Data Management and Big Data Analytics

The internet is creating 2.5 quintillion bytes of data, and according to the statistics, the percentage of data that has been generated from last two years is 90%. This data comes from many industries like climate information, social media sites, digital images and videos, and purchase transactions. This data is big data. Big data is the data that exceeds storage and processing capacity of conventional database systems. Data in today's world (big data) is usually unstructured and qualitative in nature and can be used for various applications like sentiment analysis, increasing business, etc. About 80% of data captured today is unstructured. All this data is also big data.

Artificial Intelligence in Digital Mental Health

The prevention of diseases considered a scourge of our society, as for example mental illness, particularly anxiety disorders and depressive states, is a primary and urgent goal today and a priority axis of the EU. Mental illness includes many clinical conditions associated with several changes that include limitations related with social interaction or several tasks such as sleeping through the night, doing homework, making friends, thinking capacity and reality understanding, deficits in communication skills, and difficulties in developing appropriate emotional and behavioural response. Artificial intelligence has gained a prominent role in the management and delivery of healthcare. There is a growth in mobile devices applied to health with high mobility, connectivity, and processing capacity. This chapter provides an analysis of the actual trends regarding the main problems that can be dealt with using AI in mental healthcare and the corresponding main techniques used to deal with these problems. Additionally, some case studies for using AI for mental health care are described.

DEVELOPMENT OF A METHOD FOR ESTIMATING THE CAPACITY OF GARAGE DEFROSTING OF THE TRANSPORTATION SYSTEM OF AN INDUSTRIAL ENTERPRISE

Purpose. The aim of the work is to develop a method for estimating the capacity of garages for defrosting the transport system of an industrial enterprise. Research methods. In the course of the research methods of analysis and logic were used to evaluate scientific and technical publications related to the development and calculation of the capacity of technical devices of cargo stations and unloading complexes. Results. The method of estimating the capacity of defrosting garages of the transport system of an industrial enterprise is developed in the work. The developed method is based on the comparison of the calculated and required capacity of garages for defrosting of large unloading complexes of industrial enterprises. The need to introduce the reserve capacity of defrosting garages in connection with the influence of dynamic factors into the model is substantiated during the research. The scientific novelty lies in the development of a method for estimating the capacity of garages for defrosting the transport system of an industrial enterprise. Practical value. The developed method of capacity assessment allows to optimally, comprehensively synchronize the operation of defrost garages and unloading complex with processing capacity and thus increase the efficiency of management of the transport system of an industrial enterprise.

Cognitive and Neurolinguistic Aspects of Interpreting

Over the past decade, a large and growing body of literature has explored the cognitive and neural foundations of interpreting processes. The article explores the relevance of cognitive and neurolinguistic approaches to the process of both simultaneous and consecutive interpreting. The main objective is to reveal the interpreter’s status, his/her mental and linguistic operations as cognitive units in the approaches under review. Firstly, we discuss how both interpreting modes have been understood and defined by various researchers. Secondly, we present the overview of diverse research works on cognitive and neurolinguistic scientific approaches to interpretation, trying to understand and explain the operating of interpreters’ minds. Finally, we focus on the issues of bilingualism and its impact on language comprehension and its production. It has been revealed that interpreting contributes significantly to improving cognitive and neural functions of the brain. Interpreters have always been a key figure in facilitating and bridging communication across cultures and languages. They can input, retain, retrieve, and output data but are limited in processing capacity at any given time. Quite recently, scholars in both interpreting and neurolinguistics have attempted to provide insight into the organization of bilingual speakers’ minds. In interpreting and translation tasks, it has been complemented by research works into language control in a bilingual language mode, with both language systems being simultaneously activated. Taken together, the cognitive and neurolinguistic studies reviewed in the paper support strong recommendations to regard an interpreter as a conceptual mediator relying on both his/her decision-making and probability thinking mechanisms.

Smart SRUs Pre-Investment Utilizing Oxygen Enrichment Technology

This paper presents an unparalleled engineering assessment conducted to evaluate the feasibility of pre-investing in O2 enrichment technology, with the purpose of increasing the processing capacities of conventional air-based sulfur recovery units (SRUs). Ultimately, the goal is to minimize the overall number of required SRUs for a greenfield gas plant and, consequently, capture a significant cost-avoidance opportunity. The technology review revealed that a high-level O2 enrichment can double the processing capacity of air-based SRU, depending on the H2S content in acid gas. As H2S mole fraction in feed increases, the debottlenecking capability increases. For the project under assessment, the processing capacity of air-based SRUs showed a maximum increase of 80%. On the contrary, operating with high O2 levels, will elevate SRU reaction furnace temperature, and mandates installing high-intensity burners, along with special control and ESD functions, to manage potential risk and ensure safe operation. Additionally, the liquid handling section of SRUs (condensers, collection vessels, degassing vessels, sulfur storage tanks) should be enlarged to accommodate more sulfur production. Typically, the enriched oxygen can be supplied from air separation units (ASUs), which entails significant capital cost. Apart from these special design considerations, there are several advantages for adopting this technology. Oxygen enrichment removes significant nitrogen volumes, which reduces loads on Claus, tail gas treatment, and thermal oxidizer units. Hence, lower capital cost for new plants is acquired due to equipment size reduction. In addition, higher HP steam production and less fuel gas consumption are achieved. Conventionally, O2 enrichment technology is employed in the initial design stage or used to retrofit operating SRUs facilities. However, it is unique to consider O2 enrichment-design requirements as part of new air-based SRUs design for phased program development. The objective is to enable smooth transition to fully O2 enrichment operated SRUs at a later phase of the project without the need for any design modification. This exceptional pre-investment strategy has resulted into reducing the required number of SRUs at phase II from eight to five units; and accordingly, a significant cost avoidance was captured.

Microporous Polymer Adsorptive Membranes with Unprecedented Processing Capacity for Molecular Separation

Trade-off between permeability and nanometer-level selectivity is an inherent shortcoming of membrane-based separation of molecules, while most highly porous materials with high adsorption capacity lack solution processability and stability for achieving adsorption-based molecule separation. We hereby report a hydrophilic amidoxime modified polymer of intrinsic microporosity (AOPIM-1) as a membrane adsorption material to selectively adsorb and separate small organic molecules from water with ultrahigh processing capacity. The membrane adsorption capacity for Rhodamine B reaches 26.114 g m−2, 10~1000 times higher than previously reported adsorptive membranes. Meanwhile, the membrane achieves >99.9% removal of various nano-sized organic molecules with water flux 2 orders of magnitude higher than typical pressure-driven membranes of similar rejections. This work confirms the feasibility of microporous polymers for membrane adsorption with unprecedented capacity, and provides the possibility of adsorptive membranes for molecular separation.

Maximize Asset Utilization by Effectively Identifying and Removing Bottlenecks

ADNOC Gas Processing Ruwais NGL Fractionation plant receives and fractionates the NGL produced in upstream gas processing plants. After operation of newly designed upstream NGL plants, composition of NGL feedstock has become richer in Ethane and Propane. Consequently, nameplate capacity were reduced by~25%. In view of future increased NGL production, nameplate capacity of fractionation trains needs to be re-instated. Alternatively, a new fractionation train needs to be installed to accommodate additional NGL. To explore the opportunity for maximum utilization for existing trains, in line with the ADNOC strategy of enhancing profitability and asset utilization, a technical study was conducted to increase the processing capacity back to original nameplate capacity with lighter NGL composition. This was to identify the potential bottlenecks in the facility and suggest debottlenecking options with a reasonable investment. The Technical study covers the following activities: Simulation: Rigorous process simulation including the licensor units of DEO/Propane amine units Adequacy checks and identification of bottlenecks: Line sizing adequacy check and detailed hydraulic evaluation of the major piping Equipment adequacy check Relief & blowdown and flare system adequacy check Proprietary equipment/design evaluation of licensed units Adequacy check for In-line instruments like control valves, flow elements/transmitters, thermowells Rotating equipment adequacy checks performed with the concurrence from OEMs. Licensor Endorsement: Obtained the endorsement of AGRU licensor (Shell) for the increased flow rate with revised contaminant levels with recommendations of removing identified bottlenecks. Bottlenecks mitigation: Various options for bottleneck mitigation was studied and most optimum solution was selected to remove the identified bottleneck. The study has concluded that current capacity limitation was mainly due to bottlenecks in Ethane loop. Therefore, by mitigating the identified bottlenecks (i.e. replacing lines with bigger size, providing high performance trays, high performance internals, replacing few equipment's with new one etc.), the original nameplate capacity can be re-instated. The study concludes that increased NGL forecasted flow with lighter composition could be processed in existing Ruwais fractionation trains by doing minor modifications (as compared to new train). A capacity increase of ~25% was achieved with minimum investment and requirement of new fractionation train could avoided. If extensive adequacy studies are carried out to identify the bottlenecks, the capacity enhancement in existing facilities can be achieved with minimum investment and major cost for new plants/trains can be avoided.

Delay and Energy Consumption Optimization Oriented Multi-service Cloud Edge Collaborative Computing Mechanism in IoT

The rapid development of the Internet of Things has put forward higher requirements for the processing capacity of the network. The adoption of cloud edge collaboration technology can make full use of computing resources and improve the processing capacity of the network. However, in the cloud edge collaboration technology, how to design a collaborative assignment strategy among different devices to minimize the system cost is still a challenging work. In this paper, a task collaborative assignment algorithm based on genetic algorithm and simulated annealing algorithm is proposed. Firstly, the task collaborative assignment framework of cloud edge collaboration is constructed. Secondly, the problem of task assignment strategy was transformed into a function optimization problem with the objective of minimizing the time delay and energy consumption cost. To solve this problem, a task assignment algorithm combining the improved genetic algorithm and simulated annealing algorithm was proposed, and the optimal task assignment strategy was obtained. Finally, the simulation results show that compared with the traditional cloud computing, the proposed method can improve the system efficiency by more than 25%.

Uplink and Downlink Variation in Drone Technology for Cloud, Edge, Fog and Smart Dust Integrated IoT Architecture: Demonstrated Over WSNs

IoT concepts are heavily applicable in drone communication integrated with different network architecture for optimization. Distributing the burden allows more IoT devices to execute calculations, rather than everything being done on the cloud. There are numerous IoT designs that have emerged as a result of this. By relocating calculations away from the cloud, these designs make use of the enhanced processing capacity of the devices. Based on our needs, we’ve limited it down to four architectures, each of which we have discussed for optimized flow useful in drone technology. We have also applied the one live dataset for the test drone using raspberry pi processor system powered with for end-to-end drone communication establishment. The analysis of downlink and uplink were studied for time analysis for IoT architecture using drone cell characteristics. New technology makes it possible to implement drone cell (DC) connectivity, which is highly flexible and cost-effective for the gathering of Internet-of-things (IoT) data when terrestrial networks are not yet accessible. DC’s flight path has a substantial impact on data collecting systems.

Stock-recruitment models, principles of management and rules for regulating the fishery on the main Chukotka stocks of sockeye and chum salmon

Fishery pressure on populations of pacific salmons has increased in the Rusian Far East in the last decade because of growing fishing and processing capacity, so measures for the fishery regulation are necessary, as the regime of pass days in rivers and marine coastal areas. Chukotka is now almost the only region where such restrictions are still absent. However, if the interest of fishery industry to the stocks of pacific salmon in Chukotka will grow, a successful scientifically based strategy of fishery should be developed to maintain exploitation of the stocks without exceeding the limits of excessive use. Year-to-year time series on spawning stock and recruitment of chum salmon in the Anadyr area and sockeye salmon in the Meynypilgyn area were analysed for development of recruitment models and establishment of general principles for adaptive fishery management. Nonlinear adaptive fishery management based on principles of buffer managing is proposed and tested under various regimes of landing using the stock simulation models accounting deviations from the standard stock-recruitment model. There is concluded that the level of exploitation is much lower than optimal for the Anadyr chum salmon, whereas escapement for spawning of the Meynypilgyn sockeye salmon should be increased in cases of low spawning stock of this species.