Search results for: strain based approach
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 36545

Search results for: strain based approach

35345 Networking Approach for Historic Urban Landscape: Case Study of the Porcelain Capital of China

Authors: Ding He, Ping Hu

Abstract:

This article presents a “networking approach” as an alternative to the “layering model” in the issue of the historic urban landscape [HUL], based on research conducted in the historic city of Jingdezhen, the center of the porcelain industry in China. This study points out that the existing HUL concept, which can be traced back to the fundamental conceptual divisions set forth by western science, tends to analyze the various elements of urban heritage (composed of hybrid natural-cultural elements) by layers and ignore the nuanced connections and interweaving structure of various elements. Instead, the networking analysis approach can respond to the challenges of complex heritage networks and to the difficulties that are often faced when modern schemes of looking and thinking of landscape in the Eurocentric heritage model encounters local knowledge of Chinese settlement. The fieldwork in this paper examines the local language regarding place names and everyday uses of urban spaces, thereby highlighting heritage systems grounded in local life and indigenous knowledge. In the context of Chinese “Fengshui”, this paper demonstrates the local knowledge of nature and local intelligence of settlement location and design. This paper suggests that industrial elements (kilns, molding rooms, piers, etc.) and spiritual elements (temples for ceramic saints or water gods) are located in their intimate natural networks. Furthermore, the functional, spiritual, and natural elements are perceived as a whole and evolve as an interactive system. This paper proposes a local and cognitive approach in heritage, which was initially developed in European Landscape Convention and historic landscape characterization projects, and yet seeks a more tentative and nuanced model based on urban ethnography in a Chinese city.

Keywords: Chinese city, historic urban landscape, heritage conservation, network

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35344 Predictive Modelling of Aircraft Component Replacement Using Imbalanced Learning and Ensemble Method

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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35343 Adaptive Cooperative Control of Nonholonomic Mobile Robot Based on Immersion and Invariance

Authors: Imil Hamda Imran, Sami El Ferik

Abstract:

This paper deals with adaptive cooperative control of non holonomic mobile robot moved together in a given formation. The controller is designed based on the Immersion and Invariance (I&I) approach. I&I is a framework for adaptive stabilization of nonlinear systems with uncertain parameters. We investigate the tracking control of non holonomic mobile robot with uncertainties in The I&I-based adaptive controller regulates the angular and linear velocity of non holonomic mobile robot. The results demonstrate that the ability of I&I-based adaptive cooperative control in tracking the position of non holonomic mobile robot.

Keywords: nonholonomic mobile robot, immersion and invariance, adaptive control, uncertain nonlinear systems

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35342 Applying the Extreme-Based Teaching Model in Post-Secondary Online Classroom Setting: A Field Experiment

Authors: Leon Pan

Abstract:

The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

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35341 Modified Naive Bayes-Based Prediction Modeling for Crop Yield Prediction

Authors: Kefaya Qaddoum

Abstract:

Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.

Keywords: tomato yield prediction, naive Bayes, redundancy, WSG

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35340 Image-Based UAV Vertical Distance and Velocity Estimation Algorithm during the Vertical Landing Phase Using Low-Resolution Images

Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

Abstract:

The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: altitude estimation, drone, image processing, trajectory planning

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35339 Prediction and Reduction of Cracking Issue in Precision Forging of Engine Valves Using Finite Element Method

Authors: Xi Yang, Bulent Chavdar, Alan Vonseggern, Taylan Altan

Abstract:

Fracture in hot precision forging of engine valves was investigated in this paper. The entire valve forging procedure was described and the possible cause of the fracture was proposed. Finite Element simulation was conducted for the forging process, with commercial Finite Element code DEFORMTM. The effects of material properties, the effect of strain rate and temperature were considered in the FE simulation. Two fracture criteria were discussed and compared, based on the accuracy and reliability of the FE simulation results. The selected criterion predicted the fracture location and shows the trend of damage increasing with good accuracy, which matches the experimental observation. Additional modification of the punch shapes was proposed to further reduce the tendency of fracture in forging. Finite Element comparison shows a great potential of such application in the mass production.

Keywords: hotforging, engine valve, fracture, tooling

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35338 Cardiokey: A Binary and Multi-Class Machine Learning Approach to Identify Individuals Using Electrocardiographic Signals on Wearable Devices

Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

Abstract:

Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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35337 Commoning as an Approach to Community Planning: An Inquiry into the Role of Urban Local Bodies and Commoners

Authors: Pruthvi Nath Palleti, Sarmada Madhulika Kone

Abstract:

Communities are formed based on the commonalities that exist in a set of individuals and when the group comes together on identifying those commonalities and to achieve their common goals. Thus, community planning with its vision to strengthen the community mostly involves with making or remaking of commons, which results in making or remaking of communities. This paper looks into different practices of planning around the world and tried to establish a link between commoning (the act of exercising the rights over commons by commoners) and participatory approach to community planning.

Keywords: commoners, commoning, community, participatory planning, urban local bodies

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35336 Antifungal Potential of the Plant Growth-Promoting Rhizobacteria Infecting Kidney Beans

Authors: Zhazira Shemsheyeva, Zhanara Suleimenova, Olga Shemshura, Gulnaz Mombekova, Zhanar Rakhmetova

Abstract:

Bacteria that colonize plant roots and promote plant growth are referred to as plant growth-promoting rhizobacteria (PGPR). They not only provide nutrients to the plants (direct plant growth promotion) and protect plants against the phytopathogens (indirect plant growth promotion) but also increase the soil fertility. Indirectly PGPRs improve the plant growth by becoming a biocontrol agent for a fungal pathogen. The antifungal activities of the PGPrhizobacteria were assayed against different species of phytopathogenic fungi such as Fusarium tricinctum, Fusarium oxysporum, Sclerotiniasclerotiorum, and Botrytis cinerea. Pseudomonas putidaSM-1, Azotobacter sp., and Bacillus thuringiensis AKS/16 strains have been used in experimental tests on growth inhibition of phytopathogenic fungi infecting Kidney beans. Agar well diffusion method was used in this study. Diameters of the zones of inhibition were measured in millimeters. It was found that Bacillus thuringiensis AKS/16 strain showed the lowest antifungal activity against all fungal pathogens tested. Zones of inhibition were 15-18 mm. In contrast, Pseudomonas putida SM-1 exhibited good antifungal activity against Fusarium oxysporum and Fusarium tricinctum by producing 29-30 mm clear zones of inhibition. The moderate inhibitory effect was shown by Azotobacter sp. against all fungal pathogens tested with zones of inhibition from24 to 26 mm. In summary, Pseudomonas putida SM-1 strain demonstrated the potential of controlling root rot diseases in kidney beans.

Keywords: PGPR, pseudomonas putida, kindey beans, antifungal activity

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35335 High Temperature Deformation Behavior of Al0.2CoCrFeNiMo0.5 High Entropy alloy

Authors: Yasam Palguna, Rajesh Korla

Abstract:

The efficiency of thermally operated systems can be improved by increasing the operating temperature, thereby decreasing the fuel consumption and carbon footprint. Hence, there is a continuous need for replacing the existing materials with new alloys with higher temperature working capabilities. During the last decade, multi principal element alloys, commonly known as high entropy alloys are getting more attention because of their superior high temperature strength along with good high temperature corrosion and oxidation resistance, The present work focused on the microstructure and high temperature tensile behavior of Al0.2CoCrFeNiMo0.5 high entropy alloy (HEA). Wrought Al0.2CoCrFeNiMo0.5 high entropy alloy, produced by vacuum induction melting followed by thermomechanical processing, is tested in the temperature range of 200 to 900oC. It is exhibiting very good resistance to softening with increasing temperature up to 700oC, and thereafter there is a rapid decrease in the strength, especially beyond 800oC, which may be due to simultaneous occurrence of recrystallization and precipitate coarsening. Further, it is exhibiting superplastic kind of behavior with a uniform elongation of ~ 275 % at 900 oC temperature and 1 x 10-3 s-1 strain rate, which may be due to the presence of fine stable equi-axed grains. Strain rate sensitivity of 0.3 was observed, suggesting that solute drag dislocation glide might be the active mechanism during superplastic kind of deformation. Post deformation microstructure suggesting that cavitation at the sigma phase-matrix interface is the failure mechanism during high temperature deformation. Finally, high temperature properties of the present alloy will be compared with the contemporary high temperature materials such as ferritic, austenitic steels, and superalloys.

Keywords: high entropy alloy, high temperature deformation, super plasticity, post-deformation microstructures

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35334 Reverse Logistics Information Management Using Ontological Approach

Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

Abstract:

Reverse Logistics (RL) Process is considered as complex and dynamic network that involves many stakeholders such as: suppliers, manufactures, warehouse, retails, and costumers, this complexity is inherent in such process due to lack of perfect knowledge or conflicting information. Ontologies, on the other hand, can be considered as an approach to overcome the problem of sharing knowledge and communication among the various reverse logistics partners. In this paper, we propose a semantic representation based on hybrid architecture for building the Ontologies in an ascendant way, this method facilitates the semantic reconciliation between the heterogeneous information systems (ICT) that support reverse logistics Processes and product data.

Keywords: Reverse Logistics, information management, heterogeneity, ontologies, semantic web

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35333 Literature Review and Approach for the Use of Digital Factory Models in an Augmented Reality Application for Decision Making in Restructuring Processes

Authors: Rene Hellmuth, Jorg Frohnmayer

Abstract:

The requirements of the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Even today, the methods and process models used in factory planning are predominantly based on the classical planning principles of Schmigalla, Aggteleky and Kettner, which, however, are not specifically designed for reorganization. In addition, they are designed for a largely static environmental situation and a manageable planning complexity as well as for medium to long-term planning cycles with a low variability of the factory. Existing approaches already regard factory planning as a continuous process that makes it possible to react quickly to adaptation requirements. However, digital factory models are not yet used as a source of information for building data. Approaches which consider building information modeling (BIM) or digital factory models in general either do not refer to factory conversions or do not yet go beyond a concept. This deficit can be further substantiated. A method for factory conversion planning using a current digital building model is lacking. A corresponding approach must take into account both the existing approaches to factory planning and the use of digital factory models in practice. A literature review will be conducted first. In it, approaches to classic factory planning and approaches to conversion planning are examined. In addition, it will be investigated which approaches already contain digital factory models. In the second step, an approach is presented how digital factory models based on building information modeling can be used as a basis for augmented reality tablet applications. This application is suitable for construction sites and provides information on the costs and time required for conversion variants. Thus a fast decision making is supported. In summary, the paper provides an overview of existing factory planning approaches and critically examines the use of digital tools. Based on this preliminary work, an approach is presented, which suggests the sensible use of digital factory models for decision support in the case of conversion variants of the factory building. The augmented reality application is designed to summarize the most important information for decision-makers during a reconstruction process.

Keywords: augmented reality, digital factory model, factory planning, restructuring

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35332 Knowledge Sharing and Organizational Performance: A System Dynamics Approach

Authors: Shachi Pathak

Abstract:

We are living in knowledge based economy where firms can gain competitive advantage with the help of managing knowledge within the organization. The purpose the study is to develop a conceptual model to explain the relationship between factors affecting knowledge sharing, called as knowledge enablers, in an organization, knowledge sharing activities and organizational performance, using system dynamics approach. This research is important since it will provide better understandings on what are the key knowledge enablers to support knowledge sharing activities, and how knowledge sharing activities will affect the capability of an organization to enhance the performance of the organization.

Keywords: knowledge management, knowledge sharing, organizational performance, system dynamics

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35331 Fracture Toughness Properties and FTIR Analysis of Corn Fiber Green Composites

Authors: Ahmed Hashim, Aseel Abdullah

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In this work, the fracture toughness of new green composite based on bio-PMMA resin reinforced with randomly short corn natural fiber of constant weight fraction by 10% wt was investigated. The corn fiber surface was modified by mercerization treatment with two different concentrations of sodium hydroxide (3, and 5% NaOH) for 1.5 and 3 hours respectively. The effect of mercerization treatment on the fracture behavior of the green composites was analyzed by FTIR spectra. NaOH concentration of 3% for 1.5 hrs. That was used for corn fiber green composite should the highest improvement in terms of plane strain fracture toughness KIC which increased by 62 % compared to untreated fiber composite material. On the other hand, increased both concentrations of alkali solution to 5% NaOH and time of soaking to 3 hrs. reduced the values of KIC lower than the value of the unfilled material.

Keywords: green composites, fracture toughness, corn natural fiber, bio-PMMA

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35330 Adaptive Multiple Transforms Hardware Architecture for Versatile Video Coding

Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

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The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: adaptive multiple transforms, AMT, DCT II, hardware, transform, versatile video coding, VVC

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35329 Improving Egg Production by Using Split-Phase Lighting Program

Authors: Hanan Al-Khalaifah, Afaf Al-Nasser

Abstract:

The egg shell quality and oviposition in laying hens are influenced by a range of factors including strain of birds, age, nutrition, water quality, general stress, heat stress, disease, and lighting program inside houses. A layer experiment was conducted to investigate the effect of split-phase lighting program on egg production efficiency. Four different feeds and average phosphorus (av. P) levels were tested. Diet A was a ration with an av. P level of 0.471%; Diet B was a ration with an av. P level of 0.510%; Diet C contained an av. P level of 0.293%; and Diet D contained an av. P level of 0.327%. The split-phase lighting program tested was one that inserted a 7-hour dark period from 9 am to 4 pm to reduce the heat produced by the feeding increment and physical activity of the hens. Diet B produced significantly more eggs than Diet C, or Diet D. Diet A was not significantly different from any of the other diets. Diet B also had the best feed efficiency with the other three diets in the same order and significance as for egg production. Diet D produced eggshells significantly thicker than either Diet A, or Diet B. Diet C produced thicker eggshells than Diet B, whose shells were significantly thinner than the other three diets. There were no differences in egg size. From these data, it is apparent that the minimal av. P level for the Lohmann strain of layer in Kuwait is above 0.327%. There was no difference in egg production or eggshell thickness between the split-phase light treatment and the standard light program. There was no difference in oviposition frequency. The split-phase light used 3.66% less feed, however, which was significant. The standard light produced eggs that were significantly heavier (66.30g vs. 65.73g). These results indicate that considerable savings in feed costs could be attained by using split-phase lighting, especially when cooling is not very efficient.

Keywords: egg, laying, nutrition, oviposition

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35328 Biomass and Lipid Enhancement by Response Surface Methodology in High Lipid Accumulating Indigenous Strain Rhodococcus opacus and Biodiesel Study

Authors: Kulvinder Bajwa, Narsi R. Bishnoi

Abstract:

Finding a sustainable alternative for today’s petrochemical industry is a major challenge facing by researchers, scientists, chemical engineers, and society at the global level. Microorganisms are considered to be sustainable feedstock for 3rd generation biofuel production. In this study, we have investigated the potential of a native bacterial strain isolated from a petrol contaminated site for the production of biodiesel. The bacterium was identified to be Rhodococcus opacus by biochemical test and 16S rRNA. Compositional analysis of bacterial biomass has been carried out by Fourier transform infrared spectroscopy (FTIR) in order to confirm lipid profile. Lipid and biomass were optimized by combination with Box Behnken design (BBD) of response surface methodology. The factors selected for the optimization of growth condition were glucose, yeast extract, and ammonium nitrate concentration. The experimental model developed through RSM in terms of effective operational factors (BBD) was found to be suitable to describe the lipid and biomass production, which indicated higher lipid and biomass with a minimum concentration of ammonium nitrate, yeast extract, and quite higher dose of glucose supplementation. Optimum results of the experiments were found to be 2.88 gL⁻¹ biomass and lipid content 38.75% at glucose 20 gL⁻¹, ammonium nitrate 0.5 gL⁻¹ and yeast extract 1.25 gL⁻¹. Furthermore, GCMS study revealed that Rhodococcus opacus has favorable fatty acid profile for biodiesel production.

Keywords: biofuel, Oleaginious bacteria, Rhodococcus opacus, FTIR, BBD, free fatty acids

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35327 A Socio-Technical Approach to Cyber-Risk Assessment

Authors: Kitty Kioskli, Nineta Polemi

Abstract:

Evaluating the levels of cyber-security risks within an enterprise is most important in protecting its information system, services and all its digital assets against security incidents (e.g. accidents, malicious acts, massive cyber-attacks). The existing risk assessment methodologies (e.g. eBIOS, OCTAVE, CRAMM, NIST-800) adopt a technical approach considering as attack factors only the capability, intention and target of the attacker, and not paying attention to the attacker’s psychological profile and personality traits. In this paper, a socio-technical approach is proposed in cyber risk assessment, in order to achieve more realistic risk estimates by considering the personality traits of the attackers. In particular, based upon principles from investigative psychology and behavioural science, a multi-dimensional, extended, quantifiable model for an attacker’s profile is developed, which becomes an additional factor in the cyber risk level calculation.

Keywords: attacker, behavioural models, cyber risk assessment, cybersecurity, human factors, investigative psychology, ISO27001, ISO27005

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35326 Stator Short-Circuits Fault Diagnosis in Induction Motors Using Extended Park’s Vector Approach through the Discrete Wavelet Transform

Authors: K. Yahia, A. Ghoggal, A. Titaouine, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), Inter-turn Short-Circuits Diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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35325 Thick Data Techniques for Identifying Abnormality in Video Frames for Wireless Capsule Endoscopy

Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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35324 Bi-Criteria Vehicle Routing Problem for Possibility Environment

Authors: Bezhan Ghvaberidze

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A multiple criteria optimization approach for the solution of the Fuzzy Vehicle Routing Problem (FVRP) is proposed. For the possibility environment the levels of movements between customers are calculated by the constructed simulation interactive algorithm. The first criterion of the bi-criteria optimization problem - minimization of the expectation of total fuzzy travel time on closed routes is constructed for the FVRP. A new, second criterion – maximization of feasibility of movement on the closed routes is constructed by the Choquet finite averaging operator. The FVRP is reduced to the bi-criteria partitioning problem for the so called “promising” routes which were selected from the all admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in the real-time computing. For the numerical solution of the bi-criteria partitioning problem the -constraint approach is used. An exact algorithm is implemented based on D. Knuth’s Dancing Links technique and the algorithm DLX. The Main objective was to present the new approach for FVRP, when there are some difficulties while moving on the roads. This approach is called FVRP for extreme conditions (FVRP-EC) on the roads. Also, the aim of this paper was to construct the solving model of the constructed FVRP. Results are illustrated on the numerical example where all Pareto-optimal solutions are found. Also, an approach for more complex model FVRP with time windows was developed. A numerical example is presented in which optimal routes are constructed for extreme conditions on the roads.

Keywords: combinatorial optimization, Fuzzy Vehicle routing problem, multiple objective programming, possibility theory

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35323 Fatigue Tests of New Assembly Bolt Connections for Perspective Temporary Steel Railway Bridges

Authors: Marcela Karmazínová, Michal Štrba, Miln Pilgr

Abstract:

The paper deals with the problems of the actual behavior, failure mechanism and load-carrying capacity of the special bolt connection developed and intended for the assembly connections of truss main girders of perspective railway temporary steel bridges. Within the framework of this problem solution, several types of structural details of assembly joints have been considered as the conceptual structural design. Based on the preliminary evaluation of advantages or disadvantages of these ones, in principle two basic structural configurations so-called “tooth” and “splice-plate” connections have been selected for the subsequent detailed investigation. This investigation is mainly based on the experimental verification of the actual behavior, strain and failure mechanism and corresponding strength of the connection, and on its numerical modeling using FEM. This paper is focused only on the cyclic loading (fatigue) tests results of “splice-plate” connections and their evaluation, which have already been finished. Simultaneously with the fatigue tests, the static loading tests have been realized too, but these ones, as well as FEM numerical modeling, are not the subject of this paper.

Keywords: Bolt assembly connection, cyclic loading, failure mechanisms, fatigue strength, steel structure, structural detail category, temporary railway bridge

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35322 Flocking Swarm of Robots Using Artificial Innate Immune System

Authors: Muneeb Ahmad, Ali Raza

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A computational method inspired by the immune system (IS) is presented, leveraging its shared characteristics of robustness, fault tolerance, scalability, and adaptability with swarm intelligence. This method aims to showcase flocking behaviors in a swarm of robots (SR). The innate part of the IS offers a variety of reactive and probabilistic cell functions alongside its self-regulation mechanism which have been translated to enable swarming behaviors. Although, the research is specially focused on flocking behaviors in a variety of simulated environments using e-puck robots in a physics-based simulator (CoppeliaSim); the artificial innate immune system (AIIS) can exhibit other swarm behaviors as well. The effectiveness of the immuno-inspired approach has been established with extensive experimentations, for scalability and adaptability, using standard swarm benchmarks as well as the immunological regulatory functions (i.e., Dendritic Cells’ Maturity and Inflammation). The AIIS-based approach has proved to be a scalable and adaptive solution for emulating the flocking behavior of SR.

Keywords: artificial innate immune system, flocking swarm, immune system, swarm intelligence

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35321 Numerical Simulation of Seismic Process Accompanying the Formation of Shear-Type Fault Zone in Chuya-Kuray Depressions

Authors: Mikhail O. Eremin

Abstract:

Seismic activity around the world is clearly a threat to people's lives, as well as infrastructure and capital construction. It is the instability of the latter to powerful earthquakes that most often causes human casualties. Therefore, during construction it is necessary to take into account the risks of large-scale natural disasters. The task of assessing the risks of natural disasters is one of the most urgent at the present time. The final goal of any study of earthquakes is forecasting. This is especially important for seismically active regions of the planet where earthquakes occur frequently. Gorni Altai is one of such regions. In work, we developed the physical-mathematical model of stress-strain state evolution of loaded geomedium with the purpose of numerical simulation of seismic process accompanying the formation of Chuya-Kuray fault zone Gorni Altay, Russia. We build a structural model on the base of seismotectonic and paleoseismogeological investigations, as well as SRTM-data. Base of mathematical model is the system of equations of solid mechanics which includes the fundamental conservation laws and constitutive equations for elastic (Hooke's law) and inelastic deformation (modified model of Drucker-Prager-Nikolaevskii). An initial stress state of the model correspond to gravitational. Then we simulate an activation of a buried dextral strike-slip paleo-fault located in the basement of the model. We obtain the stages of formation and the structure of Chuya-Kuray fault zone. It is shown that results of numerical simulation are in good agreement with field observations in statistical sense. Simulated seismic process is strongly bound to the faults - lineaments with high degree of inelastic strain localization. Fault zone represents en-echelon system of dextral strike-slips according to the Riedel model. The system of surface lineaments is represented with R-, R'-shear bands, X- and Y-shears, T-fractures. Simulated seismic process obeys the laws of Gutenberg-Richter and Omori. Thus, the model describes a self-similar character of deformation and fracture of rocks and geomedia. We also modified the algorithm of determination of separate slip events in the model due to the features of strain rates dependence vs time.

Keywords: Drucker-Prager model, fault zone, numerical simulation, Riedel bands, seismic process, strike-slip fault

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35320 Antibacterial Activity of Bacillus thuringiensis Activated Delta-endotoxins

Authors: R. Gounina-Allouane, N. Ouali, F. Z. Berrabah, A. Bentaleb

Abstract:

For a long time, the Gram-positive spore-forming bacteria Bacillus thuringiensis (Bt) has been widely used in biological control against devastating and disease vectors insects. This is due to the insecticidal activity of its crystalline parasporal inclusion (crystals) predominantly comprised of one or more proteins (Cry and Cyt proteins) also called δ-endotoxins, produced during sporulation. The shape and composition of Bt crystals vary among strains and crystalline proteins are extremely varied (more than 475 cry gene were discovered). The insecticidal activity of Bt crystals is very well studied, thus their insecticidal mode of action is well established, however, their antimicrobial effect is largely unknown. The lack of data on the antimicrobial effect of crystalline proteins of Bt and the need for searching new antimicrobial molecules encouraged us to carried out this study. The antibacterial effect of δ-endotoxines produced by two Bt stains; a strain isolated from soil at northern of Algeria (Bt 7.2.B), and a strain isolated from a bioinsecticide (Bacillus thuringiensis var aizawai), activated by proteolysis, was assayed on clinical bacterial strains and ATCC collection ones respectively. Gram positive and negative clinical bacterial strains (Escherichia coli, Klebsiella pneumonaie, Pseudomonas aeruginosa, Staphylococcus aureus) were sensitive to activated Bt 72B endotoxins. Similarly, bacterial strains from ATCC collection (Escherichia coli ATCC 25922, Pseudomonas aerugenosa ATCC 27853, Staphylococcus aureus ATCC 25923) were sensitive to activated B. thuringiensis var aizawai δ-endotoxines. The activated δ-endotoxins were separated by SDS-PAGE.

Keywords: Bacillus thuringiensis, crystals, cry proteins, δ-endotoxins, antibacterial activity

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35319 Meso-Scopic Structural Analysis of Chaura Thrust, Himachal Pradesh, India

Authors: Rajkumar Ghosh

Abstract:

Jhakri Thrust (JT) coeval of Sarahan Thrust (ST) was later considered to be part of Chaura Thrust (CT). The Main Central Thrust (MCT) delimits the southern extreme of Higher Himalaya, whereas the northern boundary defines by South Tibetan Detachment System (STDS). STDS is parallel set of north dipping extensional faults. The activation timing of MCT and STDS. MCT activated in two parts (MCT-L during 15- 0.7 Ma, and MCT-U during 25-14 Ma). Similarly, STDS triggered in two parts (STDS-L during 24-12 Ma, and STDS-U during 19-14 Ma). The activation ages for MBT and MFT. Besides, the MBT occurred during 11-9 Ma, and MFT followed as <2.5 Ma. There are two mylonitised zones (zone of S-C fabric) found under the microscope. Dynamic and bulging recrystallization and sub-grain formation was documented under the optical microscope from samples collected from these zones. The varieties of crenulated schistosity are shown in photomicrographs. In a rare and uncommon case, crenulation cleavage and sigmoid Muscovite were found together side-by-side. Recrystallized quartzo-feldspathic grains exist in between crenulation cleavages. These thin-section studies allow three possible hypotheses for such variations in crenulation cleavages. S/SE verging meso- and micro-scale box folds around Chaura might be a manifestation of some structural upliftment. Near Chaura, kink folds are visible. Prominent asymmetric shear sense indicators in augen mylonite are missing in meso-scale but dominantly present under the microscope. The main foliation became steepest (range of dip ~ 65 – 80 º) at this place. The aim of this section is to characterize the box fold and its signature in the regional geology of Himachal Himalaya. Grain Boundary Migration (GBM) associated temperature range (400–750 ºC) from microstructural studies in grain scale along Jhakri-Wangtu transect documented. Oriented samples were collected from the Jhakri-Chaura transect at a regular interval of ~ 1km for strain analysis. The Higher Himalayan Out-of-Sequence Thrust (OOST) in Himachal Pradesh is documented a decade ago. The OOST in other parts of the Himalayas is represented as a line in between MCTL and MCTU. But In Himachal Pradesh area, OOST activated the MCTL as well as in between a zone located south of MCTU. The expectations for strain variation near the OOST are very obvious. But multiple sets of OOSTs may produce a zigzag pattern of strain accumulation for this area and figure out the overprinting structures for multiple sets of OOSTs.

Keywords: Chaura Thrust, out-of-sequence thrust, Main Central Thrust, Sarahan Thrust

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35318 Whether Chaos Theory Could Reconstruct the Ancient Societies

Authors: Zahra Kouzehgari

Abstract:

Since the early emergence of chaos theory in the 1970s in mathematics and physical science, it has increasingly been developed and adapted in social sciences as well. The non-linear and dynamic characteristics of the theory make it a useful conceptual framework to interpret the complex social systems behavior. Regarding chaotic approach principals, sensitivity to initial conditions, dynamic adoption, strange attractors and unpredictability this paper aims to examine whether chaos approach could interpret the ancient social changes. To do this, at first, a brief history of the chaos theory, its development and application in social science as well as the principals making the theory, then its application in archaeological since has been reviewed. The study demonstrates that although based on existing archaeological records reconstruct the whole social system of the human past, the non-linear approaches in studying social complex systems would be of a great help in finding general order of the ancient societies and would enable us to shed light on some of the social phenomena in the human history or to make sense of them.

Keywords: archaeology, non-linear approach, chaos theory, ancient social systems

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35317 Engineering of Reagentless Fluorescence Biosensors Based on Single-Chain Antibody Fragments

Authors: Christian Fercher, Jiaul Islam, Simon R. Corrie

Abstract:

Fluorescence-based immunodiagnostics are an emerging field in biosensor development and exhibit several advantages over traditional detection methods. While various affinity biosensors have been developed to generate a fluorescence signal upon sensing varying concentrations of analytes, reagentless, reversible, and continuous monitoring of complex biological samples remains challenging. Here, we aimed to genetically engineer biosensors based on single-chain antibody fragments (scFv) that are site-specifically labeled with environmentally sensitive fluorescent unnatural amino acids (UAA). A rational design approach resulted in quantifiable analyte-dependent changes in peak fluorescence emission wavelength and enabled antigen detection in vitro. Incorporation of a polarity indicator within the topological neighborhood of the antigen-binding interface generated a titratable wavelength blueshift with nanomolar detection limits. In order to ensure continuous analyte monitoring, scFv candidates with fast binding and dissociation kinetics were selected from a genetic library employing a high-throughput phage display and affinity screening approach. Initial rankings were further refined towards rapid dissociation kinetics using bio-layer interferometry (BLI) and surface plasmon resonance (SPR). The most promising candidates were expressed, purified to homogeneity, and tested for their potential to detect biomarkers in a continuous microfluidic-based assay. Variations of dissociation kinetics within an order of magnitude were achieved without compromising the specificity of the antibody fragments. This approach is generally applicable to numerous antibody/antigen combinations and currently awaits integration in a wide range of assay platforms for one-step protein quantification.

Keywords: antibody engineering, biosensor, phage display, unnatural amino acids

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35316 Comparison of Risk and Return on Trading and Profit Sharing Based Financing Contract in Indonesian Islamic Bank

Authors: Fatin Fadhilah Hasib, Puji Sucia Sukmaningrum, Imron Mawardi, Achsania Hendratmi

Abstract:

Murabaha is the most popular contract by the Islamic banks in Indonesia, since there is opinion stating that the risk level of mudharaba and musyaraka are higher and the return is uncertain. This research aims to analyze the difference of return, risk, and variation coefficient between profit sharing-based and trading-based financing in Islamic bank. This research uses quantitative approach using Wilcoxon signed rank test with data sampled from 13 Indonesian Islamic banks, collected from their quarterly financial reports from 2011 to 2015. The result shows the significant difference in return, while risk and variation coefficient are almost same. From the analysis, it can be concluded that profit sharing-based financing is less desirable not because of its risk. Trading-based financing is more desirable than the profit sharing because of its return.

Keywords: financing, Islamic bank, return, risk

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