THE CULTURE OF SYSTEM CRITICISM THROUGH THE 2016 AMERICAN ELECTIONS

The study will examine the critical approaches in communication science with the culture of system criticism through alternative perspectives such as Baudrillard, who, despite not being included in this category in terms of literature, has dramatically criticized systems. The mass society created by the power of capital holding the mass media, which is the common point of the system critics that have been made up to this time, will be taken to examine the modern world order, which is the work of financial powers who want to keep the formation of public opinion in control, will be one of the main problems of this work and by going through system theory, mass society theory and partly agenda setting theory. In the center of the system formed by the cultural and ideological frameworks produced in the cultural industries, the theme of ‘the benefit belonging not to man but to the governing system’ will be summarized and the current system will be examined by recalling the basic critiques included in the communication literature by critical theory. Presidential Election at the end of 2016, which led to Donald Trump’s leadership in the US with an unexpected surprise and marginal discourses, will be considered as a sample and the background of the current conflict between ‘Trump and Built-in Layout’ will be examined using the content analysis method. Through the example of Trump, which has an unexpected systematic criticism by holding mass media and coming from within the system; the conflicts of interest between the parts of the system and the effects of ‘mass society’ which is also used as a material for these conflicts, will be discussed

Distributed scheduling based on multi-agent systems and optimization methods

The increasing relevance of complex systems in dynamic environments has received special attention during the last decade from the researchers. Such systems need to satisfy products or clients desires, which, after accomplished might change, becoming a very dynamic situation. Currently, decentralized approaches could assist in the automation of dynamic scheduling, based on the distribution of control functions over a swarm network of decision-making entities. Distributed scheduling, in an automatic manner, can be answered by a service coordination architecture of the different schedule components. However, it is necessary to introduce the control layer in the solution, encapsulating an intelligent service that merge agents with optimization methods. Multi-agent systems (MAS) can be combined with several optimization methods to extract the best of the two worlds: the intelligent control, cooperation and autonomy provided by MAS solutions and the optimum offered by optimization methods. The proposal intends to test the intelligent management of the schedule composition quality, in two case studies namely, manufacturing and home health care.FCT - Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2019

Job Shop Planning and Scheduling for Manufacturers with Manual Operations

Job shop scheduling systems are widely employed to optimise the efficiency of machine utilisation in the manufacturing industry, by searching the most cost-effective permutation of job operations based on the cost of each operation on each compatible machine and the relations between job operations. Such systems are paralysed when the cost of operations are not predictable led by the involvement of complex manual operations. This paper proposes a new genetic algorithm-based job shop scheduling system by integrating a fuzzy learning and inference sub-system in an effort to address this limitation. In particular, the fuzzy sub-system adaptively estimates the completion time and thus cost of each manual task under different conditions based on a knowledge base which is initialised by domain experts and then constantly updated based on its built-in learning ability and adaptability. The manufacturer of Point of Sale and Point of Purchase products is taken in this paper as an example case for both theoretical discussion and experimental study. The experimental results demonstrate the promising of the proposed system in improving the efficiency of manual manufacturing operations

Towards industrial internet of things: Crankshaft monitoring, traceability and tracking using RFID

This paper was accepted for publication in the journal Robotics and Computer-Integrated Manufacturing and the definitive published version is available at http://dx.doi.org/10.1016/j.rcim.2016.02.004.The large number of requirements and opportunities for automatic identification in manufacturing domains such as automotive and electronics has accelerated the demand for item-level tracking using radio-frequency identification technology. End-users are interested in implementing automatic identification systems, which are capable of ensuring full component process history, traceability and tracking preventing costly downtime to rectify processing defects and product recalls. The research outlined in this paper investigates the feasibility of implementing an RFID system for the manufacturing and assembly of crankshafts. The proposed solution involves the attachment of bolts with embedded RFID functionality by fitting a reader antenna reader to an overhead gantry that spans the production line and reads and writes production data to the tags. The manufacturing, assembly and service data captured through RFID tags and stored on a local server, could further be integrated with higher-level business applications facilitating seamless integration within the factory

Production Scheduling Requirements to Smart Manufacturing

The production scheduling has attracted a lot of researchers for many years, however most of the approaches are not targeted to deal with real manufacturing environments, and those that are, are very particular for the case study. It is crucial to consider important features related with the factories, such as products and machines characteristics and unexpected disturbances, but also information such as when the parts arrive to the factory and when should be delivered. So, the purpose of this paper is to identify some important characteristics that have been considered independently in a lot of studies and that should be considered together to develop a generic scheduling framework to be used in a real manufacturing environment.authorsversionpublishe

Review: Pharmacological effects of Capparis spinosa L.

Medicinal plants have been known as one of the most important therapeutic agents since ancient times. During the last two decades, much attention has been paid to the health-promoting effects of edible medicinal plants, because of multiple beneficial effects and negligible adverse effects. Capparis spinosa L. is one of the most common medicinal plants, used widely in different parts of the world to treat numerous human diseases. This paper aims to critically review the available scientific literature regarding the health-promoting effects of C. spinosa, its traditional uses, cultivation protocols and phytochemical constituents. Recently, a wide range of evidence has shown that this plant possesses different biological effects, including antioxidant, anticancer and antibacterial effects. Phytochemical analysis shows that C. spinosa has high quantities of bioactive constituents, including polyphenolic compounds, which are responsible for its health-promoting effects, although many of these substances are present in low concentrations and significant changes in their content occur during processing. In addition, there is negligible scientific evidence regarding any adverse effects. Different health promotion activities, as well as tremendous diversity of active constituents, make C. spinosa a good candidate for discovering new drugs. However these findings are still in its infancy and future experimental and clinical studies are needed

Transformative Effects of IoT, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges

Cloud computing plays a critical role in modern society and enables a range of applications from infrastructure to social media. Such system must cope with varying load and evolving usage reflecting societies’ interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Enabling these systems are a cohort of conceptual technologies, synthesised to meet demand of evolving computing applications. In order to understand current and future challenges of such system, there is a need to identify key technologies enabling future applications. In this study, we aim to explore how three emerging paradigms (Blockchain, IoT and Artificial Intelligence) will influence future cloud computing systems. Further, we identify several technologies driving these paradigms and invite international experts to discuss the current status and future directions of cloud computing. Finally, we proposed a conceptual model for cloud futurology to explore the influence of emerging paradigms and technologies on evolution of cloud computing