Search results for: automatic annotation

Authors: Mahmoud Mohammad Salem Al-Suod, Ushkarenko O. Alexander, Dorogan I. Olga

Abstract:

New algorithms using microprocessor systems have been proposed for protection the diesel-generator unit in autonomous power systems. The software structure is designed to enhance the control automata of the system, in which every protection module of diesel-generator encapsulates the finite state machine.

Keywords: diesel-generator unit, protection, state diagram, control system, algorithm, software components

Procedia PDF Downloads 370

Authors: Jeisson A. Estrella, Laura C. Herrera, Cristian A. Arenas

Abstract:

The Colombian electricity sector has been transforming through the insertion of new energy sources to generate electricity, one of them being solar energy, which is being promoted by companies interested in photovoltaic technology. The study of this technology is important for electricity generation in general and for the planning of the sector from the perspective of energy complementarity. Precisely in this last approach is where the project is located; we are interested in answering the concerns about the reliability of the electrical system when climatic phenomena such as El Niño occur or in defining whether it is viable to replace or expand thermoelectric plants. Reliability of the electrical system when climatic phenomena such as El Niño occur, or to define whether it is viable to replace or expand thermoelectric plants with renewable electricity generation systems. In this regard, some difficulties related to the basic information on renewable energy sources from measured data must first be solved, as these come from automatic weather stations. Basic information on renewable energy sources from measured data, since these come from automatic weather stations administered by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) and, in the range of study (2005-2019), have significant amounts of missing data. For this reason, the overall objective of the project is to complete the global solar irradiance datasets to obtain time series to develop energy complementarity analyses in a subsequent project. Global solar irradiance data sets to obtain time series that will allow the elaboration of energy complementarity analyses in the following project. The filling of the databases will be done through numerical and statistical methods, which are basic techniques for undergraduate students in technical areas who are starting out as researchers technical areas who are starting out as researchers.

Keywords: time series, global solar irradiance, imputed data, energy complementarity

Procedia PDF Downloads 37

Authors: Binh T. T. Nguyen, Zhenyu Li, Eric Yap, Yi Zhang, Ai-Qun Liu

Abstract:

Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection.

Keywords: biotoxin, photonic, ring resonator, sensor

Procedia PDF Downloads 89

Authors: Pengzhou Lu, Liming Xin, Payam Tavakoli, Zhonghua Lin, Roberto V. P. Ribeiro, Mitesh V. Badiwala

Abstract:

Ex vivo Heart Perfusion (EVHP) has been developed as an alternative strategy to expand cardiac donation by enabling resuscitation and functional assessment of hearts donated from marginal donors, which were previously not accepted. EVHP parameters, such as perfusion flow (PF) and perfusion pressure (PP) are crucial for optimal organ preservation. However, with the heart’s constant physiological changes during EVHP, such as coronary vascular resistance, manual control of these parameters is rendered imprecise and cumbersome for the operator. Additionally, low control precision and the long adjusting time may lead to irreversible damage to the myocardial tissue. To solve this problem, an automatic heart perfusion system was developed by applying a Human-Machine Interface (HMI) and a Programmable-Logic-Controller (PLC)-based circuit to control PF and PP. The PLC-based control system collects the data of PF and PP through flow probes and pressure transducers. It has two control modes: the RPM-flow mode and the pressure mode. The RPM-flow control mode is an open-loop system. It influences PF through providing and maintaining the desired speed inputted through the HMI to the centrifugal pump with a maximum error of 20 rpm. The pressure control mode is a closed-loop system where the operator selects a target Mean Arterial Pressure (MAP) to control PP. The inputs of the pressure control mode are the target MAP, received through the HMI, and the real MAP, received from the pressure transducer. A PID algorithm is applied to maintain the real MAP at the target value with a maximum error of 1mmHg. The precision and control speed of the RPM-flow control mode were examined by comparing the PLC-based system to an experienced operator (EO) across seven RPM adjustment ranges (500, 1000, 2000 and random RPM changes; 8 trials per range) tested in a random order. System’s PID algorithm performance in pressure control was assessed during 10 EVHP experiments using porcine hearts. Precision was examined through monitoring the steady-state pressure error throughout perfusion period, and stabilizing speed was tested by performing two MAP adjustment changes (4 trials per change) of 15 and 20mmHg. A total of 56 trials were performed to validate the RPM-flow control mode. Overall, the PLC-based system demonstrated the significantly faster speed than the EO in all trials (PLC 1.21±0.03, EO 3.69±0.23 seconds; p < 0.001) and greater precision to reach the desired RPM (PLC 10±0.7, EO 33±2.7 mean RPM error; p < 0.001). Regarding pressure control, the PLC-based system has the median precision of ±1mmHg error and the median stabilizing times in changing 15 and 20mmHg of MAP are 15 and 19.5 seconds respectively. The novel PLC-based control system was 3 times faster with 60% less error than the EO for RPM-flow control. In pressure control mode, it demonstrates a high precision and fast stabilizing speed. In summary, this novel system successfully controlled perfusion flow and pressure with high precision, stability and a fast response time through a user-friendly interface. This design may provide a viable technique for future development of novel heart preservation and assessment strategies during EVHP.

Keywords: automatic control system, biomedical engineering, ex-vivo heart perfusion, human-machine interface, programmable logic controller

Procedia PDF Downloads 143

Authors: Haroon Jan Khan, Xian-Feng Xu, Syed Nasir Shah, Anooshay Niazi

Abstract:

CNC machines are not only used on a large scale but also now become a prominent necessity among households and smaller businesses. Printed Circuit Boards manufactured by the chemical process are not only risky and unsafe but also expensive and time-consuming. A 3-axis precise CNC machine has been developed, which not only fabricates PCB but has also been used for multi-tasks just by changing the materials used and tools, making it versatile. The advanced CNC machine takes data from CAM software. The TB-6560 controller is used in the CNC machine to adjust variation in the X, Y, and Z axes. The advanced machine is efficient in automatic drilling, engraving, and cutting.

Keywords: CNC, G-code, CAD, CAM, Proteus, FLATCAM, Easel

Procedia PDF Downloads 125

Authors: Georgios Alexandropoulos

Abstract:

The purpose of this study is to examine the historical text of Alexiad by Anna Comnena using computational tools for the extraction of lexical bundles containing the name of her father, Alexius Comnenus. For this reason, in this research we apply corpus linguistics techniques for the automatic extraction of lexical bundles and through them we will draw conclusions about how these lexical bundles serve her support provided to her father.

Keywords: lexical bundles, computational literature, critical discourse analysis, Alexiad

Procedia PDF Downloads 595

Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

Abstract:

The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

Procedia PDF Downloads 375

Authors: Xuewei Li, Jingfeng Yuan, Jianliang Zhou

Abstract:

The 21st century has been called the century of human exploitation of underground space. Due to the characteristics of large quantity, tight schedule, low safety reserve and high uncertainty of deep foundation pit engineering, accidents frequently occur in deep foundation pit engineering, causing huge economic losses and casualties. With the successful application of information technology in the construction industry, building information modeling has become a research hotspot in the field of architectural engineering. Therefore, the application of building information modeling (BIM) and other information communication technologies (ICTs) in construction safety management is of great significance to improve the level of safety management. This research summed up the mechanism of the deep foundation pit engineering accident through the fault tree analysis to find the control factors of deep foundation pit engineering safety management, the deficiency existing in the traditional deep foundation pit construction site safety management. According to the accident cause mechanism and the specific process of deep foundation pit construction, the hazard information of deep foundation pit engineering construction site was identified, and the hazard list was obtained, including early warning information. After that, the system framework was constructed by analyzing the early warning information demand and early warning function demand of the safety management system of deep foundation pit. Finally, the safety management system of deep foundation pit construction site based on BIM through combing the database and Web-BIM technology was developed, so as to realize the three functions of real-time positioning of construction site personnel, automatic warning of entering a dangerous area, real-time monitoring of deep foundation pit structure deformation and automatic warning. This study can initially improve the current situation of safety management in the construction site of deep foundation pit. Additionally, the active control before the occurrence of deep foundation pit accidents and the whole process dynamic control in the construction process can be realized so as to prevent and control the occurrence of safety accidents in the construction of deep foundation pit engineering.

Keywords: Web-BIM, safety management, deep foundation pit, construction

Procedia PDF Downloads 119

Authors: Harold P. Villota, Alejandro Osorio B.

Abstract:

The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

Procedia PDF Downloads 134

Authors: Zhehao Zhang

Abstract:

Walking has become an indispensable and sustainable way of travel for college students in their daily lives; campus street is an important carrier for students to walk and take part in a variety of activities, improving the walkability of campus streets plays an important role in optimizing the quality of campus space environment, promoting the campus walking system and inducing multiple walking behaviors. The purpose of this paper is to explore the effect of campus layout, facility distribution, and location site selection on the walkability of campus streets, and assess the street design qualities from the elements of imageability, enclosure, complexity, transparency, and human scale, and further examines the relationship between street-level urban design perceptual qualities and walkability and its effect on walking behavior in the campus. Taking Tianjin University as the research object, this paper uses the optimized walk score method based on walking frequency, variety, and distance to evaluate the walkability of streets from a macro perspective and measures the urban design qualities in terms of the calculation of street physical environment characteristics, as well as uses behavior annotation and street image data to establish temporal and spatial behavior database to analyze walking activity from the microscopic view. In addition, based on the conclusions, the improvement and design strategy will be presented from the aspects of the built walking environment, street vitality, and walking behavior.

Keywords: walkability, streetscapes, pedestrian activity, walk score

Procedia PDF Downloads 115

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

Abstract:

This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

Procedia PDF Downloads 142

Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

Abstract:

The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

Procedia PDF Downloads 169

Authors: Amy Lebar, Kim L. Trenbath, Bennett Doherty, William Livingood

Abstract:

Plug and process loads (PPLs) account for 47% of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering and data storage. A laboratory proof of concept (PoC) demonstrated all but the data storage capabilities and these capabilities were validated using an office building scenario. The PoC can identify when a device is plugged into an outlet and the location of the device in the building. When a device is moved, the PoC’s dashboard and database are automatically updated with the new location. The PoC implements controls to devices from the system dashboard so that devices maintain correct schedules regardless of where they are plugged in within a building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. A system like ATLIS could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

Keywords: commercial buildings, grid-interactive efficient buildings (GEB), miscellaneous electric loads (MELs), plug loads, plug load management (PLM)

Procedia PDF Downloads 111

Authors: Dar-Bin Shieh, Gwo-Bin Lee, Chen-Ming Chang, Chen Sheng Yeh, Chih-Chia Huang, Tsung-Ju Li

Abstract:

Mitochondrial defects have a significant impact in many human diseases and aging associated phenotypes. The pathogenic mitochondrial DNA (mtDNA) mutations are diverse and usually present as heteroplasmic. mtDNA 4977bps deletion is one of the common mtDNA defects, and the ratio of mutated versus normal copy is significantly associated with clinical symptoms thus their quantitative detection has become an important unmet needs for advanced disease diagnosis and therapeutic guidelines. This study revealed a Micro-electro-mechanical-system (MEMS) enabled automatic microfluidic chip that only required minimal sample. The system integrated multiple laboratory operation steps into a Lab-on-a-Chip for high-sensitive and prompt measurement. The entire process including magnetic nanoparticle based mtDNA extraction in chip, mutation selective photonic DNA cleavage, and nanoparticle accelerated photonic quantitative polymerase chain reaction (qPCR). All subsystems were packed inside a miniature three-dimensional micro structured system and operated in an automatic manner. Integration of magnetic beads with microfluidic transportation could promptly extract and enrich the specific mtDNA. The near infrared responsive magnetic nanoparticles enabled micro-PCR to be operated by pulse-width-modulation controlled laser pulsing to amplify the desired mtDNA while quantified by fluorescence intensity captured by a complementary metal oxide system array detector. The proportions of pathogenic mtDNA in total DNA were thus obtained. Micro capillary electrophoresis module was used to analyze the amplicone products. In conclusion, this study demonstrated a new magnetophotonic based qPCR MEMS system that successfully detects and quantify specific disease related DNA mutations thus provides a promising future for rapid diagnosis of mitochondria diseases.

Keywords: mitochondrial DNA, micro-electro-mechanical-system, magnetophotonics, PCR

Procedia PDF Downloads 193

Authors: Manpreet Kaur, Cheol-Hong Min

Abstract:

The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

Procedia PDF Downloads 204

Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

Abstract:

Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

Procedia PDF Downloads 549

Authors: Marwa T. Badawy, Alaa F. Bakr, Nesrine Hegazi, Mohamed A. Farag, Ahmed Abdellatif

Abstract:

Diabetes Mellitus (DM) is a chronic disease affecting a large population worldwide. Africa is rich in native medicinal plants with myriad health benefits, though less explored towards the development of specific drug therapy as in diabetes. This study aims to determine the in vivo antidiabetic potential of the well-reported and traditionally used fruits of Baobab (Adansonia digitata L.) using STZ induced diabetic model. The in-vitro cytotoxic and antioxidant properties were examined using MTT assay on L-929 fibroblast cells and DPPH antioxidant assays, respectively. The extract showed minimal cytotoxicity with an IC50 value of 105.7 µg/mL. Histopathological and immunohistochemical investigations showed the hepatoprotective and the renoprotective effects of A. digitata fruits’ extract, implying its protective effects against diabetes complications. These findings were further supported by biochemical assays, which showed that i.p., injection of a low dose (150 mg/kg) of A. digitata twice a week lowered the fasting blood glucose levels, lipid profile, hepatic and renal markers. For a comprehensive overview of extract metabolites composition, ultrahigh performance (UHPLC) analysis coupled to high-resolution tandem mass spectrometry (HRMS/MS) in synchronization with molecular networks led to the annotation of 77 metabolites, among which 50% are reported for the first time in A. digitata fruits.

Keywords: adansonia digital, diabetes mellitus, metabolomics, streptozotocin, Sprague, dawley rats

Procedia PDF Downloads 132

Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

Abstract:

Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

Procedia PDF Downloads 487

Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

Abstract:

In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: fuzzy logic, paraconsistent annotated logic, level control, digital PID

Procedia PDF Downloads 257

Authors: Zeeshan Khan, Faisal Nouroz, Shumaila Noureen

Abstract:

European or common rabbit (Oryctolagus cuniculus) belongs to class Mammalia, order Lagomorpha of family Leporidae. They are distributed worldwide and are native to Europe (France, Spain and Portugal) and Africa (Morocco and Algeria). LTR retrotransposons are major Class I mobile genetic elements of eukaryotic genomes and play a crucial role in genome expansion, evolution and diversification. They were mostly annotated in various genomes by conventional approaches of homology searches, which restricted the annotation of novel elements. Present work involved de novo identification of LTR retrotransposons by LTR_FINDER in haploid genome of rabbit (2247.74 Mb) distributed in 22 chromosomes, of which 7,933 putative full-length or partial copies were identified containing 69.38 Mb of elements, accounting 3.08% of the genome. Highest copy numbers (731) were found on chromosome 7, followed by chromosome 12 (705), while the lowest copy numbers (27) were detected in chromosome 19 with no elements identified from chromosome 21 due to partially sequenced chromosome, unidentified nucleotides (N) and repeated simple sequence repeats (SSRs). The identified elements ranged in sizes from 1.2 - 25.8 Kb with average sizes between 2-10 Kb. Highest percentage (4.77%) of elements was found in chromosome 15, while lowest (0.55%) in chromosome 19. The most frequent tRNA type was Arginine present in majority of the elements. Based on gained results, it was estimated that rabbit exhibits 15,866 copies having 137.73 Mb of elements accounting 6.16% of diploid genome (44 chromosomes). Further molecular analyses will be helpful in chromosomal localization and distribution of these elements on chromosomes.

Keywords: rabbit, LTR retrotransposons, genome, chromosome

Procedia PDF Downloads 120

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

Abstract:

In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

Procedia PDF Downloads 31

Authors: Alicia C. Sanchez

Abstract:

This paper investigates the implementation of RAFU functions (radical functions) in robotics and automation. Specifically, the main goal is to show how these functions may be useful in lane-keeping control and the lateral control of autonomous machines, vehicles, robots or the like. From the knowledge of several points of a certain route, the RAFU functions are used to achieve the lateral control purpose and maintain the lane-keeping errors within the fixed limits. The stability that these functions provide, their ease of approaching any continuous trajectory and the control of the possible error made on the approximation may be useful in practice.

Keywords: automatic navigation control, lateral control, lane-keeping control, RAFU approximation

Procedia PDF Downloads 252

Authors: Jay Xiong, Li Lin

Abstract:

Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

Procedia PDF Downloads 372

Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

Abstract:

Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

Procedia PDF Downloads 107

Authors: Ahmet Karagoz, Irfan Karagoz

Abstract:

Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

Procedia PDF Downloads 340

Authors: Walter E. Allen, Robert D. Murray

Abstract:

Many large transit agencies have adopted RFID technology and electronic automatic fare collection (AFC) or smart card systems, but small and rural agencies remain tied to obsolete manual, cash-based fare collection. Small countries or transit agencies can benefit from the implementation of smart card AFC technology with the promise of increased passenger convenience, added passenger satisfaction and improved agency efficiency. For transit agencies, it reduces revenue loss, improves passenger flow and bus stop data. For countries, further implementation into security, distribution of social services or currency transactions can provide greater benefits. However, small countries or transit agencies cannot afford expensive proprietary smart card solutions typically offered by the major system suppliers. Deployment of Contactless Fare Media System (CFMS) Standard eliminates the proprietary solution, ultimately lowering the cost of implementation. Acumen Building Enterprise, Inc. chose the Yuma County Intergovernmental Public Transportation Authority (YCIPTA) existing proprietary YCAT smart card system to implement CFMS. The revised system enables the purchase of fare product online with prepaid debit or credit cards using the Payment Gateway Processor. Open and interoperable smart card standards for transit have been developed. During the 90-day Pilot Operation conducted, the transit agency gathered the data from the bus AcuFare 200 Card Reader, loads (copies) the data to a USB Thumb Drive and uploads the data to the Acumen Host Processing Center for consolidation of the data into the transit agency master data file. The transition from the existing proprietary smart card data format to the new CFMS smart card data format was transparent to the transit agency cardholders. It was proven that open standards and interoperability design can work and reduce both implementation and operational costs for small transit agencies or countries looking to expand smart card technology. Acumen was able to avoid the implementation of the Payment Card Industry (PCI) Data Security Standards (DSS) which is expensive to develop and costly to operate on a continuing basis. Due to the substantial additional complexities of implementation and the variety of options presented to the transit agency cardholder, Acumen chose to implement only the Directed Autoload. To improve the implementation efficiency and the results for a similar undertaking, it should be considered that some passengers lack credit cards and are averse to technology. There are more than 1,300 small and rural agencies in the United States. This grows by 10 fold when considering small countries or rural locations throughout Latin American and the world. Acumen is evaluating additional countries, sites or transit agency that can benefit from the smart card systems. Frequently, payment card systems require extensive security procedures for implementation. The Project demonstrated the ability to purchase fare value, rides and passes with credit cards on the internet at a reasonable cost without highly complex security requirements.

Keywords: automatic fare collection, near field communication, small transit agencies, smart cards

Procedia PDF Downloads 253

Authors: R. L. Ujjwal, Abhishek Jain

Abstract:

In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

Procedia PDF Downloads 331

Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong

Abstract:

Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.

Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga

Procedia PDF Downloads 487

Authors: Chitaranjan Sharma

Abstract:

The present paper deals with the analysis of a fuel supply system in an automobile engine of a four wheeler which is having both the option of fuel i.e. PETROL and CNG. Since CNG is cheaper than petrol so the priority is given to consume CNG as compared to petrol. An automatic switch is used to start petrol supply at the time of failure of CNG supply. Using regenerative point technique with Markov renewal process, the reliability characteristics which are useful to system designers are obtained.

Keywords: reliability, redundancy, repair time, transition, probability, regenerative points, markov renewal, process

Procedia PDF Downloads 520

Authors: Z. Nougrara, J. Meunier

Abstract:

In this paper, we present a new approach for extracting roads, there road network and its nodes from satellite image representing regions in Algeria. Our approach is related to our previous research work. It is founded on the information theory and the mathematical morphology. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. The main interest of this study is to solve the problem of the automatic mapping from satellite images. This study is thus applied for that the geographical representation of the images is as near as possible to the reality.

Keywords: nodes, road network, satellite image, updating a road map

Procedia PDF Downloads 394