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Software platform ecosystems are emerging as a dominant model for IT-based services. To accelerate third-party development, platform owners often waive restrictions on app user interfaces to provide app developers with more autonomy in interface design. The literature has indicated, however, that standardized interface design across products is a strategic necessity for firms to introduce and manage their product lines, suggesting that platform owners should not waive restrictions on app user interfaces. This tension between the two approaches raises a crucial research question: Does standardized interface design used by apps and their host platform benefit the platform and apps that it hosts? Specifically, does the coordinated design approach enhance or hinder usage between the platform and apps such that apps attract usage from their host platform and vice versa? Drawing on the theory of basic Gestalts, we theorize the three interface design properties of interface similarity, embeddedness, and synchrony, and extend the theory to investigate how these properties help both apps and their host platform attract each other's users, thus reflecting derivative usage between them. We performed a randomized field experiment to test the proposed hypotheses. The results reveal that interface similarity, embeddedness, and synchrony of the app-platform interface design strengthen users' grouping perception of the platform and its apps, thus enhancing platform-to-app forward derivative usage. Contrary to our expectations, we found that this strengthened grouping perception does not improve the app-to-platform backward derivative usage. These findings have crucial implications for the value of interface design in software platform ecosystems. [ABSTRACT FROM AUTHOR]

In the early time of oilfield development, insufficient production data and unclear understanding of oil production presented a challenge to reservoir engineers in devising effective development plans. To address this challenge, this study proposes a method using data mining technology to search for similar oil fields and predict well productivity. A query system of 135 analogy parameters is established based on geological and reservoir engineering research, and the weight values of these parameters are calculated using a data algorithm to establish an analogy system. The fuzzy matter-element algorithm is then used to calculate the similarity between oil fields, with fields having similarity greater than 70% identified as similar oil fields. Using similar oil fields as sample data, 8 important factors affecting well productivity are identified using the Pearson coefficient and mean decrease impurity (MDI) method. To establish productivity prediction models, linear regression (LR), random forest regression (RF), support vector regression (SVR), backpropagation (BP), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) algorithms are used. Their performance is evaluated using the coefficient of determination (R²), explained variance score (EV), mean squared error (MSE), and mean absolute error (MAE) metrics. The LightGBM model is selected to predict the productivity of 30 wells in the PL field with an average error of only 6.31%, which significantly improves the accuracy of the productivity prediction and meets the application requirements in the field. Finally, a software platform integrating data query, oil field analogy, productivity prediction, and knowledge base is established to identify patterns in massive reservoir development data and provide valuable technical references for new reservoir development. [ABSTRACT FROM AUTHOR]

Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the most important factors. This study aimed to analyze the performance of the coronary artery segmentation of a software platform with a deep learning-based location-adaptive threshold method (DL-LATM) against commercially available software platforms using CCTA. The dataset from intravascular ultrasound (IVUS) of 26 vessel segments from 19 patients was used as the gold standard to evaluate the performance of each software platform. Statistical analyses (Pearson correlation coefficient [PCC], intraclass correlation coefficient [ICC], and Bland-Altman plot) were conducted for the lumen or plaque parameters by comparing the dataset of each software platform with IVUS. The software platform with DL-LATM showed the bias closest to zero for detecting lumen volume (mean difference = -9.1 mm3, 95% confidence interval [CI] = -18.6 to 0.4 mm3) or area (mean difference = -0.72 mm2, 95% CI = -0.80 to -0.64 mm2) with the highest PCC and ICC. Moreover, lumen or plaque area in the stenotic region was analyzed. The software platform with DL-LATM showed the bias closest to zero for detecting lumen (mean difference = -0.07 mm2, 95% CI = -0.16 to 0.02 mm2) or plaque area (mean difference = 1.70 mm2, 95% CI = 1.37 to 2.03 mm2) in the stenotic region with significantly higher correlation coefficient than other commercially available software platforms (p < 0.001). The result shows that the software platform with DL-LATM has the potential to serve as an aiding system for CAD evaluation. [ABSTRACT FROM AUTHOR]

Purpose: of the article is to develop a model of the value system of Russian youth, which can form the basis for the formation of the orientations of young people necessary for the state, contributing to the sustainable development of the Russian Federation. Methods: the article used both traditional methods of scientifi c analysis and methods of Bayesian intelligent measurement methodology used in conditions of uncertainty, inaccuracy and incompleteness of data characteristic of social and socio-economic systems. Results: in the presented study, the extensible hierarchical information model of the value system of Russian youth has been developed. The methodology for processing questionnaire data has been developed, the results of which are presented on numerical and linguistic scales, which makes it possible to take into account the uncertainty of the information received. According to the results of the survey of university students of 10 subjects of the Russian Federation aged 17 to 30 years, a total of 1816 people obtained the values of factors characterizing the value world of Russian youth, which allowed her to form her portrait. Some value factors of young people of the Tula region are evaluated and analyzed. Conclusions and Relevance: the proposed model and methodology for processing personal data allows us to create the adequate holistic portrait of Russian youth in modern economic conditions. The formation of two groups of young people characterized by unfavorable and favorable value attitudes towards Russian society has been revealed, which in the future may lead to a confl ict of social and economic interests, thereby negatively aff ecting the pace of economic growth and sustainable development of the state. In order to reduce internal tension between youth groups and the formation of values inherent in Russian society, measures at the federal and regional levels are proposed.

This article presents a comprehensive study on the development and integration of the mesoscopic and microscopic layers within the control architecture of railway systems, enabling autonomous operation. A key outcome of this research is developing a software platform that provides the foundation for improving autonomous train control algorithms. The mesoscopic layer, defined as the high-level component of the automatic train operation (ATO) subsystem, focuses on generating setpoints to control the traction system, which are subsequently transmitted to the low-level component of the ATO subsystem. A simplified model is employed in the mesoscopic layer to enhance planning capabilities and facilitate efficient decision-making processes, while a detailed model represents the physical system. Simulations evaluate the effectiveness of this integrated system, considering various disturbances to thoroughly assess the performance of the mesoscopic layer algorithm and the microscopic layer control system. The results confirm that by successfully integrating these layers, precise and efficient control of train motion is achieved while considering all constraints imposed by the macroscopic layer. Furthermore, this software platform is set for future development, including implementing intelligent control techniques to enhance autonomous train control.

Normally in the past, the complexity of creation was only faced by the industry. Industry had the information and technology to meet the challenge and try to succeed. Today, those two ingredients are within the reach of anyone, especially university students. This is the turning point to target education toward the spirit of creation, and away from the still current aging spirit of being employed. Humanity is pushing for creation, whatever its origin, to be used for growth, productivity, welfare development and aligned with nature, making the act of creation a deeply conscious and responsible activity. Universities around the world are moving their infrastructures into these waters of education for creation, students are entering training spaces to meet immediate qualification needs, and societies are requesting an ocean of solutions. This work is focused on integrating a solution that can empower universities and students to fulfill the goal of becoming epicenters of creations, in tune with nature, and train future responsive entrepreneurs for the world. Volition is a cloud-based engine in the form of a platform for its users to become aware of the challenge of creating a solution for the market, become disciplined experts in the execution of each business responsibility, and discover what customers really want to scale the solution to the world. Volition is accompanied by an educational strategy that aims to replicate in the classroom the innovation environment at each course taught in the program, called RAIS. [ABSTRACT FROM AUTHOR]

Simple Summary: Studies have shown that the introduction of multidisciplinary tumour boards can have a positive impact on the survival of cancer patients. By bringing together the different disciplines involved in the treatment of cancer patients, tumour boards provide an interdisciplinary approach to decision-making in the treatment of oncological diseases. Tumour boards have become an integral part of treatment planning. However, their preparation is time-consuming and labour-intensive. The multiplicity of sources and clinical systems makes common communication difficult and consumes a lot of resources. Mixed reality technology could provide the necessary information as an interactive user interface. This is a new digital holographic imaging technology that can generate virtual 3D objects in space from radiological sectional images. A mixed-reality-based software prototype will be developed to analyse whether and to what extent this technology is suitable as a platform for decision making in the head and neck tumour board. The preparation and implementation of interdisciplinary oncological case reviews are time-consuming and complex. The variety of clinical and radiological information must be presented in a clear and comprehensible manner. Only if all relevant patient-specific information is demonstrated in a short time frame can well-founded treatment decisions be made on this basis. Mixed reality (MR) technology as a multimodal interactive user interface could enhance understanding in multidisciplinary collaboration by visualising radiological or clinical data. The aim of the work was to develop an MR-based software prototype for a head and neck tumour board (HNTB) to support clinical decision-making. The article describes the development phases and workflows in the planning and creation of a MR-based software prototype that were required to meet the multidisciplinary characteristics of a HNTB. [ABSTRACT FROM AUTHOR]

A software platform for quantum computing is required to run a complex algorithm on a real quantum device through automatically converting a quantum circuit level algorithm to a control sequence of target device. Moreover, the software platform must be tailored for the target quantum system by exploiting the properties of qubits and gates. In this work, we show how to implement a software platform for a photonic integrated circuit (PIC) platform with path-encoded photon qubits and quantum gates realized by means of interference in a mesh of tuneable Mach-Zehnder interferometers (MZIs). For universal and programmable quantum computing, the software platform consists of three standard modules: decomposer, mapper, and controller. To verify the software we runs example circuit through software and hardware integration platform and confirm each module generates correct output. Also the validation is done by comparing two results for conventionally used manual way and the software supported automatic way. These two points ensure that the implemented software works correctly when applied to the PIC.

Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks, such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. This paper introduces a platform that integrates keyphrase datasets and facilitates the evaluation of keyphrase extraction algorithms. The platform includes BibRank, an automatic keyphrase extraction algorithm that leverages a rich dataset obtained by parsing bibliographic data in BibTeX format. BibRank combines innovative weighting techniques with positional, statistical, and word co-occurrence information to extract keyphrases from documents. The platform proves valuable for researchers and developers seeking to enhance their keyphrase extraction algorithms and advance the field of natural language processing. [ABSTRACT FROM AUTHOR]

Purpose – This paper addresses a gap in research literature in the fields of blockchain technology (BC), supply chain network dynamics (SC) and network effect phenomena (NE). Extant BC and SC literature describes the potential benefits to be reaped through the adoption of BC technology. While BC technology does not yet meet the researched expectations of adoption, performance and efficacy, the authors analyze the three inter-related fields (BC, SC and NE) to bridge this gap in theory. Design/methodology/approach – This paper begins with a research review correlating the technological fundamentals of BC technology into fundamental value propositions for SC logistics contexts. The authors review the gap between these theoretical technological functions and the current ecosystem of BC applications. With an overarching understanding of BC in SC contexts, this paper then explores the phenomena of NE and attempts to synthesize various interrelated aspects of the three fields (BC, SC and NE). Research frameworks from extant literature are used for cross-comparing legacy software/information system solutions with potential and existing BC-based solutions. Case studies are utilized to support this analysis. Findings – Several key considerations and themes are identified to better inform practitioner and researcher decision-making. Novel insights pertain to BC platform architecture and application modularity, integrated governance and decision-making capabilities, and the automation capabilities that arise from a healthy application and smart contract ecosystem. Originality/value – The core contribution is the synthesis of network effect theory with SC phenomena and BC theory and the exploration of how these three fields are inter-related in the maturation of BC technology. Specifically, the authors deepen insights from extant literature by contextualizing findings with relevant interdisciplinary theoretical frameworks.

This paper not only studies the heterogeneous environment for oriented server, charging terminal, airborne terminal, fire terminal and handheld terminal; but also analyzes the construction requirements of army domain command information system software platform. On this basis, the command information system is developed independently, which supports key technologies such as cross-platform software development/operation/integration, multi-scene operation, multi-mode adaptive human-computer interaction and cross-platform service development and integration. In addition, heterogeneous hardware platform integration, adaptive optimization, software runtime and cross-platform middleware integration optimization are also studied. Finally, it provides basic support for heterogeneous software integration and deployment, cross-platform cooperative operation and flexible application in multiple scenarios to land force command information system.

Energy access is a key need for socio-economic growth. Proven to be a key enabler of development and progress, access to electricity has been prioritized by governments using grid extension actions and off-grid solutions, namely microgrids and home systems technologies, fed by renewable sources. However, achieving universal access to energy remains a huge challenge given the lack of resources and the large population currently unserved. The lack of adequate socio-economic data at granular scale and of a good understanding of demand uptake led by economic growth is a barrier for efficient energy planning. Access to conjoint demand and socio-economic data at local level is crucial, yet hard to obtain: often such data are unavailable or very difficult to collect, and current data platforms often lack the ability to conjointly store variegated socio-economic and time series data. For these reasons, in this paper, we present a comprehensive methodology that, based on an extensive literature review, draws guidelines for developing data-sharing platforms in energy access, develops a proposed architecture to support the data collection of conjoint socio-economic and time-series data, and proposes a prototype of the final application. The methodology leverages on a novel extensive literature review to identify the major determinants of demand uptake and the corresponding consuming entities: villages, households, and appliances. The proposed architecture is able to capture numeric, categorical, and time series information for all consuming entities, based on state-of-the-art NoSQL databases. Finally, a prototype implementation with a web-based interface developed with Angular and Spring is proposed and discussed.

For virtual care models to be able to improve the safety and quality of care, it is essential to identify the strengths and weaknesses of virtual care. In this Scoping review, literature published on virtual care was identified using international databases. The results of the included studies were summarized using a predefined taxonomy. In total, 20 studies were included in the present review. Extracting the findings of the articles showed four main topics, including "virtual care delivery models," "Video conference software platforms to provide virtual care," "virtual care delivery challenges," and "virtual care implementation facilitators." Therefore, with the development of emerging digital technologies, unique opportunities to provide virtual care and improve the provision of health services have been created in the health care system worldwide. Multifunctional video conference software platforms using specific models for each scope of care practice should be considered. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Effective exploration technology is urgently needed to carry out the strategic action of mineral exploration breakthrough in China. Aerogeophysics is an important and efficient mineral exploration method, which has played an important role in the world mineral exploration history. Since the 21st century, aero geophysical technology has made great progress in China, such as self-developed high-sensitivity instruments, higher resolution and more types of seamless data collection methods, finer data processing and more accurate interpretation methods, greater detection depth, and wider application fields. In particular, new exploration technologies such as multi-parameter aeromagnetic, airborne time-domain electromagnetic, and airborne gravity, have developed rapidly. Examples of mineral exploration show that aerogeophysics can play an important direct or indirect role in different stages of strategic mineral exploration, especially in the exploration of iron, copper, nickel, uranium, sylvite and other scarce minerals. However, for the new requirements of difficult access and deep earth prospecting, aero geophysical mineral exploration faces some difficulties, such as weak useful geophysical signals, large interference from shallow parts, uncertainty of detection results and difficult construction of geological and geophysical prospecting models. Moreover, the self-developed aeronautical geophysical instruments are not sufficiently practical and used enough. In addition, the development of UAV survey technology is slow, and higher resolution technologies such as aeromagnetic gradient tensor, aero gravity gradient tensor and airborne electromagnetic technology are developing slowly. Advanced and practical high-precision airborne geophysical data acquisition and data processing technologies need to be improved, and the integration of aero geophysical and other methods is not deep enough. The functions of different methods and stages of aero geophysical prospecting were preliminarily summarized, as well as the effectiveness of detecting different mineral species and types, and the idea of aero geophysical technology supporting strategic mineral exploration was proposed. Guided by advanced metallogenic system theory, the effective technologies or technology combinations were studied to solve the problems of mineral exploration deployment and accurate positioning of concealed mineral bodies or geological bodies. Making breakthroughs were focused on in the practicability of domestic instruments and software platforms, developing instruments with higher sensitivity, developing efficient low-altitude high-resolution aero geophysical integration exploration methods, effective information enhancement and weak signal extraction technologies, and intelligent multi-source joint inversion and geophysical geological modeling methods. At the same time, the air-ground-borehole geophysical exploration technology was looked forward to the application prospect of aviation geophysical strategic minerals exploration, and the development trend of aero geophysical exploration technology and the technical methods that need to be developed in the future were discussed. [ABSTRACT FROM AUTHOR]

An organism stems from assemblies of a variety of cells and proteins. This complex system serves as a unit, and it exhibits highly sophisticated functions in response to exogenous stimuli that change over time. The complete sequencing of the entire human genome has allowed researchers to address the enigmas of life and disease at the gene- or molecular-based level. The consequence of such studies is the rapid accumulation of a multitude of data at multiple levels, ranging from molecules to the whole body, that has necessitated the development of entirely new concepts, tools, and methodologies to analyze and integrate these data. This necessity has given birth to systems biology, an advanced theoretical and practical research framework that has totally changed the directions of not only basic life science but also medicine. During the symposium of the 95th Annual Meeting of The Physiological Society of Japan 2018, five researchers reported on their respective studies on systems biology. The topics included reactions of drugs, ion-transport architecture in an epithelial system, multi-omics in renal disease, cardiac electrophysiological systems, and a software platform for computer simulation. In this review article these authors have summarized recent achievements in the field and discuss next-generation studies on health and disease.

This paper analyzes the main causes of accidents during wellbore construction and the existing problems of safety monitoring technology, puts forward safety monitoring robot technology for wellbore construction based on negative pressure adsorption, and analyzes the basic functions of safety monitoring robot in detail. The research goal of wellbore construction safety monitoring robot based on negative pressure adsorption is proposed from the robot body structure, walking mechanism, adsorption mechanism, control, communication, intelligent sensing, identification of dangerous sources, identification of explosive detonators, software platform development, etc. The technical device of wellbore construction safety supervision robot based on negative pressure adsorption is designed, the characteristics of the technology are defined.

This paper not only studies the heterogeneous environment for oriented server, charging terminal, airborne terminal, fire terminal and handheld terminal; but also analyzes the construction requirements of army domain command information system software platform. On this basis, the command information system is developed independently, which supports key technologies such as cross-platform software development/operation/integration, multi-scene operation, multi-mode adaptive human-computer interaction and cross-platform service development and integration. In addition, heterogeneous hardware platform integration, adaptive optimization, software runtime and cross-platform middleware integration optimization are also studied. Finally, it provides basic support for heterogeneous software integration and deployment, cross-platform cooperative operation and flexible application in multiple scenarios to land force command information system. [ABSTRACT FROM AUTHOR]

Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks, such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. This paper introduces a platform that integrates keyphrase datasets and facilitates the evaluation of keyphrase extraction algorithms. The platform includes BibRank, an automatic keyphrase extraction algorithm that leverages a rich dataset obtained by parsing bibliographic data in BibTeX format. BibRank combines innovative weighting techniques with positional, statistical, and word co-occurrence information to extract keyphrases from documents. The platform proves valuable for researchers and developers seeking to enhance their keyphrase extraction algorithms and advance the field of natural language processing.

In this paper, we propose an advanced co-simulation platform that performs the unmanned aerial vehicle (UAV) simulation and the wireless network simulation concurrently. As UAV-based applications become more advanced and complicated and the commands and data transmitted between UAV and ground control station significantly increase, it is vital to safely and robustly transmit the packets carrying commands and data in a wireless network environment. However, the conventional UAV simulation platforms do not take into account the wireless network conditions encountered in the real-world flight so they cannot sufficiently simulate packet transmission. To address this issue, co-simulation platforms have been developed to verify UAV-based applications under a virtual wireless network environment. However, they still cannot effectively support the co-simulation needed to develop the UAV-based applications. In this paper, we have derived a list of improvements to the conventional co-simulation platform based on analysis of the conventional ones. Based on these improvements, we have developed an advanced co-simulation platform consisting of a UAV simulation part, a wireless network simulation part, and an integration part. In this platform, a two-channel approach was introduced to parallelize the synchronization required for performing the UAV simulation and the wireless network simulation simultaneously. The experimental results carried out on three test scenarios demonstrate that the proposed platform accurately performs co-simulation by efficient interoperation of its three parts and by remarkable reduction of the processing time delay, and that it is extendible due to its modularized software architecture.

In the context of software platforms, we examine how cross-side network effects (CNEs) on different platform sides (app-side and user-side) are temporally asymmetric, and how these CNEs are influenced by the platform’s governance policies. Informed by a perspective of value creation and capture, we theorize how the app-side and the user-side react to each other with distinct value creation/capture processes, and how these processes are influenced by the platform’s governance policies on app review and platform updates. We use a time-series analysis to empirically investigate the platform ecosystem of a leading web browser. Our findings suggest that while the growth in platform usage results in long-term growth in both the number and variety of apps, the growth in the number of apps and the variety of apps only leads to short-term growth in platform usage. We also find that long app review time weakens the long-term CNE of the user-side on the app-side, but not the short-term CNE of the app-side on the user-side. Moreover, we find that frequent platform updates weaken the CNEs of both the user-side and the app-side on each other. These findings generate important implications regarding how a software platform may better govern its ecosystem with different participants. [ABSTRACT FROM AUTHOR]

Copyright of Nuclear Safety is the property of Nuclear & Radiation Safety Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Finding the conditions to stabilize a macromolecular target for imaging remains the most critical barrier to determining its structure by cryo-electron microscopy (cryo-EM). While automation has significantly increased the speed of data collection, specimens are still screened manually, a laborious and subjective task that often determines the success of a project. Here, we present SmartScope, the first framework to streamline, standardize, and automate specimen evaluation in cryo-EM. SmartScope employs deep-learning-based object detection to identify and classify features suitable for imaging, allowing it to perform thorough specimen screening in a fully automated manner. A web interface provides remote control over the automated operation of the microscope in real time and access to images and annotation tools. Manual annotations can be used to re-train the feature recognition models, leading to improvements in performance. Our automated tool for systematic evaluation of specimens streamlines structure determination and lowers the barrier of adoption for cryo-EM.

For problems of current load balancing algorithms such as slow processing speed and unreasonable use of existing resources to complete task scheduling in processing data of smart mine system, a cuckoo search based weighted least connection (CS-WLC) algorithm was proposed and applied to smart mine software platform for load balancing. The algorithm synthetically considers backend server indexes including processing speed, RAM, disc IO speed, network throughput and process quantity, and calculates availability of each backend server through assigning weight to each index. Cuckoo search algorithm is used for global optimization of the backend servers according to the calculation results, so as to get an optimal solution collection. The backend servers are assigned weights considering linking number and usage frequency, and weighted least connection (WLC) algorithm is used to select a backend server with lighter load in the optimal solution collection to process real-time data and user access requests. Load balancing test is carried out on software platform of distributed fusion monitoring system. The results show that CS-WLC algorithm has shorter response time-delay and larger linking number than WLC algorithm under the condition of data increase, which verifies CS-WLC algorithm has better load balancing effect.

A representation of complex high-tech digital projects is proposed in the form of a directed graph that combines input, output and intermediate data with software modules into a single bundle. This representation makes it possible to consider a digital project as an informational and algorithmic unit of technical and economic interaction that do not require additional acquisition and development of software or hardware. The project in this form is created and operated on a single multi-party cloud platform for high-performance computing, which is accessible to both scientific and engineering personnel of all participants within their access rights. This approach evolves the open innovation concept for digital projects and is implemented as a cloud-based Internet platform. The latter includes a central application server and a repository that stores both algorithms and data, provides means for user registration and maintenance, communication, as well as accounting for the resource usage in form of algorithms and data in solving application problems. As a confirmation of the fundamental adequacy of the proposed approach, a working prototype of such system is presented together with a list of projects in various domain areas implemented using the prototype. [ABSTRACT FROM AUTHOR]

Nowadays it is important to know the origins of most products, not only for public health reasons, with regard to food products, but also because of the increasing people's awareness of environmental and social aspects, posing new challenges in the quality of products and their environmental impact. Food traceability information must be collected throughout the supply chain, and be registered on a platform external to all operators in that chain. This information must be available, not only to value chain operators and public health authorities, but also to end customers. One of the best ways to provide customers with this traceability information, in the places where they need to make a decision about which products to buy, is to add kiosks at the points of sale for those products. This article describes the design and architecture of a traceability platform for fish and fishery products, within the scope of the ValorMar R&D project, as well as the applications that supply the platform with traceability information, and a kiosk application for points of sale and a mobile app for final consumers, which will allow them to consult the traceability of fish and fishery products' lots.

Copyright of China Sciencepaper is the property of China Sciencepaper and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)