Product Representation Research Articles

Ulus Markalaşması Bağlamında Coğrafi İşaretli Ürünlerin Göstergebilimsel Analizi: Türkiye Örneği

Increasing a country’s reputation is directly proportional to reflecting its good to the masses in the international arena. Geographical indication (GI) products have a vital position in the sense of country branding and destination. This research aims to analyse the images related to GI products in the Türkiye’s promotional posters. The research was analysed with the semiotics method and differed from other studies as it makes the hidden message in the images visible. The study is vital in analysing the representations of GI products on country promotion posters within the framework of nation branding. These visuals which were prepared by the Ministry of Culture and Tourism regarding the promotion of the Türkiye between the years 2014-2019 constitute the universe of the study. Those images since then are the only promotional images on the website of the ministry. Therefore, this date range has been taken into account. When the GI products in the Türkiye’s promotional posters are considered, it is seen that food and beverages are at the forefront. Also, the Turkish eating habits are given priorities on the posters and introductory information explaining GI of products which is Türkiye. In this context, it has been concluded that these posters play a major promotional role.

Heterogeneous star graph attention network for product attributes prediction

The target of product attributes prediction is to complete the characteristics set for defining a particular product. Most of the existing methods treat the product attributes prediction as a Named-Entity Recognition (NER) problem from the products’ affiliated data, such as product title and introduction. However, in a large number of industrial applications of Alibaba, we found that the existing methods are good at concrete attributes extraction (e.g., color, size) but short of abstract attributes extraction (e.g., applicable event). Moreover, these abstract attributes are usually not easy to extract from the products’ affiliated data. In this paper, we propose a novel heterogeneous star graph attention network called “SAN”, which incorporates the advantages of multiple information in the e-commerce scene to predict the abstract attributes of products. Specifically, we model the customer interactive behaviors, product title and concrete attributes of a product as a star graph. Then, we extract the node features, node types and graph structure information from the heterogeneous star graph network which consists of n star graphs. By leveraging the parallel multiple attention mechanism, SAN can aggregate features and learn weights of nodes for product representation and abstract attribute prediction. Extensive experimental results of a real-world e-commerce dataset have demonstrated that SAN outperforms state-of-the-art methods significantly for product attributes prediction. These series of solutions are already planned for use in the applications of Alibaba.

Worldline description of a bi-adjoint scalar and the zeroth copy

Bi-adjoint scalars are helpful in studying properties of color/kinematics duality and the double copy, which relates scattering amplitudes of gauge and gravity theories. Here we study bi-adjoint scalars from a worldline perspective. We show how a global G × overset{sim }{G} symmetry group may be realized by worldline degrees of freedom. The worldline action gives rise to vertex operators, which are compared to similar ones describing the coupling to gauge fields and gravity, thus exposing the color/kinematics interplay in this framework. The action is quantized by path integrals to find a worldline representation of the one-loop QFT effective action of the bi-adjoint scalar cubic theory. As simple applications, we recover the one-loop beta function of the theory in six dimensions, verifying its vanishing, and compute the self-energy correction to the propagator. The model is easily extendable to that of a particle carrying an arbitrary representation of direct products of global symmetry groups, including the multi-adjoint particle, whose one-loop beta function we reproduce as well.

Coorbit spaces associated to integrably admissible dilation groups

This paper considers coorbit spaces parametrized by mixed, weighted Lebesgue spaces with respect to the quasi-regular representation of the semi-direct product of Euclidean space and a suitable matrix dilation group. The class of dilation groups that we allow, the so-called integrably admissible dilation groups, contains the matrix groups yielding an irreducible, square-integrable quasi-regular representation as a proper subclass. The obtained scale of coorbit spaces extends therefore the well-studied wavelet coorbit spaces associated to discrete series representations. We show that for any integrably admissible dilation group there exists a convienent space of smooth, admissible analyzing vectors that can be used to define a consistent coorbit space possessing all the essential properties that are known to hold in the setting of discrete series representations. In particular, the obtained coorbit spaces can be realized as Besov-type decomposition spaces by means of a Littlewood—Paley-type characterization. The classes of anisotropic Besov spaces associated to expansive matrices are shown to coincide precisely with the coorbit spaces induced by the integrably admissible one-parameter groups.

Crafting Representation: Deploying Racecraftian Techniques to Critique Gender- and Sexuality-Swapping in HBO's Lovecraft Country

Even with a significant increase in representation of minority identities in popular media – especially in stories of speculative fiction – the ways in which inclusivity is designed must be examined, with Lovecraft Country standing as a useful example for this scrutiny. Adapted from a novel of the same name, the show Lovecraft Country swapped the genders and sexualities of a few characters from the book to increase representation. The ways that these swaps reified tropes about diverse identities is the central concern of this analysis. Using Fields and Fields's conceptualization of racecraft as a "mental terrain of pervasive beliefs," this piece seeks to identify how pervasive beliefs and rules about identity were implicated in the series. The characters of Montrose Freeman, Ruby Baptiste, and Christina Braithwhite all undergo gender and/or sexuality swaps in the adaptation from page to screen, but the ways in which stereotypical assumptions around gender and sexuality are preserved in the narrative work mostly to reproduce negative tropes around these identities. This argument details narratives of violence, avoidance, and sacrifice that are given to these gender- and sexuality-swapped characters, and illustrates how, ultimately, these narratives provide detrimental instead of productive representation of diverse identities.

Multi-view Graph Attention Network for Travel Recommendation

As an e-commerce feature, the recommender system can enhance the consumer shopping experience and create huge benefits for businesses. The e-tourism has become one of the largest service industries with the application and popularity of recommender systems. Many studies have confirmed that the travel product recommendation is widely different from traditional recommendations. Due to the financial and time costs, travel products are usually browsed and purchased relatively infrequently compared with other traditional products (e.g., books, movies and food). In addition, choosing the appropriate travel product will be influenced by many factors, such as departure, destination and price. To tackle this challenging problem, we propose a MV-GAN (short for Multi-View Graph Attention Network for travel recommendation) model. It enriches user and product semantics through both metapath-guided neighbors aggregation and multi-view fusion in heterogeneous travel product recommendation graph. In particular, we design node-level and path-level attention networks for learning user and product representations from every single view. To collaboratively integrate multiple types of relationships in different views, a view-level attention mechanism is proposed to aggregate the node representations and obtain global user and product representations. We evaluate the proposed method on a public dataset and a dataset constructed from a large tourism e-commerce website in China. Extensive experiments not only validate the effectiveness of MV-GAN, but also show its potentially good interpretability.

MANUFACTURING OF RAPID PROTOTYPES OF MECHANICAL PARTS USING REVERSE ENGINEERING AND 3D PRINTING

This article focuses on the design and manufacture of mechanical parts that have complicated shapes using the technique of reverse design using a scanner or an MMT for data acquisition in the form of a point cloud, using CAD software (CATIA). The digital model created is used for a virtual representation of the final product. Then we get the physical model on a 3D printer (also called additive manufacturing process) for later use in sand moulds. To have the imprint in the sand mould, we go through the fusion of the physical model (part). The use of this technique in the industry, allows us to save a lot of time in terms of model preparation and simple to implement, especially if it is mechanical parts that do not have a definition drawing, or they are worn out, then structural analysis was applied on the model using FE based software and tools to prove the quality of the product. Von Mises equivalent strains and stresses were predicted and decreased with increasing areas and honeycomb thickness. The objective of this article is to give an overview of this relatively modern technology and its various applications.

Anomaly detection: A functional analysis perspective

We develop a new approach for detecting anomalies in the behavior of stochastic processes and random fields. The approach uses tensor product representations, in particular the multivariate Karhunen–Loève (KL) expansion on complex domains. From the associated eigenspaces of the covariance operator a series of nested function spaces are constructed, allowing detection of signals lying in orthogonal subspaces. In particular this can succeed even if the stochastic behavior of the signal changes either in a global or local sense. A mathematical approach is developed to locate and measure sizes of extraneous components based on construction of multilevel nested subspaces. We show examples in R and on a spherical domain S2. However, the method is flexible, allowing the detection of orthogonal signals on general topologies, including spatio-temporal domains.

Estimating global land system impacts of timber plantations using MAgPIE 4.3.5

Abstract. Out of 1150 Mha (million hectares) of forest designated primarily for production purposes in 2020, plantations accounted for 11 % (131 Mha) of this area and fulfilled more than 33 % of the global industrial roundwood demand. However, adding additional timber plantations to meet increasing timber demand intensifies competition for scarce land resources between different land uses such as food, feed, livestock and timber production. Despite the significance of plantations with respect to roundwood production, their importance in meeting the long-term timber demand and the implications of plantation expansion for overall land-use dynamics have not been studied in detail, in particular regarding the competition for land between agriculture and forestry in existing land-use models. This paper describes the extension of the modular, open-source land system Model of Agricultural Production and its Impact on the Environment (MAgPIE) using a detailed representation of forest land, timber production and timber demand dynamics. These extensions allow for a better understanding of the land-use dynamics (including competition for land) and the associated land-use change emissions of timber production. We show that the spatial cropland patterns differ when timber production is accounted for, indicating that timber plantations compete with cropland for the same scarce land resources. When plantations are established on cropland, it causes cropland expansion and deforestation elsewhere. Using the exogenous extrapolation of historical roundwood production from plantations, future timber demand and plantation rotation lengths, we model the future spatial expansion of forest plantations. As a result of increasing timber demand, we show a 177 % increase in plantation area by the end of the century (+171 Mha in 1995–2100). We also observe (in our model results) that the increasing demand for timber amplifies the scarcity of land, which is indicated by shifting agricultural land-use patterns and increasing yields from cropland compared with a case without forestry. Through the inclusion of new forest plantation and natural forest dynamics, our estimates of land-related CO2 emissions better match with observed data, in particular the gross land-use change emissions and carbon uptake (via regrowth), reflecting higher deforestation with the expansion of managed land and timber production as well as higher regrowth in natural forests and plantations.

Optimality-based modelling of climate impacts on global potential wheat yield

Evaluation of potential crop yields is important for global food security assessment because it represents the biophysical ‘ceiling’ determined by variety, climate and ambient CO2. Statistical approaches have limitations when assessing future potential yields, while large differences between results obtained using process-based models reflect uncertainties in model parameterisations. Here we simulate the potential yield of wheat across the present-day wheat-growing areas, using a new global model that couples a parameter-sparse, optimality-based representation of gross primary production (GPP) to empirical functions relating GPP, biomass production and yield. The model reconciles the transparency and parsimony of statistical models with a mechanistic grounding in the standard model of C3 photosynthesis, and seamlessly integrates photosynthetic acclimation and CO2 fertilization effects. The model accurately predicted the CO2 response observed in FACE experiments, and captured the magnitude and spatial pattern of EARTHSTAT ‘attainable yield’ data in 2000 CE better than process-based models in ISIMIP. Global simulations of potential yield during 1981–2016 were analysed in parallel with global historical data on actual yield, in order to test the hypothesis that environmental effects on modelled potential yields would also be shown in observed actual yields. Higher temperatures are thereby shown to have negatively affected (potential and actual) yields over much of the world. Greater solar radiation is associated with higher yields in humid regions, but lower yields in semi-arid regions. Greater precipitation is associated with higher yields in semi-arid regions. The effect of rising CO2 is reflected in increasing actual yield, but trends in actual yield are stronger than the CO2 effect in many regions, presumably because they also include effects of crop breeding and improved management. We present this hybrid modelling approach as a useful addition to the toolkit for assessing global environmental change impacts on the growth and yield of arable crops.

Construction of auditory bombardment therapy program: a pilot study

Abstract Background Speech sound disorder is a communication disorder in which children have persistent difficulty saying words or sounds correctly. It refers to any difficulty or combination of difficulties with perception, motor production, or phonological representation of speech sounds and speech segments. Aim of the Work to construct an Arabic auditory bombardment therapy program and measure its effectiveness in treatment of functional speech sound disorder. Subjects and Methods This study was applied on 60 participants divided into 2 groups (30 for each group) with age ranging from 3-5 years diagnosed with functional speech sound disorder with or without language disorders, attending at the Phoniatrics outpatient clinic in Ain Shams University Hospitals. The test for identification of phonological processes was applied on 60 patients with speech sound disorder selected to participate in this study. These were divided in to 2 groups (Group (1) received only the conventional therapy while group (2) received auditory bombardment in addition to the conventional therapy for 3 months) and the test was repeated again after therapy. Results Group (2) showed high significant difference (improvement) in consonant assimilation, voicing change, final consonant deletion, palatal fronting, gliding, lateralization and glottal replacement while group (1) showed high significant difference (improvement) in syllable deletion and partial cluster reduction. Conclusion The present study showed that application of auditory bombardment therapy program in addition to conventional therapy has high significant improvement than conventional therapy alone.

Hecke–Rogers type series representations for infinite products

Hecke–Rogers type series representations for infinite products

Learning from Substitutable and Complementary Relations for Graph-based Sequential Product Recommendation

Sequential product recommendation, aiming at predicting the products that a target user will interact with soon, has become a hotspot topic. Most of the sequential recommendation models focus on learning from users’ interacted product sequences in a purely data-driven manner. However, they largely overlook the knowledgeable substitutable and complementary relations between products. To address this issue, we propose a novel Substitutable and Complementary Graph-based Sequential Product Recommendation model, namely, SCG-SPRe. The innovations of SCG-SPRe lie in its two main modules: (1) The module of interactive graph neural networks jointly encodes the high-order product correlations in the substitutable graph and the complementary graph into two types of relation-specific product representations. (2) The module of kernel-enhanced transformer networks adaptively fuses multiple temporal kernels to characterize the unique temporal patterns between a candidate product to be recommended and any interacted product in a target behavior sequence. Thanks to the seamless integration of the two modules, SCG-SPRe obtains candidate-dependent user representations for different candidate products to compute the corresponding ranking scores. We conduct extensive experiments on three public datasets, demonstrating SCG-SPRe is superior to competitive sequential recommendation baselines and validating the benefits of explicitly modeling the product-product relations.

Inductive limits of compact quantum groups and their unitary representations

We introduce inductive limits of compact quantum groups and their unitary representation theories. Those give a more explicit representation-theoretic meaning to our previous study of quantization of characters and central probability measures in the asymptotic representation theory. We also study tensor product representations of the infinite-dimensional quantum unitary group. As a by-product, we give an explicit representation-theoretic interpretation to certain transformations that play an important role in analyzing q-central probability measures on the paths in the q-Gelfand–Tsetlin graph.

The Effect of Role-Based Product Representations on Individual and Team Coordination Practices: A Field Study of a Globally Distributed New Product Development Team

The investigation of the appealing indication that a modular product architecture is best associated to a loosely coupled organizational structure—that is, the mirroring hypothesis—has produced contradictory evidence, especially in the dynamic and ambiguous context of new product development. By integrating modularity theory and product-representation theories, we investigate how individual agency affects coordination in teams developing modular products. We conducted a field study of Flower-Net, a globally distributed team in a major IT company, engaged with the development of a modular software using agile practices. Our grounded model shows that, whereas top managers defined the product as modular and coordinated work accordingly, individuals developed different representations of the product’s architecture and conflicting individual coordination practices. We traced the individual development of product architecture representations back to the individual interpretations of organizational roles as more or less “segmented.” Conflicting individual practices, associated to different role-based product representations, were not addressed by the team—that developed a state of illusory concordance—and impaired the functioning of the team. This study contributes to the literature on modularity and the mirroring hypothesis by proposing individual role-based representations as an underexplored level of analysis for the matching between product and organizational modularity (Mirroring Hypothesis II). It also contributes to the debate on how representations affect team coordination, by detailing how role-based product representations can influence team members’ divergence and sustain illusory concordance.

Mapping the postharvest life of imported fruits from packhouse to retail stores using physics-based digital twins

Controlling the hygrothermal conditions around fresh fruit and vegetables is vital for their preservation. Therefore, cold chain stakeholders often measure temperature along the supply chain of fresh produce. However, the temperature is typically monitored only in one segment of the entire cold chain, namely from the supplier until the distribution center. Besides, such measured data are rarely used for decision-making because they are not translated into the impact on the quality of the products. We provide a solution by extending the monitoring until the retail stores and upcycling these thermal data into actionable metrics. To do so, we use physics-based digital twins, namely virtual representations of the food products. This study focuses on 331 cold chain shipments of cucumber, eggplant, strawberry, and raspberry imported from Spain to Switzerland. We followed these fruits through pre-cooling, thermally stable conditions at the distribution center, and the temperature ramp-up phase before arriving at the retail store. The temperature performance of each carrier and flow analysis of the shipment enabled us to map the complex logistic system better. The digital twins detected that the fruits lost 43 - 85% of their quality before being displayed at the retail store. This quality loss remains invisible to the retailer. Additionally, we found a strong correlation between fruit quality and shipment duration (i.e., for cucumber r = -0.95 (P < 0.001)), which emphasizes the importance of shortening the shipment to prolong the freshness of the fruit. The digital twins have shown a large potential to help further maximize shelf life and uniform product quality.

Cluster solutions in networks of weakly coupled oscillators on a 2D square torus

&#x0D; &#x0D; &#x0D; We consider a model for an N × N lattice network of weakly coupled neural oscilla- tors with periodic boundary conditions (2D square torus), where the coupling between neurons is assumed to be within a von Neumann neighborhood of size r, denoted as von Neumann r-neighborhood. Using the phase model reduction technique, we study the existence of cluster solutions with constant phase differences (Ψh, Ψv) between adjacent oscillators along the horizontal and vertical directions in our network, where Ψh and Ψv are not necessarily to be identical. Applying the Kronecker production representation and the circulant matrix theory, we develop a novel approach to analyze the stability of cluster solutions with constant phase difference (i.e., Ψh,Ψv are equal). We begin our analysis by deriving the precise conditions for stability of such cluster solutions with von Neumann 1-neighborhood and 2 neighborhood couplings, and then we generalize our result to von Neumann r-neighborhood coupling for arbitrary neighborhood size r ≥ 1. This developed approach for the stability analysis indeed can be extended to an arbitrary coupling in our network. Finally, numerical simulations are used to validate the above analytical results for various values of N and r by considering an inhibitory network of Morris-Lecar neurons.&#x0D; &#x0D; &#x0D;

Perfect extensions of de Morgan algebras

An algebra \(\mathbf{A}\) is called a perfect extension of its subalgebra \(\mathbf{B}\) if every congruence of \(\mathbf{B}\) has a unique extension to \(\mathbf{A}\). This terminology was used by Blyth and Varlet [1994]. In the case of lattices, this concept was described by Grätzer and Wehrung [1999] by saying that \(\mathbf{A}\) is a congruence-preserving extension of \(\mathbf{B}\). Not many investigations of this concept have been carried out so far. The present authors in another recent study faced the question of when a de Morgan algebra \(\mathbf{M}\) is perfect extension of its Boolean subalgebra \(B(\mathbf{M})\), the so-called skeleton of \(\mathbf{M}\). In this note a full solution to this interesting problem is given. The theory of natural dualities in the sense of Davey and Werner [1983] and Clark and Davey [1998], as well as Boolean product representations, are used as the main tools to obtain the solution.

Bee Products: A Representation of Biodiversity, Sustainability, and Health

Biodiversity strengthens the productivity of any ecosystem (agricultural land, forest, lake, etc.). The loss of biodiversity contributes to food and energy insecurity; increases vulnerability to natural disasters, such as floods or tropical storms; and decreases the quality of both life and health. Wild and managed bees play a key role in maintaining the biodiversity and in the recovery and restoration of degraded habitats. The novelty character of this perspective is to give an updated representation of bee products’ biodiversity, sustainability, and health relationship. The role of bees as bioindicators, their importance in the conservation of biodiversity, their ecosystem services, and the variety of the bee products are described herein. An overview of the main components of bee products, their biological potentials, and health is highlighted and detailed as follows: (i) nutritional value of bee products, (ii) bioactive profile of bee products and the related beneficial properties; (iii) focus on honey and health through a literature quantitative analysis, and (iv) bee products explored through databases. Moreover, as an example of the interconnection between health, biodiversity, and sustainability, a case study, namely the “Cellulose Park”, realized in Rome (Italy), is presented here. This case study highlights how bee activities can be used to assess and track changes in the quality of agricultural ecosystems—hive products could be valid indicators of the quality and health of the surrounding environment, as well as the changes induced by the biotic and abiotic factors that impact the sustainability of agricultural production and biodiversity conservation in peri-urban areas.

Simulation of the business processes of the developing enterprise to create complex products with multi-level component architecture

The problem of research of business processes related to the organization and management of projects to create the new complex technical products in aerospace, shipbuilding, and other fields of mechanical engineering is stated and solved. The relevance of the study is related to the planning of a set of business processes, taking into account the architectural representation of the complex product being created. The study aims to develop a new method of synthesis of the multilevel complex of business processes to manage the creation of new technology, taking into account the multi-component representation of the complex product architecture. Much attention is paid to the complex product architecture, which is presented as a set of interconnected components. The following component types are outlined: components that can be reused; components that can be adapted to the requirements of the new product; innovative components. The types of components are studied in terms of the building of the set of business processes on their creation, taking into account the main indicators (costs, execution time, risks). Using the positive experience of past developments in the form of ready-to-use business processes helps to minimize the risks, and the new business solutions in their turn ensure the competitiveness of the complex product. The information base of positive past business processes in the form of precedents base is being built. The precedents base is used to find the close analogs of ready-to-use business processes. The set of business processes related to the management of complex product creation is formed. It has a multilevel representation that fully corresponds to the tree-like component architecture of the complex product. The method to synthesize the complexity of business processes that are planned to perform the tasks on the management of projects on creation of complex products for the developing enterprise is constructed. It is based on the “from top to bottom” system design principle. The optimization model to find the minimum costs, time, and risks in the process of business processes creation that takes into account the multilevel structure of the business process is built. The simulation event-based model in the form of a related agent set is used to study the successful execution of planned business processes related to the creation of the complex product. The results of this study should be used in the practice of creating innovative technical products that have a complex multi-level component architecture for the organization and planning of business processes related to development management. Mathematical methods used: systems analysis, precedent theory, lexicographic ordering, component design, integer optimization, simulation modeling.