Proceedings of the NSSDC Conference on Mass Storage Systems and Technologies for Space and Earth Science Applications

The proceedings of the National Space Science Data Center Conference on Mass Storage Systems and Technologies for Space and Earth Science Applications held July 23 through 25, 1991 at the NASA/Goddard Space Flight Center are presented. The program includes a keynote address, invited technical papers, and selected technical presentations to provide a broad forum for the discussion of a number of important issues in the field of mass storage systems. Topics include magnetic disk and tape technologies, optical disk and tape, software storage and file management systems, and experiences with the use of a large, distributed storage system. The technical presentations describe integrated mass storage systems that are expected to be available commercially. Also included is a series of presentations from Federal Government organizations and research institutions covering their mass storage requirements for the 1990's

Predicting the Price of Cryptocurrency Using Machine Learning Algorithm

It is proposed to conduct a project aimed at forecasting cryptocurrency price values. The concept of cryptocurrencies refers to computerized money that is used for a variety of transactions as well as for long-term investments. The most common cryptocurrency that most of the systems use to conduct their transactions is the Ethereum cryptocurrency. However, it needs to be noted that there are many other well-known crypto currencies other than ethereum as well. We propose to use Machine Learning for this project, which will be trained from the available cryptocurrency price data, to gain intelligence, and then use this knowledge to make accurate predictions. Trading cryptocurrency prices is one of the most popular exchanges right now. It is suggested that both day traders and investors can benefit greatly from using the suggested approach

Oceanus.

v. 39, no. 2 (1996

NSSDC Conference on Mass Storage Systems and Technologies for Space and Earth Science Applications, volume 2

This report contains copies of nearly all of the technical papers and viewgraphs presented at the NSSDC Conference on Mass Storage Systems and Technologies for Space and Earth Science Application. This conference served as a broad forum for the discussion of a number of important issues in the field of mass storage systems. Topics include the following: magnetic disk and tape technologies; optical disk and tape; software storage and file management systems; and experiences with the use of a large, distributed storage system. The technical presentations describe, among other things, integrated mass storage systems that are expected to be available commercially. Also included is a series of presentations from Federal Government organizations and research institutions covering their mass storage requirements for the 1990's

Artificial Intelligence for detection and prevention of mold contamination in tomato processing

openIl presente elaborato si propone di analizzare l'uso dell'intelligenza artificiale attraverso il riconoscimento di immagini per rilevare la presenza di muffa nei pomodori durante il processo di essiccazione. La muffa nei pomodori rappresenta un rischio sia per la salute umana sia per l'industria alimentare, comportando, anche, una serie di problemi che vanno oltre l'aspetto estetico. Essa è causata principalmente da funghi che si diffondono rapidamente sulla superficie dei pomodori. Tale processo compromette così la qualità con la conseguente produzione di tossine che possono influire sulla salute umana. L'obiettivo sperimentale di questo lavoro è il problema dello spreco e della perdita di prodotto nell'industria alimentare. Quando i pomodori sono colpiti da muffe, infatti, diventano inadatti al consumo, con conseguente perdita di cibo. Lo spreco di pomodori a causa delle muffe rappresenta anche la perdita di preziose risorse, utili alla produzione, come terra, acqua, energia e tempo. Il proposito è testare, anche nella fase iniziale, la capacità di un algoritmo di rilevamento degli oggetti per identificare la muffa, e adottare misure preventive. L'analisi sperimentale ha previsto l'addestramento dell'algoritmo con un'ampia serie di foto, tra cui pomodori sani e rovinati di diversi tipi, forme e consistenze. Per etichettare le immagini e creare le epoche di addestramento è stato quindi utilizzato YOLOv7, l'algoritmo di rilevamento degli oggetti scelto, basato su reti neurali. Per valutare le prestazioni sono state utilizzate metriche di valutazione, tra cui “Precision” e “Recall”. L'ipotesi di applicazione dell'intelligenza artificiale in futuro sarà un grande potenziale per migliorare i processi di produzione alimentare, facilitando, così, l'identificazione delle muffe. Il rilevamento rapido delle muffe faciliterebbe la separazione tempestiva dei prodotti contaminati, riducendo così il rischio di diffusione delle tossine e preservando la qualità degli alimenti non contaminati. Questo approccio contribuirebbe a ridurre al minimo gli sprechi alimentari e le inefficienze delle risorse associate allo scarto di grandi quantità di prodotto. Inoltre, l'integrazione della computer vision nel contesto dell'HACCP (Hazard Analysis Critical Control Points) potrebbe migliorare i protocolli di sicurezza alimentare grazie a un rilevamento accurato e tempestivo. Questa tecnologia potrà offrire, dando priorità alla prevenzione, una promettente opportunità per migliorare la qualità, l'efficienza e la sostenibilità dei futuri processi di produzione alimentare.This study investigates the use of computer vision couples with artificial intelligence to detect mold in tomatoes during the drying process. Mold presence in tomatoes poses threats to human health and the food industry as it leads to several issues beyond appearance. It is primarily caused by fungi that spread rapidly over the tomato surface, compromising their quality, and potentially producing toxins that can harm human health. The experimental aim of this work focused on the issue of wastage and loss within the food industry. When tomatoes succumb to mold, they become unsuitable for consumption, resulting in a loss of food and resources. Considering that tomato production requires resources such as land, water, energy, and time, wasting tomatoes due to mold also represents a waste of these valuable resources. The goal was to evaluate the mold detection capabilities of an object detection algorithm, particularly in its early stages, to facilitate preventative measures. This experimental analysis entailed training the algorithm with an extensive array of images, encompassing a variety of healthy and spoiled tomatoes of different shapes, types, textures and drying stages. The chosen object detection algorithm, YOLOv7, is convolutional neural network-based and was utilized for image labeling and training epochs. Evaluation metrics, including precision and recall, were utilized to assess the algorithm's performance. The implementation of artificial intelligence in the future has significant potential for enhancing food production processes by streamlining mold identification. Prompt mold detection would expedite segregation of contaminated products, thus reducing the risk of toxin dissemination and preserving the quality of uncontaminated food. This approach could minimize food waste and resource inefficiencies linked to discarding significant product amounts. Furthermore, integrating computer vision in the HACCP (Hazard Analysis Critical Control Points) context could enhance food safety protocols via accurate and prompt detection. By prioritizing prevention, this technology offers a promising chance to optimize quality, efficiency, and sustainability of future food production processes

Supporting active and healthy aging with advanced robotics integrated in smart environment

The technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is the integration of service robotics for optimising social services and improving quality of life of the elderly population. This chapter aims to underline the barriers of the state of the art, furthermore the authors present their concrete experiences to overcome these barriers gained at the RoboTown Living Lab of Scuola Superiore Sant'Anna within past and current projects. They analyse and discuss the results in order to give recommendations based on their experiences. Furthermore, this work highlights the trend of development from stand-alone solutions to cloud computing architecture, describing the future research directions

Application of blockchain technology as a support to decentralize the information across the supply chain in the organic food industry for the colombian market

Esta investigación se realizó utilizando una metodología analítica-exploratoria estructurada, dado el estado de desarrollo temprano de la tecnología Blockchain. Comenzando con el análisis del estado del arte, la forma de implementación, casos de estudio similares y terminando con una prueba de concepto para validar su aplicabilidad. El resultado es una metodología novedosa para integrar la tecnología Blockchain en la cadena de suministro de la industria de alimentos orgánicos, que reúne las mejores prácticas en mercadeo, ingeniería de procesos y la tecnología en sí, junto con la experiencia de los autores durante su aplicación tomando como base la industria del café orgánico en el Mercado colombiano. El autor ha extraído lo mejor de las prácticas y lo ha hecho simple para cualquier persona interesada en sus uso y aplicaciones. El resultado es una metodología simple y directa que se adapta a cualquier producto, cadena de suministro y configuraciones de sistema requeridas, debido a su versatilidad y adaptabilidad.This research was made using a structured analytical – exploratory methodology, given the early-development-state of the Blockchain technology, beginning with the analisys of the current state, course of implementation, similar study cases and finishing with a prove of concept to validate its applicability. The result, it is a novel methodology to integrate the Blockchain technology in the food industry supply chain, which gathers the best practices in marketing, process engineering and the technology itself, alongside the authors’ experience during its application based on the organic coffee industry in the Colombian market. The Author has extracted the best out of the practices and made it simple for anyone interested in its uses and application. The result is a simple and straightforward methodology that suits any product, supply chain, and required system configurations, due to its versatility and adaptability.Magister en Ingeniería de Proceso

Value chain dynamics in the RFID technology

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2006.Includes bibliographical references (leaf 66).RFID (Radio Frequency Identification) technology has been one of the oldest renewed technologies with a promise of becoming a foundation of "The Internet of Things" in future. MIT's Auto-ID labs and EPCGlobal have been instrumental in advocating standards, making mass scale adoption a reality. The early adopters were found to be in the retail supply chain industry followed by many interesting applications in areas ranging from Fish Tracking to authentication of currency notes. Projects implemented till 2006 were mainly pilot in nature with a desire to understand the technology, given its limitations and challenges and conclude with value propositions or return on investment analysis for corporations. This work has attempted to study such phenomenon in greater detail, bring together the dimensions of technology and business as related to the current state of RFID. We found a very different set of value dynamics applicable to each individual component in the RFID business landscape. Analysis on presented in more detail for manufacturers (Suppliers) of goods as well as Sellers (Retailers) of goods. Further work may be in the form of analyzing the remaining components like logistics players and end customers in a similar fashion.(cont.) Case studies and interview were done to collect data. Secondary sources of information in the forms of published reports and articles are also used and referenced. Management science techniques like Systems Dynamics are used to model some of the value parameters for each component in the retail supply chain. In conclusion, we think although each component of the studied landscape has shown value enhancement and erosion (primarily to cost factors), the overall system shows net gains. As all other technologies, RFID will become cheaper with increased adoption and has a very high probability to be prevalent and ubiquitous in near future.by Milind Tavshikar.S.M

With Foreign Languages to Mutual Understanding, Better Technologies and Ecologically Safer Environment

Матеріали Х Всеукраїнської науково-практичної конференції студентів, аспірантів та викладачів лінгвістичного навчально-методичного центру кафедри іноземних мов, м. Суми, 24 березня 2016 р