Search results for: virtual machine migration

Authors: Robin Singh, Mayank Nautiyal, Priyank Jain, Vatasta Koul, Vaibhav Sharma

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The curiosity to investigate the space and its mysteries was dependably the main impetus of human interest, as the particle of livings exists from the "debut de l'Univers" (beginning of the Universe) typified with its few other living things. The sharp drive to uncover the secrets of stars and their unusual deportment was dependably an ignitor of stars investigation. As humankind lives in civilizations and states, stars likewise live in provinces named ‘clusters’. Clusters are separates into 2 composes i.e. open clusters and globular clusters. An open cluster is a gathering of thousand stars that were moulded from a comparable goliath sub-nuclear cloud and for the most part; contain Propulsion I (extremely metal-rich) and Propulsion II (mild metal-rich), where globular clusters are around gathering of more than thirty thousand stars that circles a galactic focus and basically contain Propulsion III (to a great degree metal-poor) stars. Futurology of this paper lies in the spectroscopic investigation of globular clusters like M92 and NGC419 and open clusters like M34 and IC2391 in different color bands by using software like VIREO virtual observatory, Aladin, CMUNIWIN, and MS-Excel. Assessing the outcome Hertzsprung-Russel (HR) diagram with exemplary cosmological models like Einstein model, De Sitter and Planck survey demonstrate for a superior age estimation of respective clusters. Colour-Magnitude Diagram of these clusters was obtained by photometric analysis in g and r bands which further transformed into BV bands which will unravel the idea of stars exhibit in the individual clusters.

Keywords: color magnitude diagram, globular clusters, open clusters, Einstein model

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Authors: Sukwoong Kang

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Background: The application of light-emitting diode (LED)-dependent photobiomodulation (PBM) in promoting post-tendon injury healing has been recently reported. Despite the establishment of a theoretical basis for ligament restoration through PBM, the lack of any empirical evidence deems this therapeutic strategy contentious. Therefore, the aim of this study was to investigate the potency of LED-based PBM in facilitating tendon healing in a murine model. Methods: Migration kinetics were analyzed at two specific wavelengths: 630 and 880 nm. The Achilles tendon in the hind limbs of Balb/c mice was severed via Achilles tendon transection. Subsequently, the mice were randomized into LED non-irradiation and LED irradiation groups. Mice with intact tendons were employed as healthy controls. The wounds were LED-irradiated for 20 min daily for two days. Histological properties, tendon healing mediators, and inflammatory mediators were screened on day 14. Results: The roundness of the nuclei and fiber structure, indicating the degree of infiltrated inflammatory cells and severity of fiber fragmentation, respectively, were considerably lower in the LED irradiation group than in the LED non-irradiation group. Immunohistochemical analysis depicted an increase in tenocytes (SCX+ cells) and a recovery of wounds with reduced fibrosis (lower collagen 3 and TGF-β1) in the LED irradiation group during healing; conversely, the LED non-irradiation group exhibited tissue fibrosis. The ratio of M2 macrophages to total macrophages was higher in the LED irradiation group than in the injured group. Conclusion: LED-based PBM in the Achilles tendon rupture murine model effectuated a rapid restoration of histological and immunochemical outcomes. The aforementioned findings suggest that LED-based PBM presents remarkable potential as an adjunct therapeutic for tendon healing and warrants further research to standardize various parameters to advance and establish it as a reliable treatment regime.

Keywords: photobiomodulation, light-emitting diode, tendon, regeneration

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Authors: Á. L. Bendes

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By the end of the second decade of the 21st century, artificial intelligence (AI) has become an unavoidable part of everyday life and has necessarily aroused the interest of researchers in almost every field of science. This is no different in the case of jurisprudence, whose main task is not only to create its own theoretical paradigm related to AI. Perhaps the biggest impact on digital crime is artificial intelligence. In addition, the need to create legal frameworks suitable for the future application of the law has a similar importance. The prognosis according to which AI can reshape the practical application of law and, ultimately, the entire legal life is also of considerable importance. In the past, criminal law was basically created to sanction the criminal acts of a person, so the application of its concepts with original content to AI-related violations is not expected to be sufficient in the future. Taking this into account, it is necessary to rethink the basic elements of criminal law, such as the act and factuality, but also, in connection with criminality barriers and criminal sanctions, several new aspects have appeared that challenge both the criminal law researcher and the legislator. It is recommended to continuously monitor technological changes in the field of criminal law as well since it will be timely to re-create both the legal and scientific frameworks to correctly assess the events related to them, which may require a criminal law response. Artificial intelligence has completely reformed the world of digital crime. New crimes have appeared, which the legal systems of many countries do not or do not adequately regulate. It is considered important to investigate and sanction these digital crimes. The primary goal is prevention, for which we need a comprehensive picture of the intertwining of artificial intelligence and digital crimes. The goal is to explore these problems, present them, and create comprehensive proposals that support legal certainty.

Keywords: artificial intelligence, chat forums, defamation, international criminal cooperation, social networking, virtual sites

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Authors: Jeongmin Kim, Eunju Lee, Kwang Ryel Ryu

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This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis.

Keywords: predictive control, energy management, machine learning, optimization

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Authors: Susan Amirsalari, Azime Khosrinejad, Elham Rahimian

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Objective: Epilepsy is a common brain disorder characterized by a persistent tendency to develop in neurological, cognitive, and psychological contents. Magnetic Resonance Imaging (MRI) is a neuroimaging test facilitating the detection of structural epileptogenic lesions. This study aimed to compare the MRI findings between patients with intractable and drug-responsive epilepsy. Material & methods: This case-control study was conducted from 2007 to 2019. The research population encompassed all 1-16- year-old patients with intractable epilepsy referred to the Shafa Neuroscience Center (n=72) (a case group) and drug-responsive patients referred to the pediatric neurology clinic of Baqiyatallah Hospital (a control group). Results: There were 72 (23.5%) patients in the intractable epilepsy group and 200 (76.5%) patients in the drug-responsive group. The participants' mean age was 6.70 ±4.13 years, and there were 126 males and 106 females in this study Normal brain MRI was noticed in 21 (29.16%) patients in the case group and 184 (92.46%) patients in the control group. Neuronal migration disorder (NMD)was also exhibited in 7 (9.72%) patients in the case group and no patient in the control group. There were hippocampal abnormalities and focal lesions (mass, dysplasia, etc.) in 10 (13.88%) patients in the case group and only 1 (0.05%) patient in the control group. Gliosis and porencephalic cysts were presented in 3 (4.16%) patients in the case group and no patient in the control group. Cerebral and cerebellar atrophy was revealed in 8 (11.11%) patients in the case group and 4 (2.01%) patients in the control group. Corpus callosum agenesis, hydrocephalus, brain malacia, and developmental cyst were more frequent in the case group; however, the difference between the groups was not significant. Conclusion: The MRI findings such as hippocampal abnormalities, focal lesions (mass, dysplasia), NMD, porencephalic cysts, gliosis, and atrophy are significantly more frequent in children with intractable epilepsy than in those with drug-responsive epilepsy.

Keywords: magnetic resonance imaging, intractable epilepsy, drug responsive epilepsy, neuronal migrational disorder

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Karun K. Karki

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Globalization has intensified the transnational movement of people, mainly from the Global South to the Global North. In this context of transnationalism, migration is framed within the national interests required for economic prosperity. More specifically, the competition for the ‘best and the brightest of highly educated immigrants from around the world can be perceived as evidence that countries in the North are competing in the knowledge-based global economy. Canada is not an exception. Since the early 1970s, Canada has successfully admitted, on average, 200,000 to 280,000 immigrants annually for permanent residency, primarily for economic development, family reunification and humanitarian affairs. Among these three components, economic class immigrants are the highest priority in its immigration policy. Although Canada admits highly qualified immigrant professionals with the expectation of easily integrating them, many highly skilled immigrants are marginalized in the labour market due to a myriad of layered structural and institutional barriers that prevent them from working in the professions for which they were trained in their country of origin. More than 67% of highly skilled immigrants are more likely to be in jobs for which they are formally overqualified. The deteriorating employment situation of highly educated immigrants, particularly the immigrants of racialized groups, needs analytical scrutiny of the immigration policy of Canada. In this paper, author examine how the historical legacy of colonialism still continues in Canada’s immigration policymaking and how this legacy has impacted developing countries in the global South. Author argue that the Canadian immigration policy is based on the notion of exploiting/dominating smaller countries and immigrants from these countries. Such colonial policies have systematically ‘Othered’ immigrants based on their race, ethnicity, gender, culture, and linguistic characteristics. Recommendations are made to revisit contemporary immigration and settlement policies to effectively integrate immigrants into Canadian society.

Keywords: colonialism, Canadian immigration policy, racialized immigrants, skilled immigrants

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Authors: Hashim Chunpir

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Support processes play an important role to facilitate researchers (users) to accomplish their research activities with the help of cyber-infrastructure(s). However, the current user-support process in cyber-infrastructure needs a feasible tool to support users. This tool must enable the users of a cyber-infrastructure to communicate efficiently with the staffs of a cyber-infrastructure in order to get technical and scientific assistance, whilst saving resources at the same time. This research paper narrates the real story of employing various forms of tools to support the user and staff communication. In addition, this paper projects the lessons learned from an exploration of the help-desk tools in the current state of user support process in Earth System Grid Federation (ESGF) from support staffs’ perspective. ESGF is a climate cyber-infrastructure that facilitates Earth System Modeling (ESM) and is taken as a case study in this paper. Finally, this study proposes a need for a tool, a framework or a platform that not only improves the user support process to address support servicing needs of end-users of e-Science infrastructures but also eases the life of staffs in providing assistance to the users. With the help of such a tool; the collaboration between users and the staffs of cyber-infrastructures is made easier. Consequently, the research activities of the users of e-Science infrastructure will thrive as the scientific and technical support will be available to users. Finally, this results into painless and productive e-Research.

Keywords: e-Science User Services, e-Research in Earth Sciences, Information Technology Services Management (ITSM), user support process, service desk, management of support activities, help desk tools, application of social media

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Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

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With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Saleh Elawgali

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In order to present the effect of the dynamic eccentricity on the stator currents of squirrel cage induction machines, the current spectrums of a 550 kW induction motor was calculated for the cases of full symmetry and dynamic eccentricity. The calculations presented in this paper are based on the Poly-Harmonic Model accounting for static and dynamic eccentricity, stator and rotor slotting, parallel branches as well as cage asymmetry. The calculations were followed by Fourier analysis of the stator currents in steady state operation. The paper presents the stator current spectrums for full symmetry and dynamic eccentricity cases, and demonstrates the harmonics present in each case. The effect of dynamic eccentricity is demonstrating via comparing the current spectrums related to dynamic eccentricity cases with the full symmetry one.

Keywords: current spectrum, dynamic eccentricity, harmonics, Induction machine, slot harmonic zone.

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Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: Mehmet Kale, Ramazan Sencan, Sibel Yavru, Ahmet Ak, Nuri Mamak, Sibel Hasırcıoglu, Mesih Kocamuftuoglu, Yakup Yıldırım, Hasbi Sait Saltık

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Bovine Papilloma Virus (BPV)-induced warts can cause mastitis, teat blindness, reduction of milk yield, udder deformities, and a difficulty in getting the teats into the milking machine. Especially, surgical operations cannot be performed in BPV-induced teat warts because of the increased sensitivity of the breast region and small-sized papillomas. Thus, there is a need to find new topical treatment methods. We have developed a pomade for treatment of BPV in cattle. The pomade is consists of lanoline, snakeskin (two special kind of snake), alcohol, vaseline, and ether. Firstly, we determined 46 cattle with teat warts. In the study, BPV antigen was detected in 28 cattle blood samples (61%) by ELISA. The pomade was applied to all BPV infected animals. The regression and recovery of warts were 100% in all animals. We advised using the pomade for treatment of BPV-induced warts in teats.

Keywords: bovine papilloma virus, pomade, teat, udder

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Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

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According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

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Authors: Khenfer-Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

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this paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a man-machine interface with a voice recognition system that allows the operator to tele-operate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands spoken in two languages: French and Arabic. The recognition rate obtained is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equal to 30 db, the Arabic speech recognition rate is 69% and 80% for French speech recognition rate. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: voice command, HMM, TIMIT, noise, HTK, Arabic, speech recognition

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Authors: Pavel Zlabek, Vaclav Mentl

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The fatigue crack growth rate evaluation is a basic experimental characteristic when assessment o f the remaining lifetime is needed. Within the repair welding technology project, the crack growth rate at cyclic loading was measured in base and weld metals and in the situation when cracks were initiated in base metal and grew into the weld metal through heat-affected zone and back to the base metal. Two welding technologies were applied and specimens in as-welded state and after heat treatment were tested. Fatigue crack growth rate measurement was performed on CrMoV pressure vessel steel and the tests were performed at room temperature. The crack growth rate was measured on CCT test specimens (see figure) for both the base and weld metals and also in the case of crack subsequent transition through all the weld zones. A 500 kN MTS controlled electro-hydraulic testing machine and Model 632.13C-20 MTS extensometer were used to perform the tests.

Keywords: cracks, fatigue, steels, weldments

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Authors: F. L. Bernardo, R. A. S. Zacarias

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The ways to translate are manifold since textual genres undergoing translations are diverse. In this essay, our goal is to give special attention to the literary genre and to the online translation tool Google Translate (GT), widely used either by nonprofessionals or by scholars, in order to show evidence of the indispensability of human wit in a good translation. Our study has its basis on a literary review of prominent authors, with emphasis on translation categories. Also highlighting the issue of polysemous literary translation, we aim to shed light on the translator’s craft and the fallible nature of online translation. To better illustrate these principles, the methodology consisted on performing a comparative analysis involving the original text Moll Flanders by Daniel Defoe in English to its online translation given by GT and to a translation into Brazilian Portuguese performed by a human. We proceeded to identifying and analyzing the degrees of textual equivalence according to the following categories: volume, levels and order. The results have attested the unsuitability in a translation done by a computer connected to the World Wide Web.

Keywords: Google Translator, human translation, literary translation, Moll Flanders

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Authors: Vartan Ahrens Kayayan, Mattias Gustafsson, Erik Dotzauer

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The European Union is introducing the positive energy district concept, which has the goal to reduce overall carbon dioxide emissions. Other studies have already mapped the make-up of such districts, and reviewed their definitions and where they are positioned. The Swedish energy system is unique compared to others in Europe, due to the implementation of low-carbon electricity and heat energy sources and high uptake of district heating. The goal for this paper is to start the discussion about how the concept of positive energy districts can best be applied to the Swedish context and meet their mitigation goals. To explore how these differences impact the formation of positive energy districts, two cases were analyzed for their methods and how these integrate into the Swedish energy system: a district in Uppsala with a focus on energy and another in Helsingborg with a focus on climate. The case in Uppsala uses primary energy calculations which can be critisied but take a virtual border that allows for its surrounding system to be considered. The district in Helsingborg has a complex methodology for considering the life cycle emissions of the neighborhood. It is successful in considering the energy balance on a monthly basis, but it can be problematized in terms of creating sub-optimized systems due to setting tight geographical constraints. The discussion of shaping the definitions and methodologies for positive energy districts is taking place in Europe and Sweden. We identify three pitfalls that must be avoided so that positive energy districts meet their mitigation goals in the Swedish context. The goal of pushing out fossil fuels is not relevant in the current energy system, the mismatch between summer electricity production and winter energy demands should be addressed, and further implementations should consider collaboration with the established district heating grid.

Keywords: positive energy districts, energy system, renewable energy, European Union

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Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Hikmet Cicek

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Transition metal nitrides are widely used as protective coatings on machine parts and cutting tools to protect the surfaces from abrasion and corrosion for decades. In this study, the ternary TiNbVN thin coatings were produced with closed field unbalanced magnetron sputtering system and their structural, mechanical and fatigue-like (multi-pass scratch test) properties were investigated. Two different substrates (M2 and H13 steels) were used to explore substrates effects. X-Ray diffractometer, scanning electron microscope, and energy dispersive spectroscopy were used for the structural and chemical analysis of the coatings. Nanohardness tests were proceed for mechanical properties. The fatigue-like properties of the coatings obtained from the multi-scratch test under three different cycle passes. The results showed that TiNbVN films have excellent fatigue resistance and the coatings deposited on M2 steel substrate have higher hardness and better fatigue resistance.

Keywords: physical vapor deposition, fatigue, metal nitride, multipass scratch test

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

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Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

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Authors: R. B. Patil, B. S. Kothavale, L. Y. Waghmode

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Today, the CNC turning center becomes an important machine tool for manufacturing industry worldwide. However, as the breakdown of a single CNC turning center may result in the production of an entire plant being halted. For this reason, operations and preventive maintenance have to be minimized to ensure availability of the system. Indeed, improving the availability of the CNC turning center as a whole, objectively leads to a substantial reduction in production loss, operating, maintenance and support cost. In this paper, fault tree analysis (FTA) method is used for reliability analysis of CNC turning center. The major faults associated with the system and the causes for the faults are presented graphically. Boolean algebra is used for evaluating fault tree (FT) diagram and for deriving governing reliability model for CNC turning center. Failure data over a period of six years has been collected and used for evaluating the model. Qualitative and quantitative analysis is also carried out to identify critical sub-systems and components of CNC turning center. It is found that, at the end of the warranty period (one year), the reliability of the CNC turning center as a whole is around 0.61628.

Keywords: fault tree analysis (FTA), reliability analysis, risk assessment, hazard analysis

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Authors: Iman Shabanzadeh

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In terms of its geopolitical position, Iran has been one of the main centers of migration movements in the world in recent decades. However, the policy makers' lack of preparation in completing the cycle of social integration of these immigrants, especially the second and third generation, has caused these people to always be prone to leave the country and immigrate to developed and industrialized countries. In this research, the issue of integration of immigrants in Iran from the perspective of four indicators, "Identity Documents", "Access to Banking Services", "Access to Health and Treatment Services" and "Obtaining a Driver's License" will be analyzed. The research method is descriptive-analytical. To collect information, library and document sources in the field of laws and regulations related to immigrants' rights in Iran, semi-structured interviews with experts have been used. The investigations of this study show that none of the residence documents of immigrants in Iran guarantee the full enjoyment of basic citizenship rights for them. In fact, the function of many of these identity documents, such as the census card, educational support card, etc., is only to prevent crossing the border, and none of them guarantee the basic rights of citizenship. Therefore, for many immigrants, the difference between legality and illegality is only in the risk of crossing the border, and this has led to the spread of the habit of illegal presence for them. Despite this, it seems that there is no clear and coherent policy framework around the issue of foreign immigrants in the country. This policy incoherence can be clearly seen in the diversity and plurality of identity and legal documents of the citizens present in the country and the policy maker's lack of planning to integrate and organize the identity of this huge group. Examining the differences and socioeconomic inequalities between immigrants and the native Iranian population shows that immigrants have been poorly integrated into the structures of Iranian society from an economic and social point of view.

Keywords: immigrants, social integration, citizen services, structural inequality

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Authors: Amarnath M., Ramachandra C. G., H. Chelladurai, P..Sateesh Kumar, K. Santhosh Kumar

Abstract:

Journal bearings are extensively used sliding contact machine elements to support radial/axial loaded rotors used in various applications viz. automobile crankshaft, turbine propeller shaft, rope conveyer, heavy duty electric motors. The primary reasons for the failures of these bearings include unstable lubricant film, oil degradation, misalignment, etc. This paper describes the results of experimental investigations carried out to detect surface fatigue wear developed on load bearing the contact surfaces of journal bearing. The test bearing was subjected to fatigue load cycles over a period of 600 hours. The vibration signals were acquired from the journal bearing at regular intervals of 100 hrs. These signals were post-processed by using the vibration analysis technique to obtain diagnostic information of wear propagated in the journal-bearing system.

Keywords: fatigue, journal bearing, sound signals, vibration signals, wear

Procedia PDF Downloads 45

Authors: Glaoui Hachemi

Abstract:

In this paper, a scheme based on multi-input multi output Fuzzy Sliding Mode control (MIMO-FSMC) for linear speed regulation of winding system is proposed. Once the uncoupled model of the winding system was obtained, a smooth control function with a threshold was selected to indicate how far away the case was from the sliding surface. nevertheless, this control function depends closely on the higher bound of the uncertainties, which generates overlap. So, this size has to be chosen with broad care to obtain high performances. Usually, the upper bound of uncertainties is difficult to know before motor operation, so, a Fuzzy Sliding Mode controller is investigated to resolve this problem, a simple Fuzzy inference mechanism is used to decrease the chattering phenomenon by simple adjustments. A simulation study is achieved and that the indicate fuzzy sliding mode controllers have great potential for use as an alternative to the conventional sliding mode control.

Keywords: Winding system, induction machine, Mechanical tension, Proportional-integral (PI), sliding mode control, Fuzzy logic

Procedia PDF Downloads 67

Authors: B. G. Patel, A. K. Desai, S. G. Shah

Abstract:

The main of objective of this paper is to develop new measurement technique without touching the object. DIC is advance measurement technique use to measure displacement of particle with very high accuracy. This powerful innovative technique which is used to correlate two image segments to determine the similarity between them. For this study, nine geometrically similar beam specimens of different sizes with (steel fibers and glass fibers) and without fibers were tested under three-point bending in a closed loop servo-controlled machine with crack mouth opening displacement control with a rate of opening of 0.0005 mm/sec. Digital images were captured before loading (unreformed state) and at different instances of loading and were analyzed using correlation techniques to compute the surface displacements, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It was seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

Keywords: Digital Image Correlation, fibres, self compacting concrete, size effect

Procedia PDF Downloads 366