Search results for: particle union optimization algorithm

Authors: Paulette Henry

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If Caribbean Universities wish to remain sustainable in the global education market they must meet the new demands of the 21st Centuries learners. This means preparing the teaching and learning environment with the human and material and resources so that the University can blossom out into the entrepreneurial University. The entrepreneurial University prepares the learner to become a global citizen, one who is innovative and a critical thinker and has the competencies to create jobs. Entrepreneurship education provides more equitable access to university education building capacity for the local and global economy. The entrepreneurial thinking, the mindset, must therefore be among academic and support staff as well as students. In developing countries where resources are scarce, Universities are grappling with a myriad of financial and non-financial issues. These include increasing costs, Union demands for increased remuneration for staff and reduced subvention from governments which has become the norm. In addition, there is the political pressure against increasing tuition fees and the perceptions on the moral responsibilities of universities in national development. The question is how do small universities carve out their niche, meet both political and consumer demands for a high quality, low lost education, fulfil their development mandate and still remain not only viable but competitive. Themes which are central to this discourse on the transitions necessary for the entrepreneurial university are leadership, governance and staff well-being. This paper therefore presents a case study of a Caribbean University to show how transformational leadership and the change management framework propels change towards an entrepreneurial institution seeking to have a competitive advantage despite its low resourced context. Important to this discourse are the transformational approaches used by the University to prepare staff to move from their traditional psyche to embracing an entrepreneurial mindset whilst equipping students within the same mode to become work ready and creative global citizens. Using the mixed methods approach, opinions were garnered from both members of the University community as well as external stakeholder groups on their perception of the role of the University in the business arena and as a primary stakeholder in national development. One of the critical concepts emanating from the discourse was the need to change the mindset of the those in university governance as well as how national stakeholders engage the university. This paper shows how multiple non-financial factors can contribute to change. A combination of transformational and servant leadership, strengthened institutional structures and developing new ones, rebuilding institutional trust and pride have been among the strategies employed within the change management framework. The university is no longer limited by borders but through international linkages has transcended into a transnational stakeholder.

Keywords: competitiveness, context, entrepreneurial, leadership

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Sena Su, Burak Ozbek, Yesim M. Sahin, Sevil Yucel, Dilek Kazan, Faik N. Oktar, Nazmi Ekren, Oguzhan Gunduz

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In recent years, protein, lipid or polysaccharide-based polymers have been used in order to develop biodegradable materials and their chemical nature determines the physical properties of the resulting films. Among these polymers, proteins from different sources have been extensively employed because of their relative abundance, film forming ability, and nutritional qualities. In this study, the biodegradable composite nanofiber films based on fish sarcoplasmic protein (FSP) were prepared via electrospinning technique. Biodegradable polycaprolactone (PCL) was blended with the FSP to obtain hybrid FSP/PCL nanofiber mats with desirable physical properties. Mixture solutions of FSP and PCL were produced at different concentrations and their density, viscosity, electrical conductivity and surface tension were measured. Mechanical properties of electrospun nanofibers were evaluated. Morphology of composite nanofibers was observed using scanning electron microscopy (SEM). Moreover, Fourier transform infrared spectrometer (FTIR) studies were used for analysis chemical composition of composite nanofibers. This study revealed that the FSP based nanofibers have the potential to be used for different applications such as biodegradable packaging, drug delivery, and wound dressing, etc.

Keywords: edible film, electrospinning, fish sarcoplasmic protein, nanofiber

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Authors: P.Kiruthika, K. Ramani

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This paper presented the design and advancement of a single-phase 27-level Hybrid Multilevel DC-AC Converter interfacing with Photo Voltaic. In this context, the Multicarrier Pulse Width Modulation method can be implemented in 27-level Hybrid Multilevel Inverter for generating a switching pulse. Perturb & Observer algorithm can be used in the Maximum Power Point Tracking method for the Photo Voltaic system. By implementing Maximum Power Point Tracking with three separate solar panels as an input source to the 27-level Hybrid Multilevel Inverter. This proposed method can be simulated by using MATLAB/simulink. The result shown that the proposed method can achieve silky output wave forms, more flexibility in voltage range, and to reduce Total Harmonic Distortion in medium-voltage drives.

Keywords: Multi Carrier Pulse Width Modulation Technique (MCPWM), Multi Level Inverter (MLI), Maximum Power Point Tracking (MPPT), Perturb and Observer (P&O)

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Authors: Kira Toxopeus, Kamran Siddiqui

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Channel flows are common in a wide range of engineering applications. In some types of channel flows, particularly the ones involving chemical or biological processes, the control of the flow temperature is crucial to maintain the optimal conditions for the chemical reaction or to control the growth of biological species. This often becomes an issue when the flow experiences temperature fluctuations due to external conditions. While active heating and cooling could regulate the channel temperature, it may not be feasible logistically or economically and is also regarded as a non-sustainable option. Thermal energy storage utilizing phase change material (PCM) could provide the required thermal regulation sustainably by storing the excess heat from the channel and releasing it back as required, thus regulating the channel temperature within a range in the proximity of the PCM melting temperature. However, in designing such systems, the configuration of the PCM storage within the channel is critical as it could influence the channel flow dynamics, which would, in turn, affect the heat exchange between the channel fluid and the PCM. The present research is focused on the investigation of the flow dynamical behavior in the channel during heat transfer from the channel flow to the PCM thermal energy storage. Offset vertical columns in a narrow channel were used that contained the PCM. Two different column shapes, square and circular, were considered. Water was used as the channel fluid that entered the channel at a temperature higher than that of the PCM melting temperature. Hence, as the water was passing through the channel, the heat was being transferred from the water to the PCM, causing the PCM to store the heat through a phase transition from solid to liquid. Particle image velocimetry (PIV) was used to measure the two-dimensional velocity field of the channel flow as it flows between the PCM columns. Thermocouples were also attached to the PCM columns to measure the PCM temperature at three different heights. Three different water flow rates (0.5, 0.75 and 1.2 liters/min) were considered. At each flow rate, experiments were conducted at three different inlet water temperatures (28ᵒC, 33ᵒC and 38ᵒC). The results show that the flow rate and the inlet temperature influenced the flow behavior inside the channel.

Keywords: channel flow, phase change material, thermal energy storage, thermal regulation

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Authors: Tomas Makaras

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Sticklebacks (Gasterosteiformes) are increasingly used in ecological and evolutionary research and become well-established role as model species for biologists. However, ecotoxicology studies concerning behavioural effects in sticklebacks regarding stress responses, mainly induced by chemical mixtures, have hardly been addressed. Moreover, although many authors in their studies emphasised the similarity between three-spined and nine-spined stickleback in morphological, neuroanatomical and behavioural adaptations to environmental changes, several comparative studies have revealed considerable differences between these species in and their susceptibility and resistance to variousstressors in laboratory experiments. The hypothesis of this study was that three-spined and nine-spined stickleback species will demonstrate apparent differences in response patterns and sensitivity to metal-based chemicals stimuli. For this purpose, we investigated the swimming behaviour (including mortality rate based on 96-h LC50 values) of two ecologically similar three-spined (Gasterosteusaculeatus) and nine-spined sticklebacks (Pungitiuspungitius) to short-term (up to 24 h) metal mixture (MIX) exposure. We evaluated the relevance and efficacy of behavioural responses of test species in the early toxicity assessment of chemical mixtures. Fish exposed to six (Zn, Pb, Cd, Cu, Ni and Cr) metals in the mixture were either singled out by the Water Framework Directive as priority or as relevant substances in surface water, which was prepared according to the environmental quality standards (EQSs) of these metals set for inland waters in the European Union (EU) (Directive 2013/39/EU). Based on acute toxicity results, G. aculeatus found to be slightly (1.4-fold) more tolerant of MIX impact than those of P. pungitius specimens. The performed behavioural analysis showed the main effect on the interaction between time, species and treatment variables. Although both species exposed to MIX revealed a decreasing tendency in swimming activity, these species’ responsiveness to MIX was somewhat different. Substantial changes in the activity of G. aculeatus were established after 3-h exposure to MIX solutions, which was 1.43-fold lower, while in the case of P. pungitius, 1.96-fold higher than established 96-h LC50 values for each species. This study demonstrated species-specific differences in response sensitivity to metal-based water pollution, indicating behavioural insensitivity of P. pungitiuscompared to G. aculeatus. While many studies highlight the usefulness and suitability of nine-spined sticklebacks for evolutionary and ecological research, attested by their increasing popularity in these fields, great caution must be exercised when using them as model species in ecotoxicological research to probe metal contamination. Meanwhile, G. aculeatus showed to be a promising bioindicator species in the environmental ecotoxicology field.

Keywords: acute toxicity, comparative behaviour, metal mixture, swimming activity

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Piyangkun Kukutapan, Siridech Boonsang

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The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

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Authors: Anujendra, Parag Kumar Guha Thakurta

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The data transmission between mobile hosts and base stations (BSs) in Mobile networks are often vulnerable to failure. Thus, efficient link connectivity, in terms of the services of both base stations and communication channels of the network, is required in wireless mobile networks to achieve highly reliable data transmission. In addition, it is observed that the number of blocked hosts is increased due to insufficient number of channels during heavy load in the network. Under such scenario, the channels are allocated accordingly to offer a reliable communication at any given time. Therefore, a reliability-based channel allocation model with acceptable system performance is proposed as a MOO problem in this paper. Two conflicting parameters known as Resource Reuse factor (RRF) and the number of blocked calls are optimized under reliability constraint in this problem. The solution to such MOO problem is obtained through NSGA-II (Non-dominated Sorting Genetic Algorithm). The effectiveness of the proposed model in this work is shown with a set of experimental results.

Keywords: base station, channel, GA, pareto-optimal, reliability

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Authors: Triano Nurhikmat

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Along with the progress of science and technology, the development of the industrialized world in Indonesia took place very rapidly. This leads to a process of industrialization of society Indonesia faster with the establishment of the company and the workplace are diverse. Development of the industry relates to the activity of the worker. Where in these work activities do not cover the possibility of an impending crash on either the workers or on a construction project. The cause of the occurrence of industrial accidents was the fault of electrical damage, work procedures, and error technique. The method of an association rule is one of the main techniques in data mining and is the most common form used in finding the patterns of data collection. In this research would like to know how relations of the association between the incidence of any industrial accidents. Therefore, by using methods of analysis association rule patterns associated with combination obtained two iterations item set (2 large item set) when every factor of industrial accidents with a West Jakarta so industrial accidents caused by the occurrence of an electrical value damage = 0.2 support and confidence value = 1, and the reverse pattern with value = 0.2 support and confidence = 0.75.

Keywords: association rule, data mining, industrial accidents, rules

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Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

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Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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Authors: Srinivas Vangari

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With the technological advancements around the globe, artificial intelligence (AI) has boosted supply chain management (SCM) by improving efficiency, sensitivity, and promptness. Artificial intelligence-based SCM provides comprehensive perceptions of consumer behavior in dynamic market situations and trends, foreseeing the accurate demand. It reduces overproduction and stockouts while optimizing production planning and streamlining operations. Consequently, the AI-driven SCM produces a customer-centric supply with resilient and robust operations. Intending to delve into the transformative significance of AI in SCM, this study focuses on improving efficiency in SCM with the integration of AI, understanding the production demand, accurate forecasting, and particular production planning. The study employs a mixed-method approach and expert survey insights to explore the challenges and benefits of AI applications in SCM. Further, a case analysis is incorporated to identify the best practices and potential challenges with the critical success features in AI-driven SCM. Key findings of the study indicate the significant advantages of the AI-integrated SCM, including optimized inventory management, improved transportation and logistics management, cost optimization, and advanced decision-making, positioning AI as a pivotal force in the future of supply chain management.

Keywords: artificial intelligence, supply chain management, accurate forecast, accurate planning of production, understanding demand

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Authors: Mojtaba Esmaeilzad Limoudehi, Ebrahim Amiri

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Water scarcity is now one of the leading challenges for human societies. In this regard, recognizing the relationship between soil, water, plant growth, and plant response to stress is very significant. In this paper, considering the importance of drought stress and the role of choosing suitable cultivars in resistance against drought, a split-plot experiment using early, intermediate, and late-maturing cultivars was carried out in Katul filed, Golestan province during two cultivation years of 2015 and 2016. The main factor was irrigation intervals at four levels, including 7 days, 14 days, 21 days, and 28 days. The subfactor was the subplot of six maize cultivars (two early maturing cultivars, two medium maturing cultivars, and two late-maturing cultivars). The results of variance analysis have revealed that irrigation interval and cultivars treatment have significant effects on the number of grain in each corn, number of rows in each corn, number of grain per row, the weight of 1000 grains, grain yield, and biomass yield. Although, the interaction of these two factors on the mentioned attributes was meaningful. The best grain yield was achieved at 7 days irrigation interval and late maturing maize cultivars treatment, which was equal to 12301 kg/ha.

Keywords: corn, growth period, optimization, stress

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

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Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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Authors: Carlos Cuenca, Diego Sarzosa

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Ductile fracture occurs by the mechanism of void nucleation, void growth and coalescence. Potential sites for initiation are second phase particles or non-metallic inclusions. Modelling of ductile damage at the microscopic level is very difficult and complex task for engineers. Therefore, conservative predictions of ductile failure using simple models are necessary during the design and optimization of critical structures like pressure vessels and pipelines. Nowadays, it is well known that the initiation phase is strongly influenced by the stress triaxiality and plastic deformation at the microscopic level. Thus, a simple model used to study the ductile failure under multiaxial stress condition is the Stress Modified Critical Strain (SMCS) approach. Ductile rupture has been study for a structural steel under different stress triaxiality conditions using the SMCS method. Experimental tests are carried out to characterize the relation between stress triaxiality and equivalent plastic strain by notched round bars. After calibration of the plasticity and damage properties, predictions are made for low constraint bending specimens with and without side grooves. Stress/strain fields evolution are compared between the different geometries. Advantages and disadvantages of the SMCS methodology are discussed.

Keywords: damage, SMSC, SEB, steel, failure

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Olusegun Ayodeji Olagunju, Christine Tyreesa Pillay

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Biodiesel from waste sources is regarded as an economical and most viable fuel alternative to depleting fossil fuels. In this work, biodiesel was produced from three different sources of waste cooking oil; from cafeterias, which is vegetable-based using the transesterification method. The free fatty acids (% FFA) of the feedstocks were conducted successfully through the titration method. The results for sources 1, 2, and 3 were 0.86 %, 0.54 % and 0.20 %, respectively. The three variables considered in this process were temperature, reaction time, and catalyst concentration within the following range: 50 oC – 70 oC, 30 min – 90 min, and 0.5 % – 1.5 % catalyst. Produced biodiesel was characterized using ASTM standard methods for biodiesel property testing to determine the fuel properties, including kinematic viscosity, specific gravity, flash point, pour point, cloud point, and acid number. The results obtained indicate that the biodiesel yield from source 3 was greater than the other sources. All produced biodiesel fuel properties are within the standard biodiesel fuel specifications ASTM D6751. The optimum yield of biodiesel was obtained at 98.76%, 96.4%, and 94.53% from source 3, source 2, and source 1, respectively at optimum operating variables of 65 oC temperature, 90 minutes reaction time, and 0.5 wt% potassium hydroxide.

Keywords: waste cooking oil, biodiesel, free fatty acid content, potassium hydroxide catalyst, optimization analysis

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Authors: Tae Hyun Ahn, Gyo Woo Lee, Man Young Kim

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Because of high thermal efficiency and low CO2 emission, diesel engines are being used widely in many industrial fields although it makes many PM and NOx which give both human health and environment a negative effect. NOx regulations for diesel engines, however, are being strengthened and it is impossible to meet the emission standard without NOx reduction devices such as SCR (Selective Catalytic Reduction), LNC (Lean NOx Catalyst), and LNT (Lean NOx Trap). Among the NOx reduction devices, urea-SCR system is known as the most stable and efficient method to solve the problem of NOx emission. But this device has some issues associated with the ammonia slip phenomenon which is occurred by shortage of evaporation and thermolysis time, and that makes it difficult to achieve uniform distribution of the injected urea in front of monolith. Therefore, this study has focused on the mixing enhancement between urea and exhaust gases to enhance the efficiency of the SCR catalyst equipped in catalytic muffler by changing inlet gas temperature and spray conditions to improve the spray uniformity of the urea water solution. Finally, it can be found that various parameters such as inlet gas temperature and injector and injection angles significantly affect the evaporation and mixing of the urea water solution with exhaust gases, and therefore, optimization of these parameters are required.

Keywords: UWS (Urea-Water-Solution), selective catalytic reduction (SCR), evaporation, thermolysis, injection

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Authors: Maryam Azish

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Russia, as an emerging global player in recent years, has projected a special place in the Middle East. Despite all the challenges it has faced over the years, it has always considered its presence in various fields with a strategy that has defined its maneuvering power as a level of competition and even confrontation with the United States. Therefore, its current approach is considered important as an influential actor in the Middle East. After the collapse of the Soviet Union, when the Russians withdrew completely from the Middle East, the American scene remained almost unrivaled by the Americans. With the start of the US-led war in Iraq and Afghanistan and the subsequent developments that led to the US military and political defeat, a new chapter in regional security was created in which ISIL and Taliban terrorism went along with the Arab Spring to destabilize the Middle East. Because of this, the Americans took every opportunity to strengthen their military presence. Iraq, Syria and Afghanistan have always been the three areas where terrorism was shaped, and the countries of the region have each reacted to this evil phenomenon accordingly. The West dealt with this phenomenon on a case-by-case basis in the general circumstances that created the fluid situation in the Arab countries and the region. Russian President Vladimir Putin accused the US of falling asleep in the face of ISIS and terrorism in Syria. In fact, this was an opportunity for the Russians to revive their presence in Syria. This article suggests that utilizing the recognition policy along with the constructivism theory will offer a better knowledge of Russia’s endeavors to endorse its international position. Accordingly, Russia’s distinctiveness and its ambitions for a situation of great power have played a vital role in shaping national interests and, subsequently, in foreign policy, in Putin's era in particular. The focal claim of the paper is that scrutinize Russia’s foreign policy with realistic methods cannot be attained. Consequently, with an aim to fill the prevailing vacuum, this study exploits the politics of acknowledgment in the context of constructivism to examine Russia’s foreign policy in the Middle East. The results of this paper show that the key aim of Russian foreign policy discourse, accompanied by increasing power and wealth, is to recognize and reinstate the position of great power in the universal system. The Syrian crisis has created an opportunity for Russia to unite its position in the developing global and regional order after ages of dynamic and prevalent existence in the Middle East as well as contradicting US unilateralism. In the meantime, the writer thinks that the question of identifying Russia’s position in the global system by the West has played a foremost role in serving its national interests.

Keywords: constructivism, foreign Policy, middle East, Russia, regionalism

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Authors: Tajinder Kaur, Anu Bala

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An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

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Authors: Ramzi Suleiman

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Recently, the author proposed an observationally-based relativity theory termed information relativity theory (IRT). The theory is simple and is based only on basic principles, with no prior axioms and no free parameters. For the case of a body of mass in uniform rectilinear motion relative to an observer, the theory transformations uncovered a matter-dark matter duality, which prescribes that the sum of the densities of the body's baryonic matter and dark matter, as measured by the observer, is equal to the body's matter density at rest. It was shown that the theory transformations were successful in predicting several important phenomena in small particle physics, quantum physics, and cosmology. This paper extends the theory transformations to the cases of rotating disks and spheres. The resulting transformations for a rotating disk are utilized to derive predictions of the radial distributions of matter and dark matter densities in rotationally supported galaxies based solely on their observed rotation curves. It is also shown that for galaxies with flattening curves, good approximations of the radial distributions of matter and dark matter and of the dark matter fraction could be obtained from one measurable scale radius. Test of the model on five galaxies, chosen randomly from the SPARC database, yielded impressive predictions. The rotation curves of all the investigated galaxies emerged as accurate traces of the predicted radial density distributions of their dark matter. This striking result raises an intriguing physical explanation of gravity in galaxies, according to which it is the proximal drag of the stars and gas in the galaxy by its rotating dark matter web. We conclude by alluding briefly to the application of the proposed model to stellar systems and black holes. This study also hints at the potential of the discovered matter-dark matter duality in fixing the standard model of elementary particles in a natural manner without the need for hypothesizing about supersymmetric particles.

Keywords: dark matter, galaxies rotation curves, SPARC, rotating disk

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Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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Authors: Linda Weinberg, Miriam Symon

Abstract:

While few institutions of higher education in Israel offer international programs taught entirely in English, many Israeli students today can study at least one content course taught in English during their degree program. In particular, with the growth of international partnerships and opportunities for student mobility, English medium instruction is a growing phenomenon. There are however no official guidelines in Israel for how to develop and implement content courses in English and no training to help lecturers prepare for teaching their materials in a foreign language. Furthermore, the implications for the students and the nature of the courses themselves have not been sufficiently considered. In addition, the institution must have lecturers who are able to teach these courses effectively in English. An international project funded by the European Union addresses these issues and a set of guidelines which provide guidance for lecturers in adapting their courses for delivery in English have been developed. A train-the-trainer approach is adopted in order to cascade knowledge and experience in English medium instruction from experts to language teachers and on to content teachers thus maximizing the scope of professional development. To accompany training, a model English medium course has been created which serves the dual purpose of highlighting alternatives to the frontal lecture while integrating language learning objectives with content goals. This course can also be used as a standalone content course. The development of the guidelines and of the course utilized backwards, forwards and central design in an iterative process. The goals for combined language and content outcomes were identified first after which a suitable framework for achieving these goals was constructed. The assessment procedures evolved through collaboration between content and language specialists and subsequently were put into action during a piloting phase. Feedback from the piloting teachers and from the students highlight the need for clear channels of communication to encourage frank and honest discussion of expectations versus reality. While much of what goes on in the English medium classroom requires no better teaching skills than are required in any classroom, the understanding of students' abilities in achieving reasonable learning outcomes in a foreign language must be rationalized and accommodated within the course design. Concomitantly, preparatory language classes for students must be able to adapt to prepare students for specific language and cognitive skills and activities that courses conducted in English require. This paper presents findings from the implementation of a purpose-designed English medium instruction course arrived at through an iterative backwards, forwards and central design process utilizing feedback from students and lecturers alike leading to suggested guidelines for English medium instruction in higher education.

Keywords: English medium instruction, higher education, iterative design process, train-the-trainer

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Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

Abstract:

Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

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Authors: V. Makis, L. Jafari

Abstract:

In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart.

Keywords: Bayesian u-chart, economic design, optimal stopping, semi-Markov decision process, statistical process control

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

Abstract:

In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Sergio Paez Moncaleano, Alvaro Mauricio Montenegro

Abstract:

This paper presents a novel statistical methodology for measuring and founding constructs in Latent Regression Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations on Item Response Theory (IRT). In addition, based on the fundamentals of submodel theory and with a convergence of many ideas of IRT, we propose an algorithm not just to solve the dimensionality problem (nowadays an open discussion) but a new research field that promises more fear and realistic qualifications for examiners and a revolution on IRT and educational research. In the end, the methodology is applied to a set of real data set presenting impressive results for the coherence, speed and precision. Acknowledgments: This research was financed by Colciencias through the project: 'Multidimensional Item Response Theory Models for Practical Application in Large Test Designed to Measure Multiple Constructs' and both authors belong to SICS Research Group from Universidad Nacional de Colombia.

Keywords: item response theory, dimensionality, submodel theory, factorial analysis

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Authors: Zeynep Selin Balci, Altug Gunal

Abstract:

Religion has always an effect on the policies of states. In the case of religion having a central role in defining identity, especially when becoming an independent state, the bond between religious authority and state cannot easily be broken. As independence of Greece from the Ottoman Empire was acquired at the same time with the creation of its own church under the name of the Church of Greece by declaring its independence from the Greek Orthodox Patriarchate in Istanbul, the new church became an important part of Greek national identity. As the Church has the ability to influence Greeks, its rituals, public appearances, and practices are used to provide support to the state. Although there sometimes have been controversies between church and state, it has always been a fact that church is an integral part of the state, which is proved by that paying the salaries of priest by state payroll and them being naturally civil servants. European Union membership, on the other hand, has a changing impact on this relationship. This impact started to be more visible in 2000 when then government decided to exclude the religion section from identity cards. Church’s reaction was to gather people around recalling their religious identity and followed by redefining the content of nationality, which aspired nationalist fronts. After 2015 when leftist coalition Syriza and its self-described atheist leader came to power, the situation for nationalists and Church became more tangling in addition to the economic crisis started in 2010 and evolved into the Eurozone crisis by affecting not only Greece but also other members. Although the church did not have direct confrontations with the government, the fact that Tsipras refused to take the oath on Bible created tensions because it was not acceptable for a state whose Constitution starts ‘in the name of the Holy, Consubstantial and Indivisible Trinity’. Moreover, austerity measures to overcome the economic crisis, which affected the everyday life of citizens in terms of both prices and salaries, did not harm the church’s economic situation much. Considering church being the second biggest landowner after state and paying no taxes, the fact that church was exempt from austerity measures showed to the government the necessity to find a way to make church contribute to solution for the crisis. In 2018, when the government agreed with the head of the church on cutting off the priests from government payroll automatically meaning to end priests’ civil servant status, it created tensions both for church and in society. As a result of the elections held in July 2019, Tsipras could not have the chance to apply the decision as he left the office. In light of these, this study aims to analyze the position of the church in the economic crisis and its effects on Tsipras term. In order to sufficiently understand this, it is to look at the historical changing points of Church’s influence in Greek’s eyes.

Keywords: Eurozone crisis, Greece, Orthodox Church, Tsipras

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