IGS signals in practical applications. In this paper, the multipath error problem of IGS signals is studied in depth, and an improvement method based on a digital filtering technique is proposed. The article first provides a comprehensive analysis of the impact of multipath error and identifies the shortcomings of existing studies, thus clarifying the motivation of this study. Subsequently, this paper uses digital filtering techniques to estimate the multipath error accurately and designs a corresponding improvement strategy. Through experimental verification, this paper demonstrates the significant effect of the improved method in improving signal quality and positioning accuracy. Finally, the article summarises the research results. It discusses their potential promotion value in IGS signal reception and related applications, which provides important theoretical support and practical guidance for future technology development and applications.
The Transformative Impact of Artificial Intelligence on Drug Discovery: A Technical Review
Authors: Poshan Kumar Reddy Ponnamreddy
Published: February 2025

This comprehensive article examines the transformative impact of artificial intelligence on drug discovery and development processes. The article explores traditional challenges in pharmaceutical development, including extended timelines, high costs, and low success rates, which have prompted the industry's shift toward AI-driven solutions. The article investigates how AI applications have revolutionized early research stages, clinical trial management, and validation processes. Through a detailed examination of recent implementations, the article demonstrates AI's significant improvements in target identification, molecular screening, and clinical trial optimization. The article also addresses technical considerations, including data quality requirements, algorithm development challenges, and resource implications for successful AI integration in pharmaceutical research. This article provides insights into emerging trends and future directions while highlighting AI's achievements and limitations in drug discovery.
Smart Detection of Energy Theft in Agricultural Sectors
Authors: Ashwini R  , Kaviga D  , Rohitha M  , Sivaranjani G  , Guru Deepthi V
Published: February 2025

The project revolves around the comprehensive management of energy resources through real-time monitoring, theft detection, and demand prediction. It employs AC current and voltage sensors to monitor energy consumption, with data being timestamped and compiled into a dataset. The future energy demand is forecasted using Long Short-Term Memory (LSTM) neural networks, allowing for better resource planning. Additionally, theft detection is carried out through a Support Vector Machine (SVM) algorithm trained on historical data. The gathered information is securely uploaded to the ThingSpeak cloud platform, ensuring data integrity and accessibility. To enhance user engagement and control, a web application is developed for visualizing the energy usage, demand forecasts, and theft alerts. This project addresses the pressing need for efficient energy management, enabling users to make informed decisions and combat energy theft while contributing to sustainability and resource conservation.
РОЛЬ ОБСЄ У РЕАЛІЗАЦІЇ МІЖНАРОДНИХ СТАНДАРТІВ ЗАХИСТУ ВНУТРІШНЬО ПЕРЕМІЩЕНИХ ОСІБ
Authors: ОРЛЕНКО Валентина
Published: February 2025

У статті детально розглянуто роль Організації з безпеки та співробітництва в Європі (ОБСЄ) у впровадженні міжнародних стандартів захисту внутрішньо переміщених осіб (ВПО), які є однією з найвразливіших категорій населення під час збройних конфліктів та кризових ситуацій. Зазначено, що ОБСЄ, як найбільша регіональна організація, має широкий мандат у питаннях безпеки та захисту прав людини. Її діяльність зосереджується на забезпеченні стабільності, попередженні конфліктів, моніторингу ситуацій з порушенням прав людини, а також на сприянні миротворчим процесам. Важливу роль у захисті ВПО відіграє міжнародна співпраця, зокрема взаємодія з такими організаціями, як Управління Верховного комісара ООН у справах біженців (УВКБ ООН), яка дозволяє координувати дії та уникати дублювання зусиль. Особливу увагу приділено оцінці ефективності спеціальних моніторингових місій ОБСЄ, які є важливим механізмом у забезпеченні безпеки та прав людини. Як приклад наведено Спеціальну моніторингову місію (СММ) ОБСЄ в Україні, що діяла з 2014 до 2022 року. Ця місія здійснювала неупереджене спостереження за ситуацією в зоні конфлікту, а також фіксувала порушення прав людини, надаючи міжнародним партнерам і зацікавленим сторонам актуальну інформацію для прийняття рішень. Крім того, СММ сприяла діалогу між сторонами конфлікту, що допомогло запобігти ескалації насильства. У дослідженні виявлено, що хоча ОБСЄ має значний потенціал у забезпеченні захисту ВПО, існують певні проблеми. Однією з основних є недостатня інтеграція місцевих організацій та громадянського суспільства у процеси, що спрямовані на захист ВПО. Це створює прогалини у співпраці та знижує ефективність заходів з реабілітації та інтеграції внутрішньо переміщених осіб у нові громади. Важливою перешкодою є також обмежений доступ місій ОБСЄ до певних регіонів через безпекові обмеження або відсутність правових інструментів, що ускладнює їхню роботу. У статті запропоновано кілька шляхів для покращення діяльності ОБСЄ. Насамперед, це посилення співпраці з місцевими органами влади та організаціями громадянського суспільства, які мають безпосередній доступ до постраждалого населення. Це дозволить забезпечити оперативну допомогу ВПО та створити умови для їхньої інтеграції в суспільство. Крім того, рекомендується розширити юридичні повноваження місій ОБСЄ, що дозволить їм більш ефективно реагувати на порушення прав ВПО, а також запровадити спеціальні механізми для моніторингу та захисту прав ВПО на всіх етапах конфлікту. Таким чином, діяльність ОБСЄ у сфері захисту ВПО є ключовою для стабілізації ситуацій у постконфліктних регіонах, однак потребує подальшого вдосконалення та тіснішої взаємодії з місцевими та міжнародними партнерами для забезпечення максимальної ефективності.
НАПРЯМИ РОЗВИТКУ ФІНАНСОВИХ ЕКОСИСТЕМ
Authors: Олешко Тамара , Марина Анна , Сушириба Ростислав
Published: February 2025

У роботі розглядаються сучасні напрями розвитку фінансових екосистем в умовах цифрової трансформації. Встановлено, що екосистемний підхід забезпечує прогресивний розвиток фінансового сектору на основі інтеграції банківських, фінансових небанківських та нефінансових послуги в межах єдиних платформ. Такий підхід дозволяє усім учасникам екосистеми швидко адаптуватися до динамічних ринкових змін та клієнтських очікувань. Ключовими елементами сучасних фінансових екосистем є інноваційні рішення, що реалізуються за допомогою супердодатків, блокчейн-технологій, штучного інтелекту та використання великих даних. В розвитку глобальних та національних фінансових ринків велику роль відіграють цифрові технології та фінтех, тому програми підвищення ефективності взаємодії між учасниками фінансової екосистеми мають враховувати ці тенденції. Об’єднуючи на основі сучасних технологій ключових учасників економіки, фінансові екосистеми створюють передумови для стійкого економічного зростання, соціального розвитку та глобальної взаємодії.
PUBLIC-PRIVATE PARTNERSHIP POTENTIAL IN ENSURING THE ECONOMIC STABILITY OF TERRITORIAL COMMUNITIES
Authors:   Taurida V.I. Vernadsky National University, Mozharivskyi Yaroslav
Published: February 2025

The article examines the key aspects of implementing public-private partnerships (PPP) in territorial communities of Ukraine in the context of modern economic challenges, particularly under martial law conditions. The relevance of the study is driven by the necessity to identify effective mechanisms for attracting investments to restore local infrastructure, enhance economic resilience, and improve the social well-being of the population. PPP is highlighted as one of the most promising tools for fostering cooperation between the state, businesses, and communities to address shared recovery and development objectives. The purpose of the study is to analyze the peculiarities of implementing PPP projects in Ukraine’s territorial communities, assess their impact on economic development, and formulate recommendations for improving the efficiency of this tool. The article employs a systemic approach that enables the consideration of PPP as a comprehensive mechanism for collaboration. Comparative analysis methods were used to examine the practical experience of PPP implementation in various communities, statistical analysis to evaluate the dynamics of PPP projects in recent years, and graphical methods to visually present trends in the PPP domain. The study revealed the positive impact of PPP projects on the local economy, particularly through the creation of new jobs, attraction of investments, and modernization of key infrastructure facilities. The analysis of practical experience demonstrated the significant potential of this tool for the development of territorial communities, especially under conditions of limited public funding and increasing socio-economic challenges. Based on the analysis, several recommendations were proposed, including the development of regional PPP strategies, the establishment of support centers for project preparation, the introduction of innovative financing mechanisms, and raising public awareness about the benefits of PPP. It is concluded that PPP is an effective tool for ensuring sustainable development of Ukraine’s territorial communities and overcoming the consequences of war.
SOCIAL NETWORKS AND FAKE ACCOUNTS: CHALLENGES FOR MARKETERS
Authors:   Odesa National University of Economics, Tarasova Krystyna , Kravets Daria ,   Odesa National University of Economics, Novak Hanna ,   Odesa National University of Economics
Published: February 2025

The article examines the challenges of fake social media accounts and their significant implications for marketing in the digital era. It explores the growing prevalence of fake profiles and their role in distorting analytical data, reducing the effectiveness of advertising campaigns, and undermining brand reputation. The study highlights how the widespread use of fake accounts facilitates disinformation, spam, and fraudulent activities, creating substantial obstacles for marketers seeking to build consumer trust and transparency. Special attention is given to the impact of fake reviews, manipulated public opinion, and the misuse of user data, which can disrupt marketing strategies and damage long-term business relationships. The article underscores the importance of modern technologies, including artificial intelligence and machine learning algorithms, in detecting and mitigating the impact of fake accounts. It evaluates state-of-the-art approaches, such as neural networks, GAN models, and behaviour pattern analysis, to identify non-authentic accounts and cleanse marketing datasets from inaccuracies caused by bots and fraudulent interactions. The research also discusses the ethical and social implications of fake accounts, including their influence on consumer trust, online engagement authenticity, and social media platforms' overall transparency. Furthermore, the study emphasizes the need for businesses to integrate innovative digital tools and strategies to address these challenges. It advocates for adopting AI-driven systems for real-time monitoring, proactive reputation management, and tailored responses to minimize the risks of fake accounts. The role of governmental regulations, platform accountability, and public awareness campaigns is also highlighted as crucial components in combating the spread of disinformation and fraudulent activity in social media. The findings reveal that combating fake accounts requires a multi-dimensional approach, combining advanced technological solutions with ethical marketing practices and consumer education. The study concludes that building resilient marketing strategies in the digital age demands technical innovation and a commitment to fostering trust and transparency in consumer interactions. By addressing the challenges posed by fake accounts and adapting marketing approaches to the realities of the digital environment, businesses can enhance their competitive edge and ensure sustainable growth in a rapidly evolving landscape.