bluuebunny/crossref_metadata_2025 huggingface dataset:
Profiling the Future Demands of the UK Food Supply Chain
Authors: Thomas Andrew  , Haven-Tang Claire  , Sedgley Diane  , Byard Paul
Published: February 2025

The UK food industry faces significant challenges to remain competitive. With Brexit on the horizon, companies can no longer rely on a low labour cost workforce to maintain low production costs. Industry 4.0 is seen as a technology driven paradigm that aims to significantly improve productivity and performance of a company whilst ensuring better demand/supply chain connectivity. However, there is evidence to suggest that the UK food industry has not yet embraced this new manufacturing paradigm. Through an exploratory survey of 36 food companies (8 large and 28 small) this paper discusses the key issues around whether these companies are prepared for the implementation of I.E 4.0. The discussion provided along with the primary survey data suggests that the larger food companies are starting to focus on I.E 4.0. However, greater awareness of the methods of implementation is needed if companies are able to embed such systems.
Finite Element Analysis on Conventional Drilling of Natural Fibre-Reinforced Polymer Bio-Composites
Authors: Ismail Sikiru Oluwarotimi  , Dhakal Hom Nath  , Alzaidi Yousef Awwadh
Published: February 2025

Finite element analysis (FEA) on conventional drilling of two bio-composite materials, consist of hybrid woven flax-basalt and woven basalt fibre with vinyl ester matrix, designated as composite materials A and B respectively, has been conducted. The simulation results using LS-DYNA and ANSYS software depict that different reinforcements (flax and basalt fibres) of the composite materials significantly influenced the degree of resistance, strength, deformation and elasticity exhibited during the machining process. It was observed that drilling-induced damage were experienced in different degrees by the materials. The quality of the holes produced was affected by the characteristics of these materials, when experimentally validated. Also, significant differences in tensile strength and impact of the drilling operation on the plies of the two materials were observed. Material A experienced higher stress and lower tensile strength, resulting into a higher level of push-out delamination, uncut-fibre and fibre pull-out, among other rampant drilling-induced damage, than material B. Both materials possessed high stress and deformation, which were more at the edges (entry and exit) of the drilled holes rather than the centre point where the drill impacted the hole. The equivalent elastic strain further shows a high level of impact at the surface of material A, unlike material B. Comparatively, the composite material B (woven basalt fibre reinforced polymer) has a better machinability when compared with hybrid material A (woven flax-basalt). Hence, it implies that the FRP composite materials responded to damage differently under same machining (drilling) process and condition.
Development of NPD Portfolio Management in Project Based Environments
Authors: Shah Satya  , Naghi Ganji Elmira  , Coutroubis Alec
Published: February 2025

This paper focuses towards examining the initial phases of new product development portfolio management supervising set of projects managed by a company. It also explores the selection of the most suitable projects from a series of candidates through a prioritisation criteria based on the available resources, the strategic objectives and the features of each product within the product lifecycle. Utilising a mixed methodology, the research proposes to develop a novel framework named project portfolio management practice (PPMP) within small and mid-sized project-based manufacturing companies, therefore providing a system that helps them increasing their product sales volume by ten-percent and improving the NPD-SCM alignment with PPM. Indeed, more empirical sources should be selected, with the aim of expanding the visions within any given product development environment. This generalisation aims to cover other industries, including manufacturing, service and product based environments to identify the proper measures for any type of project.
3D Object Comparison with Geometric Guides for Interactive Evolutionary CAD
Authors: Retzepi Theodora  , Goh Yee Mey  , Graham Ian J.
Published: February 2025

3D object comparison is presented as part of research into guided evolutionary Computer-Aided Design (CAD). CAD technology in development will combine human interaction and geometric optimization, within an existing evolutionary design system (EvoShape). Geometric Guides consist of simple 3D target objects (bounding volumes), to which evolving forms are compared. Before comparison, objects must be aligned and scaled, a process known as Pose Normalization (PN) in the literature. Both PN and object comparison have been implemented using standard geometric functions, enabling populations of evolving forms to be directed by the Geometric Guides. The algorithms and their implementation are presented alongside early results and analysis, discussion on limitations and robustness, and their suitability for Interactive Evolutionary CAD.
An Investigation on the Engineering Process Oriented Approach to Aerospace Quality Assurance Compliance in Manufacturing SMEs
Authors: Hussein Abdullahi  , Cheng Kai
Published: February 2025

Aerospace Manufacturing SMEs are continuously facing the challenge of complying with the aerospace quality standard requirements. Some of these requirements can be quite demanding for manufacturing SMEs compared to the big organisations with dedicated resources to maintain the organisations quality systems. The engineering process oriented approach proposed in this paper is considered to be essential for developing aerospace manufacturing quality management systems. It aims primarily to increase effectiveness and efficiency of manufacturing SMEs in achieving their business objectives. The approach is much more comprehensive than just involving manufacturing activities, which includes identifying all the resources required by processes, inputs, activities and outputs, in the context of aerospace quality assurance and compliance. Furthermore, this paper will investigate the implementation perspectives of the approach particularly against the aerospace quality assurance requirement in manufacturing SMEs. An application case study on a manufacturing SME is presented, which helps further evaluate and validate the approach through quality assurance compliance application.
Utilising Learning Analytics in Knowledge Management Adoption for Effective Manufacturing Education
Authors: Alenezi Abdullah  , Emmanouilidis Christos
Published: February 2025

Knowledge management adoption in higher education institutions is still limited. Essentially, higher education institutions have not developed their knowledge management approaches to an advanced level as opposed for instance to business and industry. The increasing use of technology in learning practices however, has brought new technology-enhanced learning solutions that provide an opportunity by linking this tangible basis to the (often) non-tangible elements of a knowledge management process. This paper maintains the significance of utilising learning analytics for knowledge management implementation in higher education institutions. It argues that knowledge management is essential to support improvements and innovation of analytical processes, which are essential for robust learning analytics. Moreover, learning analytics is required to be embedded in the organisation's strategic vision, and knowledge management can help an organisation translate its strategic vision into action. As such, the mapping between these institutions' products and the industry needs might still be lacking. Learning analytics, given the introduction and spread of virtual learning environments, provides an unprecedented opportunity for higher education institutions to improve their knowledge management initiatives. This is believed to bridge the gap between manufacturing and its education.
Using Systems Engineering to Develop a Novel Manufacturing Cost Model
Authors: Kuppusamy N.  , Whitfield R.I.  , Hird A.  , Brown S.  , McCubbin C.  , McCubbin P.
Published: February 2025

This paper describes the established process of cost model development and highlights opportunities for further improvement. Combinations of Systems Engineering tools were used within the modelling strategy in order to overcome the limitations of individual techniques. A functional modelling language was used to analyse, develop and integrate the cost model functions. The relationships between the manufacturing systems were modelled using Unified Modelling Language (UML). Furthermore, the benefits obtained by introducing changes to the cost model development process were evaluated by drawing comparisons between the two model development approaches.
Multi-Disciplinary Integrated Aircraft Cost Suite for Optimisation Study
Authors: Di Pasquale Davide  , Gore David  , Savill Mark  , Kipouros Timoleon
Published: February 2025

The importance of engineering costing within aircraft design should have a more directly influential role. A challenge for the scientific community is to adapt and to exploit the trend towards greater multidisciplinary focus in research and technology, particularly with regard to utilising cost as a metric within the process. There is a strong need to understand the cost associated with different competing concepts, and this could be addressed by incorporating cost estimation in the design process. The key feature of the developed cost suite is that it captures the attributes of a design that drive the cost, which generally is not only weight, but also assembly and detailed manufacturing costs, which are directly taken into account by means of component layout and manufacturing rules. This paper outlines the continuation of a previous work made on the integration of a Cost Suite for preliminary aircraft design within an environment framework that can automatically take inputs from external sources and allow optimisation study at early design stage.
Experimental Investigation and Optimization of Overcut in WEDM of WC-Co Composite Material
Authors: Kumar Pardeep  , Kumar Jatinder
Published: February 2025

This paper presents an experimental investigation on an important measure of the production inaccuracy, known as overcut, in wire electric discharge machining of WC-Co composite material (with 24% Co). Effect of several process parameters such as pulse on time, pulse off time, peak current and gap voltage on the response (overcut) was evaluated through designed experiments using response surface methodology. It was observed that pulse off time and gap voltage are the significant parameters affecting overcut. The optimized value of overcut was found to be 0.042 mm from the confirmation experiments. An improvement of over 10% was achieved over the best value obtained in experiments through optimization.
Experimental Investigation of Surface Roughness for Different Thickness of Aluminum in Abrasive Waterjet Machining
Authors: Zahoor Sadaf  , Shehzad Adeel  , Case Keith  , Hussain Amjad  , Zahoor Zain  , Waqar Shoaib Muhammad
Published: February 2025

Abrasive waterjet machining is a novel method of machining complex shapes and profiles. Surface roughness is a widely used machining characteristic to define the quality of the machined components. This present study reports the effects of workpiece material thickness, abrasive mass flow rate and standoff distance on surface roughness while performing abrasive waterjet machining. A L9 Taguchi array is used for the design of experimentation signal to noise ratio and analysis of variance is carried out. The experimental results show that the most influential parameter affecting surface roughness is workpiece thickness.
Study on Technologies for Applications in Tactile Internet
Authors: Zhang Yixin  , Dou Shaoyu  , Su Xin
Published: February 2025

Recently, Tactile Internet has been proposed as a promising technology to innovate the human communication within a very short delay. But now it still cannot solve the problem of high delay, which leads to Tactile Internet cannot be widely applied. Therefore, the low-latency techniques, which guarantee an approximately 1ms round-trip delay, should be developed. This survey paper lists several low-latency technologies which can be considered and applied into Tactile Internet.
Evolutionary and Bio-Inspired Algorithms in Greenhouse Control: Introduction, Review and Trends
Authors: de Moura Oliveira P.B.  , Solteiro Pires E.J.  , Boaventura Cunha J.
Published: February 2025

This paper provides a bare-bone introduction to evolutionary and bio-inspired metaheuristic in the context of environmental greenhouse control. Besides presenting general evolutionary algorithm principles, specific details are provided regarding the genetic algorithm, particle swarm optimization and differential evolution techniques. A review of these algorithms within greenhouse control applications is presented, both for single and multiple objectives, as well as current trends.
Automatic Rice Yield Estimation Using Image Processing Technique
Authors: Reza Md Nasim  , Na In Seop  , Baek Sun Wook  , Lee Kyeong-Hwan
Published: February 2025

Precision agriculture enables the dynamic use of technologies to boost up crop production, increase crop yield and at the same time decrease the input variables. Yield monitoring and estimation are considered to be the major steps to implement site-specific crop management or precision farming. Unmanned aerial vehicle (UAV) imaging based automatic rice yield estimation in different growing stages, could be a solution. In this work, we proposed a color-based segmentation algorithm that used Lab color space and k-mean clustering techniques to detect rice grain panicles area. Segmentation of grain from the image background was carried out in two steps. In the first step, a filter was applied to RGB (red, green and blue) images to remove noise and the image converted to Lab color space. The k-means clustering was applied to organize all colors contained in both a and b layers. The pixels were clustered based on their color and special features. In the second step, the variation between colors was measured and labelling of pixels was completed by cluster index. The clustering index was joined to a specific region and the images segmented using color information. The proposed method showed that rice grain can be segmented and that rice grains panicles numbers and area can be estimated from UAV images. The comparison provided significant results. The correlation between the ground truth measure and proposed method for rice grains panicles number and area were found to be around 0.931 and 0.842 respectively.
The Prospects of Jihadism Amidst a Withering Caliphate
Authors: Lahoud Nelly
Published: February 2025

The split between al-Qa‘ida (AQ) and the Islamic State may partly be attributed to a clash between two worldviews, one developed by AQ's elites, the other by thugs within jihadism, seeking to oust AQ. The differences testify to the importance of elites in engendering terrorism, but also to the fragile ideological nature of jihadism that prevents unity among those who profess the cause of jihad. Nevertheless, while dissent within jihadism may lead to its self-destruction in the long term, the fractures are likely to generate more violence in the short-term.
The Shifting Jihadist Galaxy
Authors: Plebani Andrea
Published: February 2025

While maintaining a crucial position within the jihadi discourse, since 9/11 the debate on the creation of a “truly” Islamic State has been partially obscured by the struggle against the far enemy, an objective which was given primary importance by al-Qa‘ida. Especially from 2011 onward, the situation gradually changed and the theme came back to the fore. In a context marked by the stiffening of the authoritarian regimes spared by the Arab Spring, the crisis of the liberal models invoked against them, and the collapse of the Islamist alternatives dominating in the immediate “post-Spring order”, the jihadist galaxy passed through a significant ideological and methodological shift embodied by the proclamation of the “Islamic State” (IS) in 2014. The essay aims to analyze this phenomenon focusing on the different approaches adopted by IS and al-Qa‘ida as well as on the implications this shift may have on the broader jihadi galaxy.
Viper: A Verification Infrastructure for Permission-Based Reasoning
Authors: Müller Peter  , Schwerhoff Malte  , Summers Alexander J.
Published: February 2025

The automation of verification techniques based on first-order logic specifications has benefitted greatly from verification infrastructures such as Boogie and Why. These offer an intermediate language that can express diverse language features and verification techniques, as well as back-end tools: in particular, verification condition generators.
Telemedicine in Croatia
Authors: Zorica Zoran
Published: February 2025

This article presents Croatian Institute of Telemedicine, telemedicine services and technical solutions used within the national telemedicine network.
Merging Data Science and Large Scale Computational Modeling
Authors: Sullivan Francis  , Beichl Isabel
Published: February 2025

Future exascale computers will have to be suitable for both data science applications and for more “traditional” modeling and simulation. However, data science applications are often posed as questions about discrete objects such as graphs while problems in modeling and simulation are usually stated initially in terms of classical mathematical analysis. We will present examples and arguments to show that the two points of view are not as distinct as one might think. Recognizing the connections between the two problem sets will be essential to development of algorithms capable of exascale performance. Our main examples will be from applications of Monte Carlo to attacking hard problems of the kind that occur both in data science and in computational modeling of physical phenomena. We will illustrate how taking ideas from both worlds pays wonderful dividends.
Application-Specific Energy Modeling of Multi-Core Processors
Authors: Getov Vladimir  , Macduff Matt  , Kerbyson Darren J.  , Hoisie Adolfy
Published: February 2025

Recent developments of high-end processors recognize energy monitoring and tuning as one of the main challenges towards achieving higher performance given the growing power and temperature constraints. Our thermal energy model is based on application-specific parameters such as consumed power, execution time, and equilibrium temperature as well as hardware-specific parameters such as half time for thermal rise or fall. As observed with the out-of-band instrumentation and monitoring infrastructure on our experimental cluster with air cooling, the temperature changes follow a relatively slow capacitor-style charge-discharge process. Therefore, we use the lumped thermal model that initiates an exponential process whenever there is a change in processor's power consumption. Experiments with two codes – Firestarter and Nekbone – validate our approach and demonstrate its use for analyzing and potentially improving the application-specific balance between temperature, power, and performance.
Advances in Topology-Aware Scheduling in Multidimensional Torus-Based Systems
Authors: Li Kangkang  , Malawski Maciej  , Oleksy Piotr  , Nabrzyski Jarek
Published: February 2025

Communication networks in recent high performance computing machines often have multi-dimensional torus topologies, which influences the way jobs should be scheduled into the system. With the rapid growth of the size of modern HPC system's interconnect, network contention has become a critical issue for the performance of parallel jobs, especially for those which are communication-intensive and not tolerant to inter-job interference. Moreover, to improve the runtime consistency, a contiguous allocation strategy is usually adopted, and each job is allocated a convex prism. However, using this strategy brings in internal and external fragmentation, which can degrade the system utilization. To this end, in this work, we investigate and develop various strategies in topology-aware job scheduling strategies for multidimensional torus-based systems, with the objective of improving job performance and system utilization.
Object Retrieval with Deep Convolutional Features
Authors: Mohedano Eva  , Salvador Amaia  , McGuinness Kevin  , Giró-i-Nieto Xavier  , O'connor Noel E.  , Marqués Ferran
Published: February 2025

Image representations extracted from convolutional neural networks (CNNs) outdo hand-crafted features in several computer vision tasks, such as visual image retrieval. This chapter recommends a simple pipeline for encoding the local activations of a convolutional layer of a pretrained CNN utilizing the well-known Bag of Words (BoW) aggregation scheme and called bag of local convolutional features (BLCF). Matching each local array of activations in a convolutional layer to a visual word results in an assignment map, which is a compact representation relating regions of an image with a visual word. We use the assignment map for fast spatial reranking, finding object localizations that are used for query expansion. We show the suitability of the BoW representation based on local CNN features for image retrieval, attaining state-of-the-art performance on the Oxford and Paris buildings benchmarks. We demonstrate that the BLCF system outperforms the latest procedures using sum pooling for a subgroup of the challenging TRECVid INS benchmark according to the mean Average Precision (mAP) metric.
On the Prospects of Using Deep Learning for Surveillance and Security Applications
Authors: Liu Shuo  , John Vijay  , Liu Zheng
Published: February 2025

Convolutional neural networks have achieved great success in computer vision, significant improving the state of the art in image classification, semantic segmentation, object detection and face recognition. In this chapter, we illustrate the advance made by the convolutional neural network (CNN) in surveillance and security applications using two examples. For the surveillance application, a novel military object detector called Deep Fusion Detector was proposed, which incorporates information fusion techniques and the CNN. Specifically, we fused multi-channel images within a CNN to enhance the significance of deep features, and adapted a state-of-the-art generic object detector for military scenario. For the security application, with inspiration from recent advances in the deep learning community, we presented an effective face recognition system called Deep Residual Face. Where the Inception-ResNet CNN architecture was utilized to extracting deep features and the center loss function was adopted for training the face verification network. The extensive experiments showed the effectiveness of the presented methods.
Deep Neural Networks for Image Classification
Authors: Vasuki A.  , Govindaraju S.
Published: February 2025

This chapter gives an insight into Deep Learning Neural Networks and their application to Image Classification / Pattern Recognition. The principle of Convolutional Neural Networks will be described and an in-depth study of the algorithms for image classification will be made. In artificial intelligence, machine learning plays a key role. The algorithm learns when exposed to new data or environment. Object / Pattern Recognition is an integral part of machine learning and image classification is an integral part of such algorithms. The Human Visual System efficiently classifies known objects and also learns easily when exposed to new objects. This capability is being developed in Artificial Neural Networks and there are several types of such networks with increasing capabilities in solving problems. Neural networks themselves have evolved from evolutionary computing techniques that try to simulate the behavior of the human brain in reasoning, recognition and learning. Deep neural networks have powerful architectures with the capability to learn and there are training algorithms that make the networks adapt themselves in machine learning. The networks extract the features from the object and these are used for classification. The chapter concludes with a brief overview of some of the applications / case studies already published in the literature.
Advanced Stevia Disease Detection Using Deep Learning
Authors: Lakshmi S.  , Sivakumar R.
Published: February 2025

Almost all of us are tempted to take sweets due to its pleasant nature. When it is overused, it will affect our body entirely. Diabetic is a disease that occurs when the blood glucose level is high. According to the study of World Health Organization (WHO), the prevalence percentage of diabetic persons is doubled in the last 10 years. Life style, working environment, nature of the work, food habits and hereditary are few reasons for diabetic. Diabetic leads to various health problems like heart disease, stroke, kidney problems, nerves damage, eye and dental problems over time. Stevia is a sugar substitute which is available all over the world and it is proved to give more safety for diabetic patients. Stevia contains proteins, vitamins and minerals. Stevia plant may be affected by various diseases such as root rot, charcoal rot, wilt, leaf spot disease and so on. This chapter demonstrates the deep learning approach to enable the disease detection through image recognition. A deep convolutional neural network is trained to classify the disease affected leaves, achieving the accuracy of over 99%.
Sensitivity Analysis Using a Sparse Grid Surrogate Model in Electromagnetic NDE
Authors: Bingler Arnold  , Bilicz Sándor
Published: February 2025

The global sensitivity analysis of electromagnetic nondestructive evaluation (NDE) by means of Sobol' indices are considered in this work. To reduce the computational burden, a sparse grid surrogate model is used. The latter can simply replace the true simulator to some extent, but it can also be used to numerically evaluate the integrals defining the Sobol' indices. In most of the NDE setups, the output is not a scalar quantity but functional data (e.g., a surface scan); a method is presented to take this into account. The sparse grid based sensitivity analysis is compared to classical techniques via examples drawn from electromagnetic NDE.
Adaptive Image Reconstruction Algorithm for Electrical Capacitance Tomography
Authors: Wang Yan  , Yan Hua
Published: February 2025

Since the image reconstruction of electrical capacitance tomography (ECT) is an inverse problem of ill-posedness, regularization techniques are widely used to obtain stable solutions. The choice of regularization coefficients has a direct influence on the reconstruction result. In theory, the optimal regularization coefficient exists, but for most regularization techniques, the computation cost is too large to apply in real-time ECT image reconstruction. In this paper, a new approach which can determine the regularization coefficient quickly in iterative Tikhonov regularization algorithm for ECT is proposed. In order to improve the quality of the reconstructed image further, an improved method of adaptive threshold filtering is used in the last Tikhonov iteration. The algorithm proposed is tested by the noise-free and noise-contaminated capacitance data. The simulation results demonstrate that the proposed algorithm is superior to well-known Landweber algorithm in terms of image quality.
B-Spline Sparse Grids for Eddy-Current Testing Inverse Problems
Authors: Bilicz Sándor  , Pávó József
Published: February 2025

A sparse grid surrogate model using hierarchical B-spline basis functions is used to approximate the objective function in an optimization-based inversion algorithm. The B-spline basis provides a smooth interpolant of the objective function and the gradient of the interpolant is readily available in closed-form. The latter is used in a gradient-based minimum search algorithm that results in the approximate solution of the inverse problem. The method is computationally more efficient than using gradient-free direct search methods, as illustrated by an example drawn from eddy-current nondestructive testing.
Optimizing Communication and Synchronization in CAF Applications
Authors: Fanfarillo Alessandro  , Del Vento Davide  , Nichols Patrick
Published: February 2025

Since the beginning of distributed computing, overlapping communication with computation has always been an attractive technique used to mask high communication costs. Although easy to detect by a human being, communication/computation overlapping requires knowledge about architectural and network details in order to be performed effectively.
SYCL-BLAS: Combining Expression Trees and Kernel Fusion on Heterogeneous Systems
Authors: Aliaga José I.  , Reyes Ruyman  , Goli Mehdi
Published: February 2025

The support for heterogenous platforms requires multiple specialised devices collaborate to execute an application. The SYCL standard publishes by Khronos, providing a C++ abstraction layer on top of OpenCL that provides single-source programming for a large number of heterogeneous devices. Single-source programming and task data-flow approach enable SYCL developers to leverage modern programming techniques on heterogeneous platforms. In this paper, we present how SYCL combines expression tree templates and kernel fusion to develop SYCL-BLAS, an efficient BLAS implementation for heterogeneous platforms. The use of templates permits to generate BLAS kernels related to each BLAS routine. whereas kernel fusion describes how to merge the expression trees, enlarging the BLAS kernels. These features prove that SYCL can be used to quickly develop libraries for heterogeneous systems by providing sufficient levels of abstraction. Our experiments compare the performances of clBLAS and SYCL-BLAS on a server equipped with an Intel Core i7-6700K CPU and an AMD R9 GPU.
Adaptive Execution of Parallel Programs on Grids and Clouds
Authors: Slawinski Jaroslaw  , Sunderam Vaidy
Published: February 2025

Streamlined switching between computational resources in order to select the most suitable computational environment for parallel application execution is a crucial component of utility-like computing. However, machine heterogeneity obstructs multi-target deployment for complex and multi-dependency scientific parallel codes and makes this aim intractable. We describe a proposal for a metadeployment toolkit, called ADAPT, based on reusable recipes addressing appropriate match-up between an application and an execution platform. Our research aims at exploring challenges posed by transparent application deployment with all its prerequisites on heterogeneous resources. As some IaaS clouds and grids accept customized OS images, we explore application-oriented image assembly to further improve deployment for these specific targets. We explain how our approach increases “usability” of various resources for parallel applications and simplifies arcane build processes.
Optimization of Finite-Differencing Kernels for Numerical Relativity Applications
Authors: Alfieri Roberto  , Bernuzzi Sebastiano  , Perego Albino  , Radice David
Published: February 2025

A simple optimization strategy for the computation of 3D finite-differencing kernels on many-cores architectures is proposed. The 3D finite-differencing computation is split direction-by-direction and exploits two level of parallelism: in-core vectorization and multi-threads shared-memory parallelization. The main application of this method is to accelerate the high-order stencil computations in numerical relativity codes.
Large Scale Low Power Computing System
Authors: Ammendola Roberto  , Biagioni Andrea  , Capuani Fabrizio  , Cretaro Paolo  , De Bonis Giulia  , Lo Cicero Francesca  , Lonardo Alessandro  , Martinelli Michele  , Paolucci Pier Stanislao  , Pastorelli Elena  , Pontisso Luca  , Simula Francesco  , Vicini Piero
Published: February 2025

The deployment of the next generation computing platform at ExaFlops scale requires to solve new technological challenges mainly related to the impressive number (up to 106) of compute elements required. This impacts on system power consumption, in terms of feasibility and costs, and on system scalability and computing efficiency. In this perspective analysis, exploration and evaluation of technologies characterized by low power, high efficiency and high degree of customization is strongly needed. Among the various European initiative targeting the design of ExaFlops system, ExaNeSt and EuroExa are EU-H2020 funded initiatives leveraging on high end MPSoC FPGAs. Last generation MPSoC FPGAs can be seen as non-mainstream but powerful HPC Exascale enabling components thanks to the integration of embedded multi-core, ARM-based low power CPUs and a huge number of hardware resources usable to co-design application oriented accelerators and to develop a low latency high bandwidth network architecture.
Time Collection: An Abstraction for Shared Objects in Parallel Programming
Authors: Hamidi Hamid Reza  , Kermanshahani Shokooh  , Gautier Thierry
Published: February 2025

Random access containers (ex. Arrays) and sequential containers (ex. Lists) are today of the most useful abstractions in sequential programming. They facilitate access to a group of individual objects and provide uniform structure for realizing different semantics of synchronization in concurrent applications. To overcome the same challenges in parallel programming, we propose new abstraction called Time Collection. Parallelism and asynchronism in coupling channels are considered as the main challenges to achieve high performance. The first prototype is implemented on Athapascan parallel programming environment. Coupling of parallel codes is our motivation which is one of the main challenge of recent research projects in multi-disciplinary simulation, interactive multimedia environments and multi-screen visualization.
Runtime System Architecture for Dynamic Adaptive Execution
Authors: Sterling Thomas  , Zhang Bo
Published: February 2025

Even the highest scale contemporary conventional HPC system architectures are optimized for the basic operations and access patterns of classical matrix and vector processing. These include emphasis on FPU utilization, high data reuse requiring temporal and spatial locality, and uniform strides of indexing through regular data structures. Such systems in the 100 Petaflops performance regime such as the Chinese Sunway TaihuLight, and the US CORAL Summit and Sierra to be deployed in 2018, in spite of their innovations, are still limited in these properties. Emerging classes of new application problems in data analytics, machine learning, and knowledge management demand very different operational properties in response to their highly irregular, sparse, and dynamic behaviors exhibiting little or no data reuse, random access patterns, and metadata-dominated parallel processing. At the core of these “big data” applications is dynamic adaptive graph processing, which is in some ways diametrically opposite to conventional matrix computing. Of immediate importance is the need to significantly enhance efficiency and scalability as well as user productivity, performance portability, and reduced energy. Key to success is the introduction of powerful runtime system strategies and software for the exploitation of real-time system information to support dynamic adaptive resource management and task scheduling. But software alone will be insufficient for extreme-scale where near fine-grained parallelism is necessary and software overheads will bound efficiency and scalability. A new era of architecture research is beginning in the combined domains of accelerator hardware for both graph processing and runtime systems. This paper will discuss the nature of the computational challenges, examples and experiments with state-of-the-art runtime system software HPX-5, and future directions in hardware architecture support for exascale runtime-assisted big data computation.
Strengthening NATO-Israel's Naval Cooperation in the Mediterranean Sea
Authors: Barak Michael
Published: February 2025

The Mediterranean Sea is strategically important. Today's international environment is very articulated and many actors are playing a stronger role in in this area. NATO, Russia, Turkey, Russia, Iran as well as China are developing plans of action to be more influential and get ahead of their geopolitical positioning. This paper will focus on how NATO and the other players are also developing key counter-terrorism activities and how Israel is being more determinant as a member of the Mediterranean Dialogue.
Hardware Rooted Security in Industry 4.0 Systems
Authors: Zaidenberg Nezer Jacob
Published: February 2025

Industry 4.0 is the name for the latest trend in industrial systems for automation of services, cyber physical system and data exchange between multiple players. These system have unique trusted computing cyber requirements. Many time the machine is pitted against a MATE (Man at-the-end) adversary. MATE threats require new requirements on hardware. These requirements are addressed by virtually all major hardware vendors. In this chapter we will discuss the threats, hardware capabilities and use cases offered by major hardware vendors to address Industry 4.0 hardware requirements.
A Strategy of Providing Upgradable Product Service System for Economic and Environmental Balance
Authors: Yamada Shuho  , Sugiura Takumi  , Yamada Tetsuo  , Bracke Stefan  , Inoue Masato
Published: February 2025

For the attainment of sustainable society, not only reducing resource usage, disposal and environmental load but also saving consumer's payment for receiving product and service and yielding high profit for product and service provider are necessary. This paper proposes a planning method for determination of upgrading strategy for upgradable product service system: Up-PSS that is the one of the sustainable developing and consumption business model. The meaning of sustainability in this study is generating larger profit for service provider with cheaper service cost (price) for customers and lower environmental impact for the earth compared with traditional product selling. Hence, this study defines lifecycle cost, profit, and environmental load emission as considerable agendas. At first, this study discusses the occurrence factor of Up-PSS's cost and environmental load in the entire lifecycle of an upgradable product. Second, this paper proposes a decision-making method for particular upgrading way such as send-back upgrade and serviceman upgrade. Third, modeling mothed for lifecycle cost, profit, and environmental load is shown by using aforementioned occurrence factors. Finally, proposed method is applied to a packaged product leasing as a case study. The result of case study attained lower price, higher profit, and lower environmental load in the periodic product lifecycle than conventional product selling by obtaining appropriate profit rate, product using generation, and upgrading amount.
Concept Development for CAD Model Adaptation to a Change from Injection Molding to Additive Manufacturing
Authors: Bondar Sergej  , Eufinger Jens  , Stjepandić Josip  , Vetter Dominik
Published: February 2025

The continuous spread of additive manufacturing also raises the question of what procedure to recommend when changing the manufacturing method of already constructed parts from injection molding to additive manufacturing. To answer this question, the differences between the two manufacturing processes and the respective end products are first presented. Based on this presentation, a concept for the adaptation of the CAD models affected by the changeover is developed. The goal is a procedural change that is as complication-free as possible. At the end, the finished concept will be reviewed in terms of its utility and its applicability to a specific example. In addition, a boundary between the CAD model adaptation and a new design of the components is drawn in the sense of a stress-related design.
Deriving Functional Requirements for Industry 4.0 from Industry's Assessment of Needs
Authors: Vickery Andrew  , Rauch Erwin  , Brown Christopher A.
Published: February 2025

Functional requirements (FRs) are derived from perceptions of needs expressed at workshops by small and medium enterprises (SMEs) organized to identify the requirements of SMEs to introduce Industry 4.0 in their company Rather than good expressions of customer needs (CNs), SME representatives often propose partial physical solutions, such as a robot, rather than basic needs, like orient and load parts. In Axiomatic Design (AD) the CNs are used to formulate FRs, which should be solution-neutral, to provide a large solution space, facilitating creativity and innovation in the design process. The workshops, as part of Horizons 2020 EU project, aimed to gain customer needs from SME's so that these needs could be researched and answered in future research These partial solutions proposed by the SMEs are analyzed in order to reverse engineer customer needs and functional requirements. These same reverse engineering methods also could be used to derive FRs from existing design solutions and could aid inexperienced designers who struggle to generate good, solution-neutral FRs that are appropriately devoid of physical attributes. Previous works are using a similar approach to taking the customers' proposed partial solutions and reverse engineering the FRs and CNs.
Inclusion Through Robotics: Designing Human-Robot Collaboration for Handicapped Workers
Authors: Kremer David  , Hermann Sibylle  , Henkel Christian  , Schneider Matthias
Published: February 2025

In the project AQUIAS, a pilot for division of labor in human-robot collaboration was developed, in order to support work quality and healthy working conditions for severely disabled production workers at the valve assembly of ISAK gGmbH. The interdisciplinary research team strived to harmonize the design criteria for the human-robot collaboration development, including technical feasability, safety, ergonomics, work quality, inclusion, and profitability.
Impact of Simulated Gaze Gestures on Social Interaction for People with Visual Impairments
Authors: Qiu Shi  , Han Ting  , Rauterberg Matthias  , Hu Jun
Published: February 2025

Gaze and eye contact have important social meanings in our daily lives. The sighted often uses gaze gestures in communication to convey nonverbal information that a blind interlocutor cannot access and react to. In many examples, blind people's eyes are unattractive, and often with deformities, which makes the eye appearance less appealing to the sighted. All of these factors influence the smooth face-to-face communication between the blind and sighted people, which leads to blind people's poor adaptions in the communication. We implemented a working prototype, namely E-Gaze (glasses), an assistive device based on an eye tracking system. E-Gaze attempts to simulate the natural gaze for blind people, especially establishing the “eye contact” between the blind and sighted people to enhance the engagement in the face-to-face communication. The interactive gaze behaviors of the E-Gaze are based on a model that combines a turn-taking strategy and the eye-contact mechanism. In order to test the impact of the interactive gaze model in the face-to-face communication, we conducted an experiment with sixteen participants. In the user experiment, participants had a monologue with a dummy wearing the E-Gaze. Two monologues took place under two experimental conditions (i.e., Interactive Gaze and Random Gaze) with counter balancing to avoid carry-over effects. Results well support the hypothesis that the interactive gaze model of the E-Gaze can enable the sighted to feel attention from the listener, enhancing the level of engagement in the face-to-face communication. We also obtain insights and design implications from participants' comments.
Simulation and Analysis of an Automotive Active Head Restraint
Authors: Polorotoff Terence  , Bil Cees
Published: February 2025

Safety is an important aspect in automotive vehicle design. The New Car Assessment Program (NCAP) provides the industry with a quantifiable assessment of the safety of their vehicles. With NCAP moving to introduce head restraint performance as a component of their assessment of vehicle safety, automotive manufacturers are developing methods to improve the safety of their head restraints. The philosophy is to reduce neck injuries., but most occupants do not position the headrest optimally for safety, thus an active system is the most effective approach. Previous assessment of the performance of the active head restraint systems has generally been accomplished by sled tests. Such methods can be a drain on resources, and do not allow for efficient optimisation of the system. A computer model allows for numerous tests to be run to assess the performance of several optimised designs before manufacturing of the seat begins. This paper describes the simulation and analysis of an Active Head Restraint system against a baseline system.
Research and Analysis of Opportunities in Product Development Cost Estimation Through Expert Systems
Authors: Voltolini Rafael  , Vasconcelos Kaio  , Borsato Milton  , Peruzzini Margherita
Published: February 2025

The early stages of product development are characterized by uncertainties and assumption of parameters that directly affect the product and project costs, the development time, and the quality of the manufacturing process. Designers must deal with challenges that arise unexpectedly in an agile and responsive manner. Expert information systems based on ontological models are a promising approach to capture knowledge and rationale of domain specialists, either for decision making or knowledge reuse. The present study presents a bibliometric analysis on the use of ontologies in product development for cost estimation. It identifies trends and research opportunities that can orient future works. From a general search in scientific databases that originally listed thousands of entries, 31 articles were found and selected based on criteria established using the Proknow-C method. The outcome of the present study can help researchers in the search of relevant research gaps to guide future scientific investigations in the area of knowledge-based cost estimation for product development. Results indicate that there are several possibilities for solutions using ontological and hybrid, transdisciplinary approaches. In the search for solutions that support the product cost estimation in the early stages of development, the use of intelligent systems is not only promising, but is also challenging as a new and real transdisciplinary research area of interest.
Use of Corporate and Consumer Knowledge in Product Development: Bibliometric and Systemic Analysis
Authors: Kulaitis Junior Alvaro Cesar  , Borsato Milton  , Gobbo Junior Otavio
Published: February 2025

Companies need to be agile to face today's market competition, as well as the demand for new products from consumers. In this context, product development can benefit from corporate knowledge and consumer knowledge to reduce the time to launch new products. This article review study seeks to locate studies related to this subject, as well as opportunities for new research. To this end, the ProKnow-C process was used to select a bibliographic portfolio and conduct bibliometric analysis and systemic analysis. In the first stage, 23 articles were selected. They were analyzed quantitatively to identify the most important studies, authors and journals. In the systemic analysis the articles were evaluated in order to identify gaps in the research related to the topic.