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Results presentation of two field test allowing efficiency measurement of tires under real conditions of use, Présentation des résultats de deux tests de terrain permettant d'accéder à l'efficience des pneumatiques agricoles en utilisation réelle

Vessel arrival uncertainty in ports has become a very common problem worldwide. Although ship operators have to notify the Estimated Time of Arrival (ETA) at predetermined time intervals, they frequently have to update the latest ETA due to unforeseen circumstances. This causes a series of inconveniences that often impact on the efficiency of terminal operations, especially in the daily planning scenario. Thus, for our study we adopted a machine learning approach in order to provide a qualitative estimate of the vessel delay/advance and to help mitigate the consequences of late/early arrivals in port. Using data on delays/advances at the individual vessel level, a comparative study between two transshipment container terminals is presented and the performance of three algorithmic models is evaluated. Results of the research indicate that when the distribution of the outcome is bimodal the performance of the discrete models is highly relevant for acquiring data characteristics. Therefore, the models are not flexible in representing data when the outcome distribution exhibits unimodal behavior. Moreover, graphical visualisation of the importance-plots made it possible to underline the most significant variables which might explain vessel arrival uncertainty at the two European ports., European Journal of Transport and Infrastructure Research, Vol 15 No 4 (2015)

In a container terminal task assignment optimization may not be sufficient to ensure efficiency. By contrast, a systemic approach to terminal operations planning is required to ensure efficient coordination day by day of the all the operations in-volved. As far as management is concerned, a number of interacting factors need to be taken into account, ranging from prediction of ships’ arrivals to manpower and vehicles optimization strategies for the different work shifts. This paper describes three modules comprising a Decision Support System designed to assist port operations planners: - Ships’ arrivals forecasting module; - Optimal human resources allocation module; - Maintenance process engineering module. First tests indicate that this integrated tool makes flexible and prompt planning of overall operations possible, thereby reducing costs and enhancing their efficiency and thus competitiveness of the container terminal.

The human resources allocation (HRA) is a major issue for container terminals. The workload is organized in shifts covering 24 hours a day and, due to union and work rules, shifts are typically requested to be planned a number of months before their implementation. As a consequence, information on the workforce demand is imprecise when HRA must be planned. This problem must be addressed by a superior exibility, which can be achieved by the two planning levels: the long term stage and the short term one, which encompasses one or more days. In this talk we address the operational planning level which inherits some unchangea- ble decisions from the long term plan and considers the terminal resources involved in real workload. The related literature on HRA does not consider personnel shortfall, which is the most risky situation for terminals, because it may result in vessel delays and in high penalties charged by shipping companies to terminals. The ability to correct manpower shortfalls in a timely fashion is a key factor for the overall productivity of container terminals and their com- petitiveness in the shipping industry. In this talk we present an Integer Linear Programming Model, which addresses this gap by modelling shortages as appropriate decision variables. The objective of our model is to determine the optimal allocation of workers to tasks, shifts and terminal activities, as well as to minimize shortfalls. The model has been used in a rolling horizon fashion, to compare here-and-now decisions deriving from a one-day and a two-day planning horizon. It is exactly solved by a state-of-art solver within reasonable times for the needs of terminal containers. Our experimentation shows that personnel shortfalls can be signi cantly reduced if the model encompasses a longer-than-one-day planning horizon in a rolling horizon fashion. Moreover, whenever shortfalls are observed, they are clustered in low level tasks.

Over the last few decades, competition among maritime container terminals has increased due to large growth rates on major seaborne container routes. Thus terminals have to carefully plan the management of their facilities and services in order to satisfy shipping companies’ demands. Failure to do so will lead customers to re-schedule their routes calling at new promising terminals. As a result, and so as not to lose competitiveness, container terminals are showing a growing interest in advanced decision support systems for their management, in which optimization methods play a crucial role. In this context, the optimal management of human resources is a major issue for terminals, particularly in case of high labor costs. Workload is organized in shifts covering 24 hours a day. Due to union and work rules, shifts are typically required to be planned a number of months in advance. However, a significant feature of terminal activities is the lack of precise information about the time each activity will be performed. This problem should be addressed by greater flexibility, which can be achieved by defining two planning levels: long term, which uses a monthly horizon and short term (operational), which encompasses one or more days [1, 2]. In this work we address the operational planning level, because it inherits some unchangeable decisions from the long term plan, involves the use of terminal resources considering the real work demand and leads to final estimations of benefits deriving from optimization processes. Although there is plenty of literature on workforce management in several areas, little attention has been devoted to the specific context of maritime container terminals [3]. Moreover, none of these formulations have highlighted personnel shortfall, which is the most tricky situation for terminals, because it may result in vessel delays. In these cases, high penalties are charged by shipping companies to terminals. In this work we present an integer linear programming model to address this gap. The objective of the model is to determine the optimal allocation of workers to tasks, shifts and terminal activities, as well as to minimize shortfalls. Different requirements are taken into account for permanent staff and external workers. Moreover, since a longer-than-a-day planning horizon can exploit the visibility of more data, we aim to investigate the effect of a longer planning horizon on this problem. The proposed model is exactly solved by a state-of-art solver within reasonable times for the needs of terminal containers. Preliminary tests show that two-day planning horizons lead to lower shortages than standard daily ones. Moreover, whenever shortfalls are observed, they seem to be clustered in low level tasks, which are easier to tackle by overtime.

This work is motivated by the manpower allocation problem arising at the Cagliari International Terminal Container. Generally speaking, human resources allocation plays a key role in terminals with high labor costs, in order to achieve high levels of productivity and quality services for customers. As a result, terminal containers exhibit a growing interest in advanced decision support systems, in which optimization methods play a crucial role. In this talk we present an optimization model for manpower allocation in transshipment container terminals. The objective is to determine the optimal daily allocation of crane operators and trailer drivers at an operational planning level, taking into account different requirements for permanent staff, external workers and personnel shortfall. The model is exactly solved by a state-of-art solver within reasonable times for the needs of terminal containers.

This work is motivated by the manpower allocation problem arising at the Cagliari International Terminal Container. Generally speaking, human resources allocation plays a key role in terminals with high labor costs, in order to achieve high levels of productivity and quality services for customers. As a result, terminal containers exhibit a growing interest in advanced decision support systems, in which optimization methods play a crucial role. In this talk we present an optimization model for manpower allocation in transshipment container terminals. The objective is to determine the optimal daily allocation of crane operators and trailer drivers at an operational planning level, taking into account different requirements for permanent staff, external workers and personnel shortfall. The model is exactly solved by a state-of-art solver within reasonable times for the needs of terminal containers.

Previsione degli arrivi delle navi ed ottimizzazione delle risorse umane in un terminal hub container

The purpose of the work described in this paper is to construct and implement prediction models for optimizing container handling in particular at Cagliari’s Terminal Container. Prediction models are based on heuristic algorithms such as neural networks and classification and regression trees and evolutionary algorithms such as Genetic Algorithms (GA) and Ant Colony Optimization (ACO). These models form part of a Web Oriented Decision Support System, for real time external data acquisition (GPS information, weather information, etc.), providing operators with the information processed in real time. The most commonly used parameter for assessing terminal performance is productivity, namely the number of containers handled in the unit of time considered. This parameter can be associated with the terminal as a whole, or with the ship, the stevedores, each vehicle used, the single operator and related to different time intervals (year, month, week, day, hour and shift). Usually the hourly average is considered for monitoring operations and identifying shortcomings. The rate at which operations are performed can significantly reduce turn round time and thus minimize the loss of productivity associated with the ship’s time in port. Because of the complexity of analyzing decision-making processes two sublevels are defined, that differ for type of decision and time horizon: - The first level, generally organized around a weekly time horizon (from 10 to 1 days prior to ship’s arrival in port), for scheduling operations and activities in the different areas such as, ship, quay, yard, for making decisions that satisfy the different requirements;- The second level, aimed at specific resource allocation (personnel and equipment) on the basis of the decisions made at the first planning level in order to maximise productivity and minimize costs over a time horizon of roughly 24h. Both levels of planning are characterized by temporal fragmentation and uncertain information. The information is received at undefined times and is continually updated, resulting in uncertain content. The strong dependence of the planning process on information flow, means it is necessarily dynamic and makes it difficult to effectively optimize and integrate decisions over sufficiently broad time horizons. The aim of the study is to construct a model for predicting containership arrivals using heuristic-based evolutionary algorithms. The so-called ―Inspect Inspired Algorithms‖ are proving effective tools for solving industrial optimization issues. In this study the different models proposed are implemented in a ―Decision Support System‖, while data are analysed from a temporal aspect adopting a ―learning from data‖ approach. Indeed the observation of real data (actual arrival time of ships and handling in port) form the knowledge base which relies on learning from the past. All discrepancies observed between prediction models and reality, along with other factors governing that condition prediction errors, create a historical base on which models are automatically recalibrated. This approach has the dual purpose of analysing the causes (shortcomings) of prediction errors while refining models for future prediction; an analysis of the causes and effects of recalibrating the models. The proposed DSS can also be used for simulation purposes. In fact the algorithms will be implemented for studying the effects of external variables taken individually or interacting with one another, thus providing a useful planning tool.

Variable message signs have today become an indispensable tool for managing traffic in urban and suburban areas, such as sending real-time information to motorists in transit along roads where panels are positioned. The study draws on drivers’ response to a series of interviews conducted in the city of Brescia. The interviews showed that a large proportion of drivers does not read the messages, and indeed very often does not even remember having seeing the sign. The marginal usefulness of these facilities can probably be attributed to the fact that the panels are constantly used to display messages devoid of immediate interest (eg, greetings, penalties for traffic violations, general information about the highway code , etc.), with the result that drivers become jaded to their content. The fuzzy logic technique, devised specifically for handling vague and imprecise data, is adopted here to evaluate the vague and unclear memory drivers retain of messages and of the type of display board used. The analysis has highlighted the need to display information using a specific layout for the VMS messages.

Anche in Italia, come da decenni in altri Paesi, i pannelli a messaggio variabile (PMV) stanno trovando una sempre più ampia diffusione, sia in ambito urbano che extraurbano: essi consentono di inviare, in tempo reale, informazioni di qualsiasi genere agli automobilisti in transito lungo le strade ove tali pannelli sono posizionati. I messaggi trasmessi riguardano notizie relative allo stato della viabilità (condizioni di congestione, blocchi stradali per incidenti, lavori in corso) ed informazioni di varia natura (segnalazioni turistiche, news di aggiornamento, pubblicità, ect.). È noto dai principi della Biodinamica dei fattori umani come la percezione del messaggio sia fortemente influenzata dalla struttura, composizione e modalità di trasmissione dello stesso, in base al contenuto del testo, all’uso di specifiche tipologie di caratteri e di colori, di disegni o foto, di specifici vocaboli, ed altro ancora. Attraverso i modelli di Teoria dell’Informazione, è inoltre possibile valutare le modalità di invio e di strutturazione più corretta del messaggio, affinché il contenuto dello stesso possa essere percepito in maniera, rapida e priva di ambiguità e conseguentemente ingenerare la decisione attesa. Ciò al fine di evitare che i conducenti, durante la lettura del messaggio, distolgano lo sguardo dal campo di visuale principale per tempi troppo lunghi, o possano equivocare il contenuto dello stesso, od, ancora, compiere un’azione differente da quella sottesa dal messaggio stesso. La memoria illustra i primi risultati di una ricerca congiunta che le Università di Cagliari e Brescia stanno sviluppando sulle tematiche della segnaletica stradale, analizzati attraverso l’applicazione dei principi della disciplina dei fattori umani. Nell’applicazione qui presentata, è stata valutata la qualità della percezione di messaggi, inviati tramite PMV, da parte di un insieme di automobilisti intervistati subito dopo il transito al di sotto dei pannelli. I dati sono stati analizzati mediante il supporto di tecniche multivariate, che hanno consentito l’individuazione delle principali variabili che influenzano la percezione da parte dei conducenti. I risultati hanno posto in evidenza come tali messaggi vengano, in generale, poco letti dai conducenti, che spesso li percepiscono come sfondo indistinto del paesaggio intorno alla via di marcia. Tale scarsa utilità degli impianti sembrerebbe derivi principalmente dal fatto che i PMV vengono costantemente mantenuti attivi per inviare messaggi privi di interesse immediato (quali, ad esempio, messaggi augurali, sanzioni per infrazioni, avvisi generali sul Codice della Strada), creando una sorta di disinteresse alla lettura per assuefazione da informazioni inutili. Nel proseguo della ricerca ci si è posti l’obiettivo di pervenire alla definizione delle modalità più opportune di gestione dei PMV ed alla indicazione delle regole più efficaci di composizione testuale del messaggio e di trasmissione alternativa dello stesso (mediante l’uso di caratteri, colori ed immagini) per renderlo più efficace e sicuro.

Anche in Italia, come da decenni avviene in altri Paesi, i pannelli a messaggio variabile (PMV) stanno trovando una sempre più ampia diffusione, sia in ambito urbano che extraurbano: essi consentono di inviare, in tempo reale, informazioni di qualsiasi genere agli automobilisti in transito lungo le strade ove tali pannelli sono posizionati. I messaggi trasmessi riguardano notizie relative allo stato della viabilità (condizioni di congestione, blocchi stradali per incidenti, lavori in corso) ed informazioni di varia natura (segnalazioni turistiche, news di aggiornamento, pubblicità, ect.). La memoria illustra i risultati di una ricerca congiunta che le Università di Cagliari e Brescia hanno sviluppato sulle tematiche della segnaletica stradale, analizzati attraverso l’applicazione dei principi della disciplina dei fattori umani. Nell’applicazione qui presentata, è stata valutata la qualità della percezione di messaggi, inviati tramite PMV, da parte di un insieme di automobilisti intervistati subito dopo il transito al di sotto dei pannelli. I dati sono stati analizzati con tecniche multivariate, che hanno consentito l’individuazione delle principali variabili che influenzano la percezione da parte dei conducenti. In modo particolare ci si è posti l’obiettivo di pervenire alla definizione delle modalità di gestione dei PMV mediante l’individuazione delle regole più efficaci di composizione testuale del messaggio. I risultati hanno posto in evidenza come tali messaggi vengano, in generale, poco letti e compresi dai conducenti, anche perché non sempre la struttura e la composizione del testo proiettato nel pannello risponde ai criteri base della disciplina dei fattori umani. A ciò si somma il fatto che quasi sempre i PMV vengono mantenuti costantemente attivi per inviare messaggi privi di interesse immediato (quali, ad esempio, messaggi augurali, sanzioni per infrazioni, avvisi generali sul Codice della Strada), creando una sorta di disinteresse alla lettura per assuefazione da informazioni inutili. Dall’analisi è tuttavia risultato come un testo scarno e con poche indicazioni si riveli maggiormente efficace e comprensibile per l’utenza. Indicazioni pleonastiche nel messaggio, benché supportate da copiosa bibliografia, hanno complicato e reso maggiormente difficoltosa la lettura e la successiva memorizzazione del messaggio.

UN AGGIORNAMENTO DELLA DISTRIBUZIONE DEI CROSTACEI ANOSTRACA DI ACQUA DOLCE VIENE PROPOSTO PER IL TERRITORIO PUGLIESE

A diploid parthenogenetic strain of Artemia has been found in the Torre Colimena hypersaline lake. The species coexists with another anostracan of the genus Branchinella. The present described strain is compared, with a multidisciplinary approach, with other parthenogenetic Artemia strains from all the Mediterranean basin.

International audience; The ENTAM as the European Network of Testing stations of Agricultural Machines and equipment has settled up a new ENTAM Technical Working Group in order to draft a common methodology to test the agricultural tyre energy efficiency, in close cooperation with one of the biggest tyre manufacturer. The aim was to find a compromise between easiness and representativeness of the measurements, with reproducible records carried out on real agricultural fields, in standardized soil conditions. It is described a proposal for a dimensionless tyre performance index and a way to standardize the test methodology and the test devices.

A case of pleomorphic rhabdomyosarcoma of the larynx is presented, which is extremely rare in a laryngeal site. The symptomatology and macroscopic aspect of the neoplasm can simulate the presence of other neoplastic variants of the larynx, and, for this reason, histological examination must be associated with immunohistochemistry for correct diagnosis and treatment.

The still debated question of whether the expression of mental retardation in heterozygous carriers of the Martin-Bell syndrome is influenced by X inactivation has been investigated in a group of phase-known double heterozygotes for the FRA-X mutant and the G6PD Mediterranean variant. In these individuals, the number of somatic cells (fibroblasts or red cells) with an active FRA-X chromosome could be assessed through the G6PD phenotype at the single-cell level. The data reported indicate a significant inverse correlation between the IQ level (as measured by the Wechsler-Bellevue test) and the percentage of fibroblast cells with an FRA-X active chromosome. In contrast, no significant correlation was found when the IQ level and red cell data were compared, thus suggesting the occurrence of somatic selection against hematopoietic stem cells with an active FRA-X chromosome.

This paper presents an approach to model and simulate industrial plant accidents as well as the related emergency management; interoperable simulation is proposed as approach for applying High Level Architecture in this context. The authors are focusing their attention on the disaster simulation and its interaction with the emergency management. Modern simulation, by using technology enables such as mobile solution, enhance its support to first responders, the dynamic reaction to crisis evolution as well as the improvement in training and management of safe routing and handling of injured people. This paper introduces these elements as part of new research track devoted to get benefits from interoperable simulation in federating multidisciplinary models for industrial plant emergency management.