Search results for: causal logic

Authors: D. van der Merwe

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As the environment and associated media in which creativity is expressed transitions towards digital spaces, that same creativity undergoes a transition from individual to social forms of expression. This paper explores how the emerging social construction collectively called ‘The Metaverse’ will fundamentally alter creativity: by examining creativity as a social rather than individual process, as well as the mimetic logic underlying the platforms in which this creativity is expressed, a crisis in identity, commodification and social programming is revealed wherein the artist is more a commodity than their creations, resulting in prosthetic personalities pandering to an economic logic driven by biased algorithms. Consequently the very aura of the art and creative media produced within the digital domain must be re-assessed in terms of its cultural and exhibition value.

Keywords: aura, commodification, creativity, metaverse, mimesis, social programming

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Authors: Alex Vakaloudis, Juan Manuel Escano-Gonzalez

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Setting up a system to broadcast live lectures on the web is a procedure which on the surface does not require any serious technical skills mainly due to the facilities provided by popular learning management systems and their plugins. Nevertheless, producing a system of outstanding quality is a multidisciplinary and by no means a straightforward task. This complicatedness may be responsible for the delivery of an overall poor experience to the learners, and it calls for a formal rating framework that takes into account the diverse aspects of an architecture for synchronous video e-learning systems. We discuss the specifications of such a framework which at its final stage employs fuzzy logic technique to transform from qualitative to quantitative results.

Keywords: synchronous video, fuzzy logic, rating framework, e-learning

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Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

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This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

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Authors: T. Wanyama, B. Far

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Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

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Authors: Saurabh Rawat, Anushree Sah

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K Maps are generally and ideally, thought to be simplest form for obtaining solution of Boolean equations. Cubical Representation of Boolean equations is an alternate pick to incur a solution, otherwise to be meted out with Truth Tables, Boolean Laws, and different traits of Karnaugh Maps. Largest possible k- cubes that exist for a given function are equivalent to its prime implicants. A technique of minimization of Logic functions is tried to be achieved through cubical methods. The main purpose is to make aware and utilise the advantages of cubical techniques in minimization of Logic functions. All this is done with an aim to achieve minimal cost solution.r

Keywords: K-maps, don’t care conditions, Boolean equations, cubes

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Authors: Lisandy Arinta Suryana, Santi Novani, Utomo Sarjono

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Paradox of business strategic is associated with the contradictory practice. It becomes one of the critical way to survive and win in the dynamic competitive landscape – high level of uncertainty and rapid change in the business environment. Those characteristics are similar with the environment of hijab fashion business, especially in Indonesia. This paper aims to describe the success of paradoxical strategic based on historical data of hijab fashion business which have been validated by qualitative approach. This paper discusses two main aspects of paradoxical strategic such as paradox in human resource management, and logistic center management. Then, the detail effects from each practice are described in term of causal loop diagram. Moreover, the practice of paradoxical strategic depends on leadership that can make a brave and dynamic decision by capturing the main problems and opportunities in their business, and also build commitment to achieve a specific goal.

Keywords: paradox of business strategic, paradoxical strategic, causal loop diagram, sustainable business, hijab fashion business, business strategic

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Authors: Rudra P. Pradhan

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This paper examines the Granger causal nexus between financial development and energy consumption in the group of 35 Financial Action Task Force (FATF) Countries over the period 1988-2012. The study uses two financial development indicators such as private sector credit and stock market capitalization and seven energy consumption indicators such as coal, oil, gas, electricity, hydro-electrical, nuclear and biomass. Using panel cointegration tests, the study finds that financial development and energy consumption are cointegrated, indicating the presence of a long-run relationship between the two. Using a panel vector error correction model (VECM), the study detects both bidirectional and unidirectional causality between financial development and energy consumption. The variation of this causality is due to the use of different proxies for both financial development and energy consumption. The policy implication of this study is that economic policies should recognize the differences in the financial development-energy consumption nexus in order to maintain sustainable development in the selected 35 FATF countries.

Keywords: energy consumption, financial development, FATF countries, Panel VECM

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Authors: Amir Ghasem Norouzi, Mahdi Zowghi

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This study propose a framework based on the fuzzy T-Norms, T-conorm, a novel operator, and multi-expert approach to help organizations build awareness of the critical influential factors on the success of knowledge management (KM) implementation, analysis the failure of knowledge management. This study considers the complex uncertainty concept that is in knowledge management implementing capability (KMIC) and it is used by fuzzy logic for this reason. The contribution of our paper is shown with an empirical study in a nonprofit educational organization evaluation.

Keywords: fuzzy logic, knowledge management, multi expert analysis, consensus oriented average operator

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Authors: Yao Jiajia, Wu Guanlin, LIU Fang, Xue Junshuai, Zhang Jincheng, Hao Yue

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Resonant tunneling diodes (RTDs) based on GaN have been extensively studied. However, no results of multiple logic states achieved by RTDs were reported by the methods of epitaxy in the GaN materials. In this paper, the multiple negative-differential resistance regions by combining two discrete double-barrier RTDs in series have been first demonstrated. Plasma-assisted molecular beam epitaxy (PA-MBE) was used to grow structures consisting of two vertical RTDs. The substrate was a GaN-on-sapphire template. Each resonant tunneling structure was composed of a double barrier of AlN and a single well of GaN with undoped 4-nm space layers of GaN on each side. The AlN barriers were 1.5 nm thick, and the GaN well was 2 nm thick. The resonant tunneling structures were separated from each other by 30-nm thick n+ GaN layers. The bottom and top layers of the structures, grown neighboring to the spacer layers that consist of 200-nm-thick n+ GaN. These devices with two tunneling structures exhibited uniform peaks and valleys current and also had two negative differential resistance NDR regions equally spaced in bias voltage. The current-voltage (I-V) characteristics of resonant tunneling structures with diameters of 1 and 2 μm were analyzed in this study. These structures exhibit three stable operating points, which are investigated in detail. This research demonstrates that using molecular beam epitaxy MBE to vertically grow multiple resonant tunneling structures is a promising method for achieving multiple negative differential resistance regions and stable logic states. These findings have significant implications for the development of digital circuits capable of multi-value logic, which can be achieved with a small number of devices.

Keywords: GaN, AlN, RTDs, MBE, logic state

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: driver, fuzzy logic, perception reaction time, premise variable

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Authors: M. Doumi, A. Miloudi, A.G. Aissaoui, K. Tahir, C. Belfedal, S. Tahir

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The studies on the photovoltaic system are extensively increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the photovoltaic system, it is necessary to track the maximum power point of the PV array, for this Maximum Power Point Tracking (MPPT) technique is used. These algorithms are based on the Perturb-Observe, Conductance-Increment and the Fuzzy Logic methods. These techniques vary in many aspects as: simplicity, convergence speed, digital or analogical implementation, sensors required, cost, range of effectiveness, and in other aspects. This paper presents a comparative study of three widely-adopted MPPT algorithms; their performance is evaluated on the energy point of view, by using the simulation tool Simulink®, considering different solar irradiance variations. MPPT using fuzzy logic shows superior performance and more reliable control to the other methods for this application.

Keywords: photovoltaic system, MPPT, perturb and observe (P&O), incremental conductance (INC), Fuzzy Logic (FLC)

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Authors: Francesco Ceresia

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Workplace aggression is broadly recognized as a main work-related risk for healthcare organizations the world over. Scholars underlined that nonfatal workplace aggressions can be also produced by Type II workplace aggression, that occur when the aggressor has a legitimate relationship with the organization and commits an act of hostility while being served or cared for by members of the organization. Several reviews and meta-analysis highlighted the main antecedents and consequences of Type II verbal and physical workplace aggression in the healthcare sector, also focusing on its economic and psychosocial costs. However, some scholars emphasized the need for a systemic and multi-factorial approach to deeply understand and effectively respond to such kind of aggression. The main aim of the study is to propose a qualitative model of Type II workplace aggression in a health care organization in accordance with the system thinking and multi-factorial perspective. A case study research approach, conducted in an Italian non-hospital healthcare organization, is presented. Two main data collection methods have been adopted: individual and group interviews with a sample (N = 24) of physicians, nurses and clericals. A causal loop diagram (CLD) that describes the main causal relationships among the key-variables of the proposed model has been outlined. The main feedback loops and the causal link polarities have been also defined to fully describe the structure underlining the Type II workplace aggression phenomenon. The proposed qualitative model shows how the Type II workplace aggression is related with burnout, work performance, job satisfaction, turnover intentions, work motivation and emotional dissonance. Finally, strategies and policies to reduce the strength of workplace aggression’s drivers are suggested.

Keywords: healthcare, system thinking, work motivation, workplace aggression

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Authors: Swati Arun

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The present paper argues that Balance of Power (BOP) needs to conjugate with certain contingencies like geography. It is evident that sea powers (‘insular’ for better clarity) are not balanced (if at all) in the same way as land powers. Its apparent that artificial insularity that the US has achieved reduces the chances of balancing (constant) and helps it maintain preponderance (variable). But how precise is this approach in assessing the dynamics between China’s rise and reaction of other powers and US. The ‘evolved’ theory can be validated by putting China and US in the equation. Systemic Relation between the nations was explained through the Balance of Power theory much before the systems theory was propounded. The BOP is the crux of functionality of ‘power relation’ dynamics which has played its role in the most astounding ways leading to situations of war and peace. Whimsical; but true that, the BOP has remained a complicated and indefinable concepts since Hans. Morganthau to Kenneth Waltz. A challenge of the BOP, however remains; “ that it has too many meanings”. In the recent times it has become evident that the myriad of expectations generated by BOP has not met the practicality of the current world politics. It is for this reason; the BoP has been replaced by Preponderance Theory (PT) to explain prevailing power situation. PT does provide an empirical reasoning for the success of this theory but fails in a abstract logical reasoning required for making a theory universal. Unipolarity clarifies the current system as one where balance of power has become redundant. It seems to reach beyond the contours of BoP, where a superpower does what it must to remain one. The centrality of this arguments pivots around - an exception, every time BOP fails to operate, preponderance of power emerges. PT does not sit well with the primary logic of a theory because it works on an exception. The evolution of such a pattern and system where BOP fails and preponderance emerges is absent. The puzzle here is- if BOP really has become redundant or it needs polishing. The international power structure changed from multipolar to bipolar to unipolar. BOP was looked at to provide inevitable logic behind such changes and answer the dilemma we see today- why US is unchecked, unbalanced? But why was Britain unchecked in 19th century and why China was unbalanced in 13th century? It is the insularity of the state that makes BOP reproduce “imbalance of power”, going a level up from off-shore balancer. This luxury of a state to maintain imbalance in the region of competition or threat is the causal relation between BOP’s and geography. America has applied imbalancing- meaning disequilibrium (in its favor) to maintain the regional balance so that over time the weaker does not get stronger and pose a competition. It could do that due to the significant parity present between the US and the rest.

Keywords: balance of power, china, preponderance of power, US

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: corporate reputation, fuzzy logic, fuzzy model, stock market investors

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Authors: Mathieu Bere

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Al-Qaeda and Islamic State-affiliated groups such as Ja’amat Nusra al Islam Wal Muslimim (JNIM) and the Islamic State-Greater Sahara Faction, which is now part of the Boko Haram splinter group, Islamic State in West Africa, were responsible, between 2018 and 2020, for at least 1.333 violent incidents against both military and civilian targets, including the assassination and kidnapping for ransom of Western citizens in Mali, Burkina Faso and Niger, the Central Sahel. Protecting civilians from the terrorist violence that is now spreading from the Sahel to the coastal countries of West Africa has been very challenging, mainly because of the many unknowns that surround the perpetrators. To contribute to a better protection of civilians in the region, this paper aims to shed light on the motivations and targeting logic of jihadist perpetrators of terrorist violence against civilians in the central Sahel region. To that end, it draws on relevant secondary data retrieved from datasets, the media, and the existing literature, but also on primary data collected through interviews and surveys in Burkina Faso. An analysis of the data with the support of qualitative and statistical analysis software shows that military and rational strategic motives, more than purely ideological or religious motives, have been the main drivers of terrorist violence that strategically targeted government symbols and representatives as well as local leaders in the central Sahel. Behind this targeting logic, the jihadist grand strategy emerges: wiping out the Western-inspired legal, education and governance system in order to replace it with an Islamic, sharia-based political, legal, and educational system.

Keywords: terrorism, jihadism, Sahel, targeting logic

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Authors: Mikheil Kalmakhelidze

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Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

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Authors: John McDowall, Lucy Lightfoot

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Stigma constitutes a significant barrier to the recovery and social integration of individuals affected by mental illness. Although there is some debate in the literature regarding the definition and utility of stigma as a concept, it is widely accepted that it comprises three components: stereotypical beliefs, prejudicial reactions, and discrimination. Stereotypical beliefs describe the cognitive knowledge-based component of stigma, referring to beliefs (often negative) about members of a group that is based on cultural and societal norms (e.g. ‘People with anxiety are just weak’). Prejudice refers to the affective/evaluative component of stigma and describes the endorsement of negative stereotypes and the resulting negative emotional reactions (e.g. ‘People with anxiety are just weak, and they frustrate me’). Discrimination refers to the behavioural component of stigma, which is arguably the most problematic, as it exerts a direct effect on the stigmatized person and may lead people to behave in a hostile or avoidant way towards them (i.e. refusal to hire them). Research exploring anti-stigma initiatives focus primarily on an educational approach, with the view that accurate information will replace misconceptions and decrease stigma. Many approaches take a biogenetic stance, emphasising brain and biochemical deficits - the idea being that ‘mental illness is an illness like any other.' While this approach tends to effectively reduce blame, it has also demonstrated negative effects such as increasing prognostic pessimism, the desire for social distance and perceptions of stereotypes. In the present study 144 participants were split into three groups and read one of three vignettes presenting causal explanations for Generalised Anxiety Disorder (GAD): One explanation emphasized biogenetic factors as being important in the etiology of GAD, another emphasised psychosocial factors (e.g. aversive life events, poverty, etc.), and a third stressed the adaptive features of the disorder from an evolutionary viewpoint. A variety of measures tapping the various components of stigma were administered following the vignettes. No difference in stigma measures as a function of causal explanation was found. People who had contact with mental illness in the past were significantly less stigmatising across a wide range of measures, but this did not interact with the type of causal explanation.

Keywords: generalised anxiety disorder, discrimination, prejudice, stigma

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

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Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

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Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

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What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

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Authors: Eftychia Kessopoulou, Styliani Xanthopoulou, Ypatia Theodorakioglou, George Tsiotras, Katerina Gotzamani

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Public sector managers frequently herald that implementing best practices as a set of standards, may lead to superior organizational performance. However, recent research questions the objectification of best practices, highlighting: a) the inability of public sector organizations to develop innovative administrative practices, as well as b) the adoption of stereotypical renowned practices inculcated in the public sector by international governance bodies. The process through which organizations construe what a best practice is, still remains a black box that is yet to be investigated, given the trend of continuous changes in public sector performance, as well as the burgeoning interest of sharing popular administrative practices put forward by international bodies. This study aims to describe and understand how organizational best practices are constructed by public sector performance management teams, like benchmarkers, during the benchmarking-mediated performance improvement process and what mechanisms enable this construction. A critical realist action research methodology is employed, starting from a description of various approaches on best practice nature when a benchmarking-mediated performance improvement initiative, such as the Common Assessment Framework, is applied. Firstly, we observed the benchmarker’s management process of best practices in a public organization, so as to map their theories-in-use. As a second step we contextualized best administrative practices by reflecting the different perspectives emerged from the previous stage on the design and implementation of an interview protocol. We used this protocol to conduct 30 semi-structured interviews with “best practice” process owners, in order to examine their experiences and performance needs. Previous research on best practices has shown that needs and intentions of benchmarkers cannot be detached from the causal mechanisms of the various contexts in which they work. Such causal mechanisms can be found in: a) process owner capabilities, b) the structural context of the organization, and c) state regulations. Therefore, we developed an interview protocol theoretically informed in the first part to spot causal mechanisms suggested by previous research studies and supplemented it with questions regarding the provision of best practice support from the government. Findings of this work include: a) a causal account of the nature of best administrative practices in the Greek public sector that shed light on explaining their management, b) a description of the various contexts affecting best practice conceptualization, and c) a description of how their interplay changed the organization’s best practice management.

Keywords: benchmarking, action research, critical realism, best practices, public sector

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L., Schinus terebinthifolius Raddi

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

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Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: dissolved gas-in-oil analysis, fuzzy logic, power transformer, prediction

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Authors: Agord M. Pinto Jr., Yuzo Iano, Leandro T. Manera, Raphael R. N. Souza

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This paper describes an optimization tool-based design strategy for a Current Mode Logic CML divide-by-2 circuit. Representing a building block for output frequency generation in a RFID protocol based-frequency synthesizer, the circuit was designed to minimize the power consumption for driving of multiple loads with unbalancing (at transceiver level). Implemented with XFAB XC08 180 nm technology, the circuit was optimized through MunEDA WiCkeD tool at Cadence Virtuoso Analog Design Environment ADE.

Keywords: divide-by-2 circuit, CMOS technology, PLL phase locked-loop, optimization tool, CML current mode logic, RF transceiver

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Prajamitra Bhuyan

Abstract:

Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

Abstract:

The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

Procedia PDF Downloads 614

Authors: B. Güney, Ç. Teke

Abstract:

In recent years, rapid and correct decision making is crucial for both people and enterprises. However, uncertainty makes decision-making difficult. Fuzzy logic is used for coping with this situation. Thus, fuzzy linear programming models are developed in order to handle uncertainty in objective function and the constraints. In this study, a problem of a factory in food industry is investigated, required data is obtained and the problem is figured out as a fuzzy linear programming model. The model is solved using Zimmerman approach which is one of the approaches for fuzzy linear programming. As a result, the solution gives the amount of production for each product type in order to gain maximum profit.

Keywords: food industry, fuzzy linear programming, fuzzy logic, linear programming

Procedia PDF Downloads 650