Search results for: Jurassic sequences
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 645

Search results for: Jurassic sequences

285 Chaos Fuzzy Genetic Algorithm

Authors: Mohammad Jalali Varnamkhasti

Abstract:

The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

Procedia PDF Downloads 385
284 Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification

Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

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One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: malware detection, network security, targeted attack, computational intelligence

Procedia PDF Downloads 263
283 Anomaly Detection in a Data Center with a Reconstruction Method Using a Multi-Autoencoders Model

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 194
282 Noninvasive Disease Diagnosis through Breath Analysis Using DNA-functionalized SWNT Sensor Array

Authors: W. J. Zhang, Y. Q. Du, M. L. Wang

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Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancement in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Eight DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, cirrhosis and diabetes. Our tests indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, reproducibility, and repeatability. Furthermore, different molecules can be distinguished through pattern recognition enabled by this sensor array. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or bimolecular detection for the noninvasive diagnostics of diseases and health monitoring.

Keywords: breath analysis, diagnosis, DNA-SWNT sensor array, noninvasive

Procedia PDF Downloads 348
281 Bulk Amounts of Linear and Cyclic Polypeptides on Our Hand within a Short Time

Authors: Yu Zhang, Il Kim

Abstract:

Polypeptides with defined peptide sequences illustrate the power of remarkable applications in drug delivery, tissue engineering, sensing and catalysis. Especially the cyclic polypeptides, the distinctive topological architecture imparts many characteristic properties comparing to linear polypeptides. Here, a facile and highly efficient strategy for the synthesis of linear and cyclic polypeptides is reported using N-heterocyclic carbenes (NHCs)-mediated ring-opening polymerization (ROP) of α-amino acid N-carboxyanhydrides (NCA) in the presence or absence of primary amine initiator. The polymerization proceeds rapidly in a quasi-living manner, allowing access to linear and cyclic polypeptides of well-defined chain length and narrow polydispersity, as evidenced by nuclear magnetic resonance spectrum (1H NMR and 13C NMR spectra) and size exclusion chromatography (SEC) analysis. The cyclic architecture of the polypeptides was further verified by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectra (MALDI-TOF MS) and electrospray ionization (ESI) mass spectra, as well as viscosity studies. This approach can also simplify workup procedures and make bulk scale synthesis possible, which thereby opens avenues for practical uses in diverse areas, opening up the new generation of polypeptide synthesis.

Keywords: α-amino acid N-carboxyanhydrides, living polymerization, polypeptides, N-heterocyclic carbenes, ring-opening polymerization

Procedia PDF Downloads 167
280 Adaptive Analysis of Housing Policies in Development Programming After 1970s (Case Study: Kermanshah City in the Western Iran)

Authors: Zeinab. Shahrokhifar, Abolfazl Meshkini, Seyed Ali. Alavi

Abstract:

Considering the different dimensions of deprivation, housing supply is noted as a basic requirement in Iran after 1979 (coming to work of the new government). The government had built the constitution and obliged to meet this need in the form of five-year development programs in Iran’s provinces. This study focused on the adaptive analysis of housing policies in these five development programs in Kermanshah province located in western Iran. Our research is divided into two different analytical sections. In the first section, we collected the documentary information using approved plans and field studies. In the second section, a questionnaire was prepared and designed for the elite community (30) to support the documentary analysis. The results showed that various projects adopted in the form of strategic plans and implemented the policies included both quantitative and qualitative housing in Kermanshah province after 1979. The quality of housing, from the first to the fifth development plans has improved the situation in the housing indicators. The quantity of housing units for households has also been implemented through various policies that has desired results. The sequences of housing policies and plans do not overlap in the five development programs. According to the radar graph, the development programs overlapped in some policies, which shows the continuation of the previous policies, but this overlap is not perfect.

Keywords: law enforcement policy, housing policy, development programs, housing indicators, the city of Kermanshah

Procedia PDF Downloads 73
279 Antibacterial Activity of Salvadora persica Extracts against Oral Cavity Bacteria

Authors: Sulaiman A. Alrumman, Abd El-Latif Hesham

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Despite medical progress worldwide, dental caries are still widespread. Miswak is derived from the plant arak (Salvadora persica). It is used by Muslim people as a natural product for the cleansing of teeth, to ensure oral and dental hygiene. This study was designed to evaluate the antimicrobial effects of ethanol, methanol, and ethanol/methanol extracts of miswak against three bacterial pathogens of the oral cavity. The pathogens were isolated from the oral cavity of volunteers/patients and were identified on the basis of 16S rRNA gene amplification data. Sequence comparisons were made with 16S rRNA gene sequences available in the GenBank database. The results of sequence alignment and phylogenetic analysis identified the three pathogens as being Staphylococcus aureus strain KKU-020, Enterococcus faecalis strain KKU-021 and Klebsiella pneumoniae strain KKU-022. All miswak extracts showed powerful antimicrobial activity against the three pathogens. The maximum zone of inhibition (40.67±0.88 mm) was observed against E. faecalis with ethanolic extracts whilst methanolic extracts showed the minimum zone of inhibition (10.33±0.88 mm) against K. pneumonia KKU-022. Based on the significant effects of the miswak extracts against the oral cavity pathogens in our study, we recommend that miswak is to be used as a dental hygiene method to prevent tooth caries.

Keywords: antibacterial, miswak, Salvadora persica, oral cavity pathogens

Procedia PDF Downloads 294
278 Particle Filter Supported with the Neural Network for Aircraft Tracking Based on Kernel and Active Contour

Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

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In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: video tracking, particle filter, greedy snake, neural network

Procedia PDF Downloads 342
277 The Ontological Memory in Bergson as a Conceptual Tool for the Analysis of the Digital Conjuncture

Authors: Douglas Rossi Ramos

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The current digital conjuncture, called by some authors as 'Internet of Things' (IoT), 'Web 2.0' or even 'Web 3.0', consists of a network that encompasses any communication of objects and entities, such as data, information, technologies, and people. At this juncture, especially characterized by an "object socialization," communication can no longer be represented as a simple informational flow of messages from a sender, crossing a channel or medium, reaching a receiver. The idea of communication must, therefore, be thought of more broadly in which it is possible to analyze the process communicative from interactions between humans and nonhumans. To think about this complexity, a communicative process that encompasses both humans and other beings or entities communicating (objects and things), it is necessary to constitute a new epistemology of communication to rethink concepts and notions commonly attributed to humans such as 'memory.' This research aims to contribute to this epistemological constitution from the discussion about the notion of memory according to the complex ontology of Henri Bergson. Among the results (the notion of memory in Bergson presents itself as a conceptual tool for the analysis of posthumanism and the anthropomorphic conjuncture of the new advent of digital), there was the need to think about an ontological memory, analyzed as a being itself (being itself of memory), as a strategy for understanding the forms of interaction and communication that constitute the new digital conjuncture, in which communicating beings or entities tend to interact with each other. Rethinking the idea of communication beyond the dimension of transmission in informative sequences paves the way for an ecological perspective of the digital dwelling condition.

Keywords: communication, digital, Henri Bergson, memory

Procedia PDF Downloads 164
276 Bacterial Profiling and Development of Molecular Diagnostic Assays for Detection of Bacterial Pathogens Associated with Bovine mastitis

Authors: Aqeela Ashraf, Muhammad Imran, Tahir Yaqub, Muhammad Tayyab, Yung Fu Chang

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For the identification of bovine mastitic pathogen, an economical, rapid and sensitive molecular diagnostic assay is developed by PCR multiplexing of gene and pathogenic species specific DNA sequences. The multiplex PCR assay is developed for detecting nine important bacterial pathogens causing mastitis Worldwide. The bacterial species selected for this study are Streptococcus agalactiae, Streptococcus dysagalactiae, Streptococcus uberis, Staphylococcus aureus, Escherichia coli, Staphylococcus haemolyticus, Staphylococcus chromogenes Mycoplasma bovis and Staphylococcus epidermidis. A single reaction assay was developed and validated by 27 reference strains and further tested on 276 bacterial strains obtained from culturing mastitic milk. The multiplex PCR assay developed here is further evaluated by applying directly on genomic DNA isolated from 200 mastitic milk samples. It is compared with bacterial culturing method and proved to be more sensitive, rapid, economical and can specifically identify 9 bacterial pathogens in a single reaction. It has detected the pathogens in few culture negative mastitic samples. Recognition of disease is the foundation of disease control and prevention. This assay can be very helpful for maintaining the udder health and milk monitoring.

Keywords: multiplex PCR, bacteria, mastitis, milk

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275 Evaluation and Assessment of Bioinformatics Methods and Their Applications

Authors: Fatemeh Nokhodchi Bonab

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Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

Procedia PDF Downloads 127
274 An Automated Optimal Robotic Assembly Sequence Planning Using Artificial Bee Colony Algorithm

Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta

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Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.

Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates

Procedia PDF Downloads 237
273 Lower Cretaceous Clay in Anti-Lebanon Mountains, Syria and their Importance in Ceramic Manufacturing

Authors: Abdul Salam Turkmani

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The Lower Cretaceous rocks are exposed only in the mountains regions of Syria, such as the Anti- Lebanon mountain on the western side of Damascus. The lower cretaceous sequences are made up of different rocks. The upper and middle parts of the section are composed mainly of carbonate sediments and, less frequently, gypsum and anhydrite. The lower beds are mainly composed of sandstone, conglomerate and clay. Clay samples were collected from the study area, which is located about 45 km west of the city of Damascus, near the border village of Kfer Yabous and to the left of the Damascus -Beirut International Road, within the lower Cretaceous upper Aptian deposits. The properties of clay were carried out by X-ray diffraction (XRD) and, X-ray fluorescence (XRF) and Thermal Analysis (DTA-TG-DSC) techniques. The studied samples of clay were mainly composed of kaolinite, quartz, illite. Chemical analysis shows the content of SiO₂ varied between 46.06 to 73 % Al₂O₃ 14.55-26.56%, about the staining oxides (Fe₂O₃ + TiO₂), the total content is about 4.3 to 12.5%. The physical properties were determined by studying the behavior of the body before and after firing, showed low bending strength values (22.5 kg/cm²) after drying, and (about 247 kg/cm²) after firing at 1180°C, water absorption value was about 10%. The cubic thermal expansion coefficient at 1140°C is 213.77 x 10-7 /°C. All of the presented results confirm the suitability of this clay for the ceramic industry.

Keywords: anti-Lebanon, Damascus, ceramic, clay, thermal analysis, thermal expansion coefficient

Procedia PDF Downloads 187
272 Multi-Stage Multi-Period Production Planning in Wire and Cable Industry

Authors: Mahnaz Hosseinzadeh, Shaghayegh Rezaee Amiri

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This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.

Keywords: goal programming approach, GP, production planning, serial manufacturing process, wire and cable industry

Procedia PDF Downloads 160
271 Quality Service Standard of Food and Beverage Service Staff in Hotel

Authors: Thanasit Suksutdhi

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This survey research aims to study the standard of service quality of food and beverage service staffs in hotel business by studying the service standard of three sample hotels, Siam Kempinski Hotel Bangkok, Four Seasons Resort Chiang Mai, and Banyan Tree Phuket. In order to find the international service standard of food and beverage service, triangular research, i.e. quantitative, qualitative, and survey were employed. In this research, questionnaires and in-depth interview were used for getting the information on the sequences and method of services. There were three parts of modified questionnaires to measure service quality and guest’s satisfaction including service facilities, attentiveness, responsibility, reliability, and circumspection. This study used sample random sampling to derive subjects with the return rate of the questionnaires was 70% or 280. Data were analyzed by SPSS to find arithmetic mean, SD, percentage, and comparison by t-test and One-way ANOVA. The results revealed that the service quality of the three hotels were in the international level which could create high satisfaction to the international customers. Recommendations for research implementations were to maintain the area of good service quality, and to improve some dimensions of service quality such as reliability. Training in service standard, product knowledge, and new technology for employees should be provided. Furthermore, in order to develop the service quality of the industry, training collaboration between hotel organization and educational institutions in food and beverage service should be considered.

Keywords: service standard, food and beverage department, sequence of service, service method

Procedia PDF Downloads 352
270 Real-Time Multi-Vehicle Tracking Application at Intersections Based on Feature Selection in Combination with Color Attribution

Authors: Qiang Zhang, Xiaojian Hu

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In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 163
269 Blood Volume Pulse Extraction for Non-Contact Photoplethysmography Measurement from Facial Images

Authors: Ki Moo Lim, Iman R. Tayibnapis

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According to WHO estimation, 38 out of 56 million (68%) global deaths in 2012, were due to noncommunicable diseases (NCDs). To avert NCD, one of the solutions is early detection of diseases. In order to do that, we developed 'U-Healthcare Mirror', which is able to measure vital sign such as heart rate (HR) and respiration rate without any physical contact and consciousness. To measure HR in the mirror, we utilized digital camera. The camera records red, green, and blue (RGB) discoloration from user's facial image sequences. We extracted blood volume pulse (BVP) from the RGB discoloration because the discoloration of the facial skin is accordance with BVP. We used blind source separation (BSS) to extract BVP from the RGB discoloration and adaptive filters for removing noises. We utilized singular value decomposition (SVD) method to implement the BSS and the adaptive filters. HR was estimated from the obtained BVP. We did experiment for HR measurement by using our method and previous method that used independent component analysis (ICA) method. We compared both of them with HR measurement from commercial oximeter. The experiment was conducted under various distance between 30~110 cm and light intensity between 5~2000 lux. For each condition, we did measurement 7 times. The estimated HR showed 2.25 bpm of mean error and 0.73 of pearson correlation coefficient. The accuracy has improved compared to previous work. The optimal distance between the mirror and user for HR measurement was 50 cm with medium light intensity, around 550 lux.

Keywords: blood volume pulse, heart rate, photoplethysmography, independent component analysis

Procedia PDF Downloads 329
268 Impact of Welding Distortion on the Design of Fabricated T-Girders Using Finite Element Modeling

Authors: Ahmed Hammad, Yehia Abdel-Nasser, Mohamed Shamma

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The main configuration of ship construction consists of standard and fabricated stiffening members which are commonly used in shipbuilding such as fabricated T-sections. During the welding process, the non-uniform heating and rapid cooling lead to the inevitable presence of out-of-plane distortion and welding induced residual stresses. Because of these imperfections, the fabricated structural members may not attain their design load to be carried. The removal of these imperfections will require extra man-hours. In the present work, controlling these imperfections has been investigated at both design and fabrication stages. A typical fabricated T-girder is selected to investigate the problem of these imperfections using double-side welding. A numerical simulation based on finite element (FE) modeling has been used to investigate the effect of different parameters of the selected fabricated T-girder such as geometrical properties and welding sequences on the magnitude of welding imperfections. FE results were compared with the results of experimental model of a double-side fillet weld. The present work concludes that: Firstly, in the design stage, the optimum geometry of the fabricated T- girder is determined based on minimum steel weight and out- of- plane distortion. Secondly, in the fabrication stage, the best welding sequence is determined on the basis of minimum welding out- of- plane distortion.

Keywords: fabricated T-girder, FEM, out-of-plane distortion, section modulus, welding residual stresses

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267 BodeACD: Buffer Overflow Vulnerabilities Detecting Based on Abstract Syntax Tree, Control Flow Graph, and Data Dependency Graph

Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

Abstract:

As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

Procedia PDF Downloads 170
266 Genome Sequencing of Infectious Bronchitis Virus QX-Like Strain Isolated in Malaysia

Authors: M. Suwaibah, S. W. Tan, I. Aiini, K. Yusoff, A. R. Omar

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Respiratory diseases are the most important infectious diseases affecting poultry worldwide. One of the avian respiratory virus of global importance causing significant economic losses is Infectious Bronchitis Virus (IBV). The virus causes a wide spectrum disease known as Infectious Bronchitis (IB), affecting not only the respiratory system but also the kidney and the reproductive system, depending on its strain. IB and Newcastle disease are two of the most prevalent diseases affecting poultry in Malaysia. However, a study on the molecular characterization of Malaysian IBV is lacking. In this study, an IBV strain IBS130 which was isolated in 2015 was fully sequenced using next-gene sequencing approach. Sequence analysis of IBS130 based on the complete genome, polyprotein 1ab and S1 genes were compared with other IBV sequences available in Genbank, National Center for Biotechnology Information (NCBI). IBV strain IBS130 is characterised as QX-like strain based on whole genome and S1 gene sequence analysis. Comparisons of the virus with other IBV strains showed that the nucleotide identity ranged from 67% to 99.2%, depending on the region analysed. The similarity in whole genome nucleotide ranging from 84.9% to 90.7% with the least similar was from Singapore strains (84.9%) and highly similar with China QX-like strains. Meanwhile, the similarity in polyprotein 1ab ranging from 85.3% to 89.9% with the least similar to Singapore strains (85.3%) and highly similar with Mass strains from USA.

Keywords: infectious bronchitis virus, phylogenetic analysis, chicken, Malaysia

Procedia PDF Downloads 187
265 Dynamic Gabor Filter Facial Features-Based Recognition of Emotion in Video Sequences

Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

Procedia PDF Downloads 278
264 Experimental and Computational Analysis of Glass Fiber Reinforced Plastic Beams with Piezoelectric Fibers

Authors: Selin Kunc, Srinivas Koushik Gundimeda, John A. Gallagher, Roselita Fragoudakis

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This study investigates the behavior of Glass Fiber Reinforced Plastic (GFRP) laminated beams additionally reinforced with piezoelectric fibers. The electromechanical behavior of piezoelectric materials coupled with high strength/low weight GFRP laminated beams can have significant application in a wide range of industries. Energy scavenging through mechanical vibrations is the focus of this study, and possible applications can be seen in the automotive industry. This study examines the behavior of such composite laminates using Classical Lamination Theory (CLT) under three-point bending conditions. Fiber orientation is optimized for the desired stiffness and deflection that yield maximum energy output. Finite element models using ABAQUS/CAE are verified through experimental testing. The optimum stacking sequences examined are [0o]s, [ 0/45o]s, and [45/-45o]s. Results show the superiority of the stacking sequence [0/45o]s, providing higher strength at a lower weight, and maximum energy output. Furthermore, laminated GFRP beams additionally reinforced with piezoelectric fibers can be used under bending to not only replace metallic component while providing similar strength at a lower weight but also provide an energy output.

Keywords: classical lamination theory (CLT), energy scavenging, glass fiber reinforced plastics (GFRP), piezoelectric fibers

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263 Signal Amplification Using Graphene Oxide in Label Free Biosensor for Pathogen Detection

Authors: Agampodi Promoda Perera, Yong Shin, Mi Kyoung Park

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The successful detection of pathogenic bacteria in blood provides important information for early detection, diagnosis and the prevention and treatment of infectious diseases. Silicon microring resonators are refractive-index-based optical biosensors that provide highly sensitive, label-free, real-time multiplexed detection of biomolecules. We demonstrate the technique of using GO (graphene oxide) to enhance the signal output of the silicon microring optical sensor. The activated carboxylic groups in GO molecules bind directly to single stranded DNA with an amino modified 5’ end. This conjugation amplifies the shift in resonant wavelength in a real-time manner. We designed a capture probe for strain Staphylococcus aureus of 21 bp and a longer complementary target sequence of 70 bp. The mismatched target sequence we used was of Streptococcus agalactiae of 70 bp. GO is added after the complementary binding of the probe and target. GO conjugates to the unbound single stranded segment of the target and increase the wavelength shift on the silicon microring resonator. Furthermore, our results show that GO could successfully differentiate between the mismatched DNA sequences from the complementary DNA sequence. Therefore, the proposed concept could effectively enhance sensitivity of pathogen detection sensors.

Keywords: label free biosensor, pathogenic bacteria, graphene oxide, diagnosis

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262 Biosensor Design through Molecular Dynamics Simulation

Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

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261 Using Genetic Algorithms to Outline Crop Rotations and a Cropping-System Model

Authors: Nicolae Bold, Daniel Nijloveanu

Abstract:

The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: chromosomes, cropping, genetic algorithm, genes

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260 Development and Characterization of Polymorphic Genomic-SSR Markers in Asian Long-Horned Beetle (Anoplophora glabripennis)

Authors: Zhao Yang Liu, Jing Tao

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The Asian long-horned beetle, Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae: Lamiinae), is a wood-borer and polyphagous xylophages native to Asia and killing healthy trees. As it causes serious danger to trees, the beetle has been paid close attention in the world. However, the genetic markers limited, especially microsatellite. In this study, 24 novel simple sequence repeat (SSR) molecular markers, a powerful tool for genetic diversity studies and linkage map construction, were developed and characterized from whole genome shotgun sequences. We developed SSR loci of 2 to 6 repeated and perfect units including 9895 points, the density of SSRs was found one SSR per 56.57 kb and the abundance of SSR was 0.02/kb, besides 140 types of repeats motifs were found. Half of the 48 pairs SSR primers (containing 4 di-, 7 tri-, 2 tetra- and 11 hexamers SSRs) we selected randomly from 1222 pairs of primers were polymorphism. The number of alleles for these markers in 48 individuals varied from 3 to 21 with an average of 7.71, the number of effective alleles ranged from 1.22 to 9.97 with an average of 3.54. Besides this, the polymorphic information content (PIC) ranged from 0.18 to 0.89 with a mean of 0.65, And Shannon's Information index (I) ranged from 0.46 to 2.62 with an average of 1.44. The results suggest that the method for screening of SSR in the whole genome is feasible and efficient. SSR markers developed in this study can be used for population genetic studies of A. glabripennis. Moreover, they may also be helpful for the development of microsatellites for other Coleoptera.

Keywords: SSR markers, Anoplophora glabripennis, genetic diversity, whole genome

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259 Performance Analysis of 5G for Low Latency Transmission Based on Universal Filtered Multi-Carrier Technique and Interleave Division Multiple Access

Authors: A. Asgharzadeh, M. Maroufi

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5G mobile communication system has drawn more and more attention. The 5G system needs to provide three different types of services, including enhanced Mobile BroadBand (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC). Universal Filtered Multi-Carrier (UFMC), Filter Bank Multicarrier (FBMC), and Filtered Orthogonal Frequency Division Multiplexing (f-OFDM) are suggested as a well-known candidate waveform for the coming 5G system. Themachine-to-machine (M2M) communications are one of the essential applications in 5G, and it involves exchanging of concise messages with a very short latency. However, in UFMC systems, the subcarriers are grouped into subbands but f-OFDM only one subband covers the entire band. Furthermore, in FBMC, a subband includes only one subcarrier, and the number of subbands is the same as the number of subcarriers. This paper mainly discusses the performance of UFMC with different parameters for the UFMC system. Also, paper shows that UFMC is the best choice outperforming OFDM in any case and FBMC in case of very short packets while performing similarly for long sequences with channel estimation techniques for Interleave Division Multiple Access (IDMA) systems.

Keywords: universal filtered multi-carrier technique, UFMC, interleave division multiple access, IDMA, fifth-generation, subband

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258 Computationally Efficient Stacking Sequence Blending for Composite Structures with a Large Number of Design Regions Using Cellular Automata

Authors: Ellen Van Den Oord, Julien Marie Jan Ferdinand Van Campen

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This article introduces a computationally efficient method for stacking sequence blending of composite structures. The computational efficiency makes the presented method especially interesting for composite structures with a large number of design regions. Optimization of composite structures with an unequal load distribution may lead to locally optimized thicknesses and ply orientations that are incompatible with one another. Blending constraints can be enforced to achieve structural continuity. In literature, many methods can be found to implement structural continuity by means of stacking sequence blending in one way or another. The complexity of the problem makes the blending of a structure with a large number of adjacent design regions, and thus stacking sequences, prohibitive. In this work the local stacking sequence optimization is preconditioned using a method found in the literature that couples the mechanical behavior of the laminate, in the form of lamination parameters, to blending constraints, yielding near-optimal easy-to-blend designs. The preconditioned design is then fed to the scheme using cellular automata that have been developed by the authors. The method is applied to the benchmark 18-panel horseshoe blending problem to demonstrate its performance. The computational efficiency of the proposed method makes it especially suited for composite structures with a large number of design regions.

Keywords: composite, blending, optimization, lamination parameters

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257 Temporal Characteristics of Human Perception to Significant Variation of Block Structures

Authors: Kuo-Cheng Liu

Abstract:

In the latest research efforts, the structures of the image in the spatial domain have been successfully analyzed and proved to deduce the visual masking for accurately estimating the visibility thresholds of the image. If the structural properties of the video sequence in the temporal domain are taken into account to estimate the temporal masking, the improvement and enhancement of the as-sessing spatio-temporal visibility thresholds are reasonably expected. In this paper, the temporal characteristics of human perception to the change in block structures on the time axis are analyzed. The temporal characteristics of human perception are represented in terms of the significant variation in block structures for the analysis of human visual system (HVS). Herein, the block structure in each frame is computed by combined the pattern masking and the contrast masking simultaneously. The contrast masking always overestimates the visibility thresholds of edge regions and underestimates that of texture regions, while the pattern masking is weak on a uniform background and is strong on the complex background with spatial patterns. Under considering the significant variation of block structures between successive frames, we extend the block structures of images in the spatial domain to that of video sequences in the temporal domain to analyze the relation between the inter-frame variation of structures and the temporal masking. Meanwhile, the subjective viewing test and the fair rating process are designed to evaluate the consistency of the temporal characteristics with the HVS under a specified viewing condition.

Keywords: temporal characteristic, block structure, pattern masking, contrast masking

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256 Sequence Analysis and Structural Implications of Rotavirus Capsid Proteins

Authors: Nishal Parbhoo, John B. Dewar, Samantha Gildenhuys

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Rotavirus is the major cause of severe gastroenteritis worldwide in children aged 5 and younger. Death rates are high particularly in developing countries. The mature rotavirus is a non-enveloped triple-layered nucleocapsid containing 11 double-stranded RNA segments. Here a global view on the sequence and structure of the three main capsid proteins, VP7, VP6, and VP2 is taken by generating a consensus sequence for each of these rotavirus proteins, for each species obtained from published data of representative rotavirus genotypes from across the world and across species. The degree of conservation between species was represented on homology models for each of the proteins. VP7 shows the highest level of variation with 14 - 45 amino acids showing conservation of less than 60%. These changes are localized to the outer surface which is exposed to antibodies alluding to a possible mechanism in evading the immune system. The middle layer, VP6 shows lower variability with only 14-32 sites having lower than 70% conservation. The inner structural layer made up of VP2 showed the lowest variability with only 1-16 sites having less than 70% conservation across species. The results correlate with proteins’ multiple structural roles. Although the nucleotide sequences vary due to an error-prone replication and lack of proofreading, the corresponding amino acid sequence of VP2, 6 and 7 remains conserved. Sequence conservation maintained for the virus results in stable protein structures, fit for function. This can be exploited in drug design, molecular studies and biotechnological applications.

Keywords: amino acid sequence conservation, capsid protein, protein structure, vaccine candidate

Procedia PDF Downloads 290