Search results for: input processing

Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng

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Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.

Keywords: indoor navigation, low light, RGB-D camera, vision based

Procedia PDF Downloads 453

Authors: Gonzalez Carlos, Martinez Fransisco

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There are various types of analysis that allow us to involve seismic phenomena that cause strong requirements for structures that are designed by society; one of them is a probabilistic analysis which works from prediction equations that have been created based on metadata seismic compiled in different regions. These equations form models that are used to describe the 5% damped pseudo spectra response for the various zones considering some easily known input parameters. The biggest problem for the creation of these models requires data with great robust statistics that support the results, and there are several places where this type of information is not available, for which the use of alternative methodologies helps to achieve adjustments to different models of seismic prediction.

Keywords: GMPM, 5% damped pseudo-response spectra, models of seismic prediction, PSHA

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Vishwanath Mali, Hemant Warhatkar, Raju Pawade

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Drilling of bone has been always challenging for surgeons due to the adverse effect it may impart to bone tissues. Force has to be applied manually by the surgeon while performing conventional bone drilling which may lead to permanent death of bone tissues and nerves. During bone drilling the temperature of the bone tissues increases to higher values above 47 ⁰C that causes thermal osteonecrosis resulting into screw loosening and subsequent implant failures. An attempt has been made here to study the input drilling parameters and surgical drill bit geometry affecting bone health during bone drilling. A One Factor At a Time (OFAT) method is used to plan the experiments. Input drilling parameters studied include spindle speed and feed rate. The drill bit geometry parameter studied include point angle and helix angle. The output variables are drilling thrust force and bone temperature. The experiments were conducted on goat femur bone at room temperature 30 ⁰C. For measurement of thrust forces KISTLER cutting force dynamometer Type 9257BA was used. For continuous data acquisition of temperature NI LabVIEW software was used. Fixture was made on RPT machine for holding the bone specimen while performing drilling operation. Bone specimen were preserved in deep freezer (LABTOP make) under -40 ⁰C. In case of drilling parameters, it is observed that at constant feed rate when spindle speed increases, thrust force as well as temperature decreases and at constant spindle speed when feed rate increases thrust force as well as temperature increases. The effect of drill bit geometry shows that at constant helix angle when point angle increases thrust force as well as temperature increases and at constant point angle when helix angle increase thrust force as well as temperature decreases. Hence it is concluded that as the thrust force increases temperature increases. In case of drilling parameter, the lowest thrust force and temperature i.e. 35.55 N and 36.04 ⁰C respectively were recorded at spindle speed 2000 rpm and feed rate 0.04 mm/rev. In case of drill bit geometry parameter, the lowest thrust force and temperature i.e. 40.81 N and 34 ⁰C respectively were recorded at point angle 70⁰ and helix angle 25⁰ Hence to avoid thermal necrosis of bone it is recommended to use higher spindle speed, lower feed rate, low point angle and high helix angle. The hard nature of cortical bone contributes to a greater rise in temperature whereas a considerable drop in temperature is observed during cancellous bone drilling.

Keywords: bone drilling, helix angle, point angle, thrust force, temperature, thermal necrosis

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Authors: Mohammad A. Bani-Khaled

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In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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Authors: Muhammad Arif Jalil, Xaythavay Luangvilay, Montree Bunruangses, Somchat Sonasang, Preecha Yupapin

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Black and white holes form the entangled pair⟨BH│WH⟩, where a white hole occurs when the particle moves at the same speed as light. The entangled black-white hole pair is at the center with the radian between the gap. When the speed of particle motion is slower than light, the black hole is gravitational (positive gravity), where the white hole is smaller than the black hole. On the downstream side, the entangled pair appears to have a black hole outside the gap increases until the white holes disappear, which is the emptiness paradox. On the upstream side, when moving faster than light, white holes form times tunnels, with black holes becoming smaller. It will continue to move faster and further when the black hole disappears and becomes a wormhole (Singularity) that is only a white hole in emptiness (Emptiness). This research studies use of black and white holes generated by a two-level circuit for communication transmission carriers, in which high ability and capacity of data transmission can be obtained. The black and white hole pair can be generated by the two-level system circuit when the speech of a particle on the circuit is equal to the speed of light. The black hole forms when the particle speed has increased from slower to equal to the light speed, while the white hole is established when the particle comes down faster than light. They are bound by the entangled pair, signal and idler, ⟨Signal│Idler⟩, and the virtual ones for the white hole, which has an angular displacement of half of π radian. A two-level system is made from an electronic circuit to create black and white holes bound by the entangled bits that are immune or cloning-free from thieves. Start by creating a wave-particle behavior when its speed is equal to light black hole is in the middle of the entangled pair, which is the two bit gate. The required information can be input into the system and wrapped by the black hole carrier. A timeline (Tunnel) occurs when the wave-particle speed is faster than light, from which the entangle pair is collapsed. The transmitted information is safely in the time tunnel. The required time and space can be modulated via the input for the downlink operation. The downlink is established when the particle speed is given by a frequency(energy) form is down and entered into the entangled gap, where this time the white hole is established. The information with the required destination is wrapped by the white hole and retrieved by the clients at the destination. The black and white holes are disappeared, and the information can be recovered and used.

Keywords: cloning free, time machine, teleportation, two-level system

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Authors: I. Zahraoui, J. Terhzaz, A. Errkik, El. H. Abdelmounim, A. Tajmouati, L. Abdellaoui, N. Ababssi, M. Latrach

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This paper presents a novel design of a microstrip fractal antenna based on the use of Sierpinski triangle shape, it’s designed and simulated by using FR4 substrate in the operating frequency bands (GPS, WiMAX), the design is a fractal antenna with a modified ground structure. The proposed antenna is simulated and validated by using CST Microwave Studio Software, the simulated results presents good performances in term of radiation pattern and matching input impedance.

Keywords: dual-band antenna, fractal antenna, GPS band, modified ground structure, sierpinski triangle, WiMAX band

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Authors: Latha Nataraj, Todd Henry, Micheal Wallock, Asha Hall, Christine Hatter, Babak Anasori, Yury Gogotsi

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Multifunctional composites with enhanced strength and toughness for superior damage tolerance are essential for advanced aerospace and military applications. Detection of structural changes prior to visible damage may be achieved by incorporating fillers with tunable properties such as two-dimensional (2D) nanomaterials with high aspect ratios and more surface-active sites. While 2D graphene with large surface areas, good mechanical properties, and high electrical conductivity seems ideal as a filler, the single-atomic thickness can lead to bending and rolling during processing, requiring post-processing to bond to polymer matrices. Lately, an emerging family of 2D transition metal carbides and nitrides, MXenes, has attracted much attention since their discovery in 2011. Metallic electronic conductivity and good mechanical properties, even with increased polymer content, coupled with hydrophilicity make MXenes a good candidate as a filler material in polymer composites and exceptional as multifunctional damage indicators in composites. Here, we systematically study MXene-based (Ti₃C₂) coated on glass fibers for fiber reinforced polymer composite for self-sensing using microscopy and micromechanical testing. Further testing is in progress through the investigation of local variations in optical, acoustic, and thermal properties within the damage sites in response to strain caused by mechanical loading.

Keywords: damage sensing, fiber composites, MXene, self-sensing

Procedia PDF Downloads 118

Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

Procedia PDF Downloads 142

Authors: Chong-Yang Qiao

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Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: mobile augmented reality, remote collaboration, user experience, cognition model

Procedia PDF Downloads 194

Authors: Mahesh Kothari, K. D. Gharde

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The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river.

Keywords: transferred function, sigmoid, backpropagation, membership function, defuzzification

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Authors: D. F. Carvalho, A. O. Uscamayta, J. C. Guerrero, H. F. Oliveira, P. M. Azevedo-Marques

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The creation of vector contours slices (ROIs) on body silhouettes in oncologic patients is an important step during the radiotherapy planning in clinic and hospitals to ensure the accuracy of oncologic treatment. The radiotherapy planning of patients is performed by complex softwares focused on analysis of tumor regions, protection of organs at risk (OARs) and calculation of radiation doses for anomalies (tumors). These softwares are supplied for a few manufacturers and run over sophisticated workstations with vector processing presenting a cost of approximately twenty thousand dollars. The Brazilian project SIPRAD (Radiotherapy Planning System) presents a proposal adapted to the emerging countries reality that generally does not have the monetary conditions to acquire some radiotherapy planning workstations, resulting in waiting queues for new patients treatment. The SIPRAD project is composed by a set of integrated and interoperabilities softwares that are able to execute all stages of radiotherapy planning on simple personal computers (PCs) in replace to the workstations. The goal of this work is to present an image processing technique, computationally feasible, that is able to perform an automatic contour delineation in patient body silhouettes (SIPRAD-Body). The SIPRAD-Body technique is performed in tomography slices under grayscale images, extending their use with a greedy algorithm in three dimensions. SIPRAD-Body creates an irregular polyhedron with the Canny Edge adapted algorithm without the use of preprocessing filters, as contrast and brightness. In addition, comparing the technique SIPRAD-Body with existing current solutions is reached a contours similarity at least 78%. For this comparison is used four criteria: contour area, contour length, difference between the mass centers and Jaccard index technique. SIPRAD-Body was tested in a set of oncologic exams provided by the Clinical Hospital of the University of Sao Paulo (HCRP-USP). The exams were applied in patients with different conditions of ethnology, ages, tumor severities and body regions. Even in case of services that have already workstations, it is possible to have SIPRAD working together PCs because of the interoperability of communication between both systems through the DICOM protocol that provides an increase of workflow. Therefore, the conclusion is that SIPRAD-Body technique is feasible because of its degree of similarity in both new radiotherapy planning services and existing services.

Keywords: radiotherapy, image processing, DICOM RT, Treatment Planning System (TPS)

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Authors: Jimmy Jiun-Ming Su, Yuan-Min Lin

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Bioprinting has been applied to produce 3D cellular constructs for tissue engineering. Microextrusion printing is the most common used method. However, printing low viscosity bioink is a challenge for this method. Herein, we developed a new 3D printing system to fabricate cell-laden hydrogels via a DLP-based projector. The bioprinter is assembled from affordable equipment including a stepper motor, screw, LED-based DLP projector, open source computer hardware and software. The system can use low viscosity and photo-polymerized bioink to fabricate 3D tissue mimics in a layer-by-layer manner. In this study, we used gelatin methylacrylate (GelMA) as bioink for stem cell encapsulation. In order to reinforce the printed construct, surface modified hydroxyapatite has been added in the bioink. We demonstrated the silanization of hydroxyapatite could improve the crosslinking between the interface of hydroxyapatite and GelMA. The results showed that the incorporation of silanized hydroxyapatite into the bioink had an enhancing effect on the mechanical properties of printed hydrogel, in addition, the hydrogel had low cytotoxicity and promoted the differentiation of embedded human bone marrow stem cells (hBMSCs) and retinal pigment epithelium (RPE) cells. Moreover, this bioprinting system has the ability to generate microchannels inside the engineered tissues to facilitate diffusion of nutrients. We believe this 3D bioprinting system has potential to fabricate various tissues for clinical applications and regenerative medicine in the future.

Keywords: bioprinting, cell encapsulation, digital light processing, GelMA hydrogel

Procedia PDF Downloads 171

Authors: Amy M. Kwon

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Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

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Authors: M. Yusefzad

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Law of energy conservation is one of the fundamental laws of physics. Energy is conserved, and the total amount of energy is constant. It can be transferred from one object to another and changed from one state to another. However, in the case of wave interference, this law faces important contradictions. Based on the presented mathematical relationship in this paper, it seems that validity of this law depends on the path of energy wave, like light, in which it is located. In this paper, by using some fundamental concepts in physics like the constancy of the electromagnetic wave speed in a specific media and wave theory of light, it will be shown that law of energy conservation is not valid in every condition and in some circumstances, it is possible to increase energy of a system with a determined amount of energy without any input.

Keywords: power, law of energy conservation, electromagnetic wave, interference, Maxwell’s equations

Procedia PDF Downloads 259

Authors: Bentayeb-Ait Lounis Saïda, Cheref Zahia, Cherifi Thizi, Ri Kahina Bahmed, Kahina Hallali Yasmine Abdellaoui, Kenza Adli

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Algeria is the leading consumer of dairy products in North Africa. This is a fact. However, the nutritional quality of the latter remains unknown. The aim of this study is to characterise the dairy products available on the Algerian market in order to assess whether they constitute a healthy and safe choice. To do this, it collected data on the labelling of 390 dairy products, including cheese, yoghurt, UHT milk and milk drinks, infant formula and dairy creams. We assessed their degree of processing according to the NOVA classification, as well as the proportion of imitation products. The study was carried out between March 2020 and August 2023. The results show that 88% are ultra-processed; 84% for 'cheese', 92% for dairy creams, 92% for 'yoghurt', 100% for infant formula, 92% for margarines and 36% for UHT milk/dairy drinks. As for imitation/analogue dairy products, the study revealed the following proportions: 100% for infant formula, 78% for butter/margarine, 18% for UHT milk/milk-based drinks, 54% for cheese, 2% for camembert and 75% for dairy cream. The harmful effects of consuming ultra-processed products on long-term health are increasingly documented in dozens of publications. The findings of this study sound the alarm about the health risks to which Algerian consumers are exposed. Various scientific, economic and industrial bodies need to be involved in order to safeguard consumer health in both the short and long term. Food awareness and education campaigns should be organised.

Keywords: dairy, UPF, NOVA, yoghurt, cheese

Procedia PDF Downloads 26

Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

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Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

Procedia PDF Downloads 475

Authors: Jung–Min Yang

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In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine.

Keywords: asynchronous sequential machines, parallel composi-tion, corrective control, fault tolerance

Procedia PDF Downloads 224

Authors: Lahari Ramya Pa, Sudhakar Ib, Madhu Vc, Madhusudhan Reddy Gd, Srinivasa Rao E.

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Selection of suitable armor materials for defense applications is very crucial with respect to increasing mobility of the systems as well as maintaining safety. Therefore, determining the material with the lowest possible areal density that resists the predefined threat successfully is required in armor design studies. A number of light metal and alloys are come in to forefront especially to substitute the armour grade steels. AA5083 aluminium alloy which fit in to the military standards imposed by USA army is foremost nonferrous alloy to consider for possible replacement of steel to increase the mobility of armour vehicles and enhance fuel economy. Growing need of AA5083 aluminium alloy paves a way to develop supplement aluminium alloys maintaining the military standards. It has been witnessed that AA 2xxx aluminium alloy, AA6xxx aluminium alloy and AA7xxx aluminium alloy are the potential material to supplement AA5083 aluminium alloy. Among those cited aluminium series alloys AA7xxx aluminium alloy (heat treatable) possesses high strength and can compete with armour grade steels. Earlier investigations revealed that layering of AA7xxx aluminium alloy can prevent spalling of rear portion of armour during ballistic impacts. Hence, present investigation deals with fabrication of hard layer (made of boron carbide) i.e. layer on AA 7075 aluminium alloy using friction stir processing with an intention of blunting the projectile in the initial impact and backing tough portion(AA7xxx aluminium alloy) to dissipate residual kinetic energy. An analytical approach has been adopted to unfold the ballistic performance of projectile. Penetration of projectile inside the armour has been resolved by considering by strain energy model analysis. Perforation shearing areas i.e. interface of projectile and armour is taken in to account for evaluation of penetration inside the armour. Fabricated surface composites (targets) were tested as per the military standard (JIS.0108.01) in a ballistic testing tunnel at Defence Metallurgical Research Laboratory (DMRL), Hyderabad in standardized testing conditions. Analytical results were well validated with experimental obtained one.

Keywords: AA7075 aluminium alloy, friction stir processing, boron carbide, ballistic performance, target

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Authors: M. T. Alodat

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In this paper, we propose a generalization to the Gaussian process regression(GPR) model called the extended skew Gaussian process for regression(ESGPr) model. The ESGPR model works better than the GPR model when the errors are skewed. We derive the predictive distribution for the ESGPR model at a new input. Also we apply the ESGPR model to FOREX data and we find that it fits the Forex data better than the GPR model.

Keywords: extended skew normal distribution, Gaussian process for regression, predictive distribution, ESGPr model

Procedia PDF Downloads 547

Authors: Janneth González, George Barreto, Ludis Morales, Angélica Sabogal

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Sea anemone neurotoxins are peptides that interact with Na+ and K+ channels, resulting in specific alterations on their functions. Some of these neurotoxins (1ROO, 1BGK, 2K9E, 1BEI) are important for the treatment of nearly eighty autoimmune disorders due to their specificity for Kv1.3 channel. The aim of this study was to identify the common residues among these neurotoxins by computational methods, and establish whether there is a pattern useful for the future generation of a treatment for autoimmune diseases. Our results showed eight new key common residues between the studied neurotoxins interacting with a histidine ring and the selectivity filter of the receptor, thus showing a possible pattern of interaction. This knowledge may serve as an input for the design of more promising drugs for autoimmune treatments.

Keywords: neurotoxins, potassium channel, Kv1.3, computational methods, autoimmune diseases

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Authors: Mahnaz Hosseinzadeh, Mohammad Reza Mehregan

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In this paper, we have developed a morphological field to assist multi- methodology (combining methodologies together in whole or part) in Operations Research (OR) for the problem contexts in Iranian organizations. So, we have attempted to identify some dimensions for problem context according to Iranian organizational problems. Then, a general morphological program is designed which helps the OR practitioner to determine the suitable OR methodology as output for any configuration of conditions in a problem context as input and to reveal the fields necessary to be improved in OR. Applying such a program would have interesting results for OR practitioners.

Keywords: hard, soft and emancipatory operations research, General Morphological Analysis (GMA), multi-methodology, problem context

Procedia PDF Downloads 294

Authors: R. Tajau, R. Rohani, M. S. Alias, N. H. Mudri, K. A. Abdul Halim, M. H. Harun, N. Mat Isa, R. Che Ismail, S. Muhammad Faisal, M. Talib, M. R. Mohamed Zin

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Bio-based polymeric materials are increasingly used for a variety of applications, including surface coating, drug delivery systems, and tissue engineering. These polymeric materials are ideal for the aforementioned applications because they are derived from natural resources, non-toxic, low-cost, biocompatible, and biodegradable, and have promising thermal and mechanical properties. The nature of hydrocarbon chains, carbon double bonds, and ester bonds allows various sources of oil (edible), such as soy, sunflower, olive, and oil palm, to fine-tune their particular structures in the development of innovative materials. Palm oil can be the most eminent raw material used for manufacturing new and advanced natural polymeric materials involving radiation techniques, such as coating resins, nanoparticles, scaffold, nanotubes, nanocomposites, and lithography for different branches of the industry in countries where oil palm is abundant. The radiation technique is among the most versatile, cost-effective, simple, and effective methods. Crosslinking, reversible addition-fragmentation chain transfer (RAFT), polymerisation, grafting, and degradation are among the radiation mechanisms. Exposure to gamma, EB, UV, or laser irradiation, which are commonly used in the development of polymeric materials, is used in these mechanisms. Therefore, this review focuses on current radiation processing technologies for the development of various radiation-curable bio-based polymeric materials with a promising future in biomedical and industrial applications. The key focus of this review is on radiation curable palm oil-based products, which have been published frequently in recent studies.

Keywords: palm oil, radiation processing, surface coatings, VOC

Procedia PDF Downloads 180

Authors: F. Bellali, M. Kharroubi, M. Loutfi, N.Bourhim

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In Morocco, fish processing industry is an important source income for a large amount of byproducts including skins, bones, heads, guts and scales. Those underutilized resources particularly scales contain a large amount of proteins and calcium. Scales from Sardina plichardus resulting from the transformation operation have the potential to be used as raw material for the collagen production. Taking into account this strong expectation of the regional fish industry, scales sardine upgrading is well justified. In addition, political and societal demands for sustainability and environment-friendly industrial production systems, coupled with the depletion of fish resources, drive this trend forward. Therefore, fish scale used as a potential source to isolate collagen has a wide large of applications in food, cosmetic and bio medical industry. The main aim of this study is to isolate and characterize the acid solubilize collagen from sardine fish scale, Sardina pilchardus. Experimental design methodology was adopted in collagen processing for extracting optimization. The first stage of this work is to investigate the optimization conditions of the sardine scale deproteinization on using response surface methodology (RSM). The second part focus on the demineralization with HCl solution or EDTA. Moreover, the last one is to establish the optimum condition for the isolation of collagen from fish scale by solvent extraction. The basic principle of RSM is to determinate model equations that describe interrelations between the independent variables and the dependent variables.

Keywords: Sardina pilchardus, scales, valorization, collagen extraction, response surface methodology

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Authors: Antonietta Maoloni, Federica Cardinali, Vesna Milanović, Andrea Osimani, Ilario Ferrocino, Maria Rita Corvaglia, Luca Cocolin, Lucia Aquilanti

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Table olives (Olea europaea L.) are among the most important fermented vegetables all over the world, while sea fennel (Crithmum maritimum L.) is an emerging food crop with interesting nutritional and sensory traits. Both of them are characterized by the presence of several bioactive compounds with potential beneficial health effects, thus representing two valuable substrates for the manufacture of innovative vegetable-based preserves. Given these premises, the present study was aimed at exploring the co-fermentation of table olives and sea fennel to produce new high-value preserves. Spanish style or Greek style processing method and the use of a multiple strain starter were explored. The preserves were evaluated for their microbial dynamics and key sensory traits. During the fermentation, a progressive pH reduction was observed. Mesophilic lactobacilli, mesophilic lactococci, and yeasts were the main microbial groups at the end of the fermentation, whereas Enterobacteriaceae decreased during fermentation. An evolution of the microbiota was revealed by metataxonomic analysis, with Lactiplantibacillus plantarum dominating in the late stage of fermentation, irrespective of processing method and use of the starter. Greek style preserves resulted in more crunchy and less fibrous than Spanish style one and were preferred by trained panelists.

Keywords: lactic acid bacteria, Lactiplantibacillus plantarum, metataxonomy, panel test, rock samphire

Procedia PDF Downloads 124

Authors: Shuangxin Wu

Abstract:

Superalloy ultra-thin-walled components occupy a considerable proportion of aero engines and play an increasingly important role in structural weight reduction and performance improvement. To solve problems such as high deformation resistance and poor formability at room temperature, the introduction of pulse current in the processing process can improve the plasticity of metal materials, but the influence mechanism of pulse current on the forming limit of superalloy ultra-thin sheet is not clear, which is of great significance for determining the material processing window and improving the micro-forming process. The effect of pulse current on the microstructure evolution of superalloy thin plates was observed by optical microscopy (OM) and X-ray diffraction topography (XRT) by applying pulse current to GH3039 with a thickness of 0.2mm under plane strain and uniaxial tensile states. Compared with the specimen without pulse current applied at the same temperature, the internal void volume fraction is significantly reduced, reflecting the non-thermal effect of pulse current on the growth of micro-pores. ED (electrically deforming) specimens have larger and deeper dimples, but the elongation is not significantly improved because the pulse current promotes the void coalescence process, resulting in material fracture. The electro-plastic phenomenon is more obvious in the plane strain state, which is closely related to the effect of stress triaxial degree on the void evolution under pulsed current.

Keywords: pulse current, superalloy, ductile fracture, void damage

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

Abstract:

Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: Ocheme B. Ocheme, Omobolanle O. Oloyede, S. James, Eleojo V. Akpa

Abstract:

The effect of fermentation time on some functional properties of Moringa (Moringa oleifera) seed flour was examined. Fermentation, an effective processing method used to improve nutritional quality of plant foods, tends to affect the characteristics of food components and their behaviour in food systems just like other processing methods. Hence the need for this study. Moringa seeds were fermented naturally by soaking in potable water and allowing it to stand for 12, 24, 48 and 72 hours. At the end of fermentation, the seeds were oven dried at 600C for 12 hours and then milled into flour. Flour obtained from unfermented seeds served as control: hence a total of five flour samples. The functional properties were analyzed using standard methods. Fermentation significantly (p<0.05) increased the water holding capacity of Moringa seed flour from 0.86g/g - 2.31g/g. The highest value was observed after 48 hours of fermentation The same trend was observed for oil absorption capacity with values between 0.87 and 1.91g/g. Flour from unfermented Moringa seeds had a bulk density of 0.60g/cm3 which was significantly (p<0.05) higher than the bulk densities of flours from seeds fermented for 12, 24 and 48. Fermentation significantly (p<0.05) decreased the dispersibility of Moringa seed flours from 36% to 21, 24, 29 and 20% after 12, 24, 48 and 72 hours of fermentation respectively. The flours’ emulsifying capacities increased significantly (p<0.05) with increasing fermentation time with values between 50 – 68%. The flour obtained from seeds fermented for 12 hours had a significantly (p<0.05) higher foaming capacity of 16% while the flour obtained from seeds fermented for 0, 24 and 72 hours had the least foaming capacities of 9%. Flours from seeds fermented for 12 and 48 hours had better functional properties than flours from seeds fermented for 24 and 72 hours.

Keywords: fermentation, flour, functional properties, Moringa

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Authors: Rupali, Anil Kumar Jaiswal

Abstract:

Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model

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Authors: Vadim Kulikov

Abstract:

The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

Procedia PDF Downloads 260