Search results for: automated feeding
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1475

Search results for: automated feeding

665 Multi-Agent System for Irrigation Using Fuzzy Logic Algorithm and Open Platform Communication Data Access

Authors: T. Wanyama, B. Far

Abstract:

Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

Procedia PDF Downloads 290
664 Distributed Processing for Content Based Lecture Video Retrieval on Hadoop Framework

Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

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There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

Procedia PDF Downloads 523
663 Intelligent System and Renewable Energy: A Farming Platform in Precision Agriculture

Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

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This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: fuzzy logic, intelligent system, precision agriculture, renewable energy

Procedia PDF Downloads 124
662 Development of K-Factor for Road Geometric Design: A Case Study of North Coast Road in Java

Authors: Edwin Hidayat, Redi Yulianto, Disi Hanafiah

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On the one hand, parameters which are used for determining the number of lane on the new road construction are average annual average daily traffic (AADT) and peak hour factor (K-factor). On the other hand, the value of K-factor listed in the guidelines and manual for road planning in Indonesia is a value of adoption or adaptation from foreign guidelines or manuals. Thus, the value is less suitable for Indonesian condition due to differences in road conditions, vehicle type, and driving behavior. The purpose of this study is to provide an example on how to determine k-factor values at a road segment with particular conditions in north coast road, West Java. The methodology is started with collecting traffic volume data for 24 hours over 365 days using PLATO (Automated Traffic Counter) with the approach of video image processing. Then, the traffic volume data is divided into per hour and analyzed by comparing the peak traffic volume in the 30th hour (or other) with the AADT in the same year. The analysis has resulted that for the 30th peak hour the K-factor is 0.97. This value can be used for planning road geometry or evaluating the road capacity performance for the 4/2D interurban road.

Keywords: road geometry, K-factor, annual average daily traffic, north coast road

Procedia PDF Downloads 155
661 Impact of Some Experimental Procedures on Behavioral Patterns and Physiological Traits of Rats

Authors: Amira, A. Goma, U. E. Mahrous

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Welfare may be considered to be a subjective experience; it has a biological function that is related to the fitness and survival of the animal accordingly, researches have suggested that welfare is compromised when the animal's evolutionary fitness is reduced. This study was carried out to explain the effect of some managerial stressors as handling and restraint on behavioral patterns and biochemical parameters of rats. A total of 24 (12 males and 12 females) Sprague-Dawley rats (12 months and 150-180g) were allotted into 3 groups, handled group (4 male and 4 female), restrained group (4 male and 4 female) and control group (4 males and 4 females). The obtained results revealed that time spent feeding, drinking frequency, movement and cage exploration increased significantly in handled rats than other groups, while lying time and licking increased significantly in restrained rats than handled and controls. Moreover, social behavior decreased in both stressed groups than control. Triglycerides were significantly increased in handled rats than other groups, while total lipid, total protein and globulin significantly increased in both treated groups than control. Corticosterone increased in restrained and handled rats than control ones. Moreover, there was an increment in packed cell volume significantly in restrained rats than others. These deducted that if we want to study the effect of stress on animal welfare it is necessary to study the effect of such stressors on animal’s behavior and physiological responses.

Keywords: handling, restraint, welfare, rat, behavior, physiology

Procedia PDF Downloads 446
660 Validation of Visibility Data from Road Weather Information Systems by Comparing Three Data Resources: Case Study in Ohio

Authors: Fan Ye

Abstract:

Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

Procedia PDF Downloads 242
659 Machine Learning Approach for Mutation Testing

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 194
658 Tibyan Automated Arabic Correction Using Machine-Learning in Detecting Syntactical Mistakes

Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic language acquisition and learning, natural language processing, morphological analyzer, part-of-speech

Procedia PDF Downloads 146
657 CSRFDtool: Automated Detection and Prevention of a Reflected Cross-Site Request Forgery

Authors: Alaa A. Almarzuki, Nora A. Farraj, Aisha M. Alshiky, Omar A. Batarfi

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The number of internet users is dramatically increased every year. Most of these users are exposed to the dangers of attackers in one way or another. The reason for this lies in the presence of many weaknesses that are not known for native users. In addition, the lack of user awareness is considered as the main reason for falling into the attackers’ snares. Cross Site Request Forgery (CSRF) has placed in the list of the most dangerous threats to security in OWASP Top Ten for 2013. CSRF is an attack that forces the user’s browser to send or perform unwanted request or action without user awareness by exploiting a valid session between the browser and the server. When CSRF attack successes, it leads to many bad consequences. An attacker may reach private and personal information and modify it. This paper aims to detect and prevent a specific type of CSRF, called reflected CSRF. In a reflected CSRF, a malicious code could be injected by the attackers. This paper explores how CSRF Detection Extension prevents the reflected CSRF by checking browser specific information. Our evaluation shows that the proposed solution succeeds in preventing this type of attack.

Keywords: CSRF, CSRF detection extension, attackers, attacks

Procedia PDF Downloads 410
656 Effect of Sowing Dates on Incidence of Sorghum Head Bug Eurystylus Sp (Hemiptera; Miridae) at Rainfed Sector, Blue Nile State, Sudan

Authors: Eisa Y. Adam, Anas A. Fadlelmula, Ali E. Ali

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Sorghum head bug is a key insect pest of sorghum, and it is important to pay attention to the peak time of the pest abundance. The objective of this study was to study the effect of planting date on head bugs population. Field experiment was conducted during 2007/08 – 2008/09 and 2013/14 - 2014/15 cropping seasons at the Damazine Research Station Farm, Blue Nile State to determine sorghum head bugs incidence and abundance through the sowing date. Different sowing dates (early, mid and late sowing) and a susceptible sorghum variety known as Wad Ahmed variety were used the experiment. The experimental design used was randomized complete block design (RCBD). Data were collected on the number of head bug adults and nymphs/panicle, damage percent, coloration and a puncture due to bug feeding and oviposition, 1000 seeds weight and yield. The results showed that significantly (P<0.05) higher number of bugs and damage percent were recorded on the late sowing date for the four seasons followed by the mid sowing, while the early sowing gave low number of bugs, damage percent and high1000 weight. There were significant differences between protected and unprotected heads. The late sowing (August) is a critical sorghum planting time because it coincided with highest numbers of the head bugs.

Keywords: abundance, damage, headbugs, panicle

Procedia PDF Downloads 258
655 A Research Using Remote Monitoring Technology for Pump Output Monitoring in Distributed Fuel Stations in Nigeria

Authors: Ofoegbu Ositadinma Edward

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This research paper discusses a web based monitoring system that enables effective monitoring of fuel pump output and sales volume from distributed fuel stations under the domain of a single company/organization. The traditional method of operation by these organizations in Nigeria is non-automated and accounting for dispensed product is usually approximated and manual as there is little or no technology implemented to presently provide information relating to the state of affairs in the station both to on-ground staff and to supervisory staff that are not physically present in the station. This results in unaccountable losses in product and revenue as well as slow decision making. Remote monitoring technology as a vast research field with numerous application areas incorporating various data collation techniques and sensor networks can be applied to provide information relating to fuel pump status in distributed fuel stations reliably. Thus, the proposed system relies upon a microcontroller, keypad and pump to demonstrate the traditional fuel dispenser. A web-enabled PC with an accompanying graphic user interface (GUI) was designed using virtual basic which is connected to the microcontroller via the serial port which is to provide the web implementation.

Keywords: fuel pump, microcontroller, GUI, web

Procedia PDF Downloads 428
654 Fermented Unripe Plantain (Musa paradisiacal) Peel Meal as a Replacement for Maize in the Diet of Nile Tilapia (Oreochromis niloticus) Fingerlings

Authors: N. A. Bamidele, S. O. Obasa, I. O. Taiwo, I. Abdulraheem, O. C. Odebiyi, A. A. Adeoye, O. E. Babalola, O. V. Uzamere

Abstract:

A feeding trial was conducted to investigate the effect of fermented unripe plantain peel meal (FUP) on growth performance, nutrients digestibility and economic indices of production of Nile tilapia, Oreochromis niloticus fingerlings. Fingerlings (150) of Nile tilapia (1.70±0.1g) were stocked at 10 per plastic tank. Five iso-nitrogenous diets containing 40% crude protein in which maize meal was replaced by fermented unripe plantain peel meal at 0% (FUP0), 25% (FUP25), 50% (FUP50), 75% (FUP75) and 100% (FUP100) were formulated and prepared. The fingerlings were fed at 5% body weight per day for 56 days. There was no significant difference (p > 0.05) in all the growth parameters among the treatments. Feed conversion ratio of 1.35 in fish fed diet FUP25 was not significantly different (P > 0.05) from 1.42 of fish fed diet FUP0. Apparent protein digestibility of 86.94% in fish fed diet FUP100 was significantly higher (p < 0.05) than 70.37% in fish fed diet FUP0 while apparent carbohydrate of 88.34% in fish fed diet FUP0 was significantly different (p < 0.05) from 70.29% of FUP100. Red blood cell (4.30 ml/mm3) of fish fed diet FUP100 was not significantly different from 4.13 ml/mm3 of fish fed diet FUP50. The highest percentage profit of 88.85% in fish fed diet FUP100 was significantly higher than 66.68% in fish fed diet FUP0 while the profit index of 1.89 in fish fed diet FUP100 was significantly different from 1.67 in fish fed diet FUP0. Therefore, fermented unripe plantain peel meal can completely replace maize in the diet of O. niloticus fingerlings.

Keywords: fermentation, fish diets, plantain peel, tilapia

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653 Nutritive Value of Three-Stage Olive Cake (Olea europaea L.) for Growing Rabbit

Authors: Zahia Dorbane, Si Ammar Kadi, Dalila Boudouma, Thierry Gidenne

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In rabbits feeding, minimum fibre intake is essential to avoid digestive disorders. However, this concentration of fibre is not easy to obtain when formulating feeds, without reduction of nutritional value. Three stage olive cake, the residual material after oil extraction by centrifugation, including pulp and stones, can be used as a fibre source in rabbit diet. The incorporation of olive cake can allow a better balance between different fibre fractions and reduce health disorder. However, for practical use of any raw material, it is necessary to know its chemical and nutritive value. The aim of this study was to assess the nutritive value of three-stage olive cake (TSOC) for growing rabbits. Thus, 36 rabbits weaned at 35 days (702.8 ± 28.5) were divided into three groups of 12 receiving one of the following diets: control with 0% of TSOC, TSOC10 (10% of TSOC) and TSOC20 (20% TSOC). The rabbits were individually housed in digestibility cages and received ad libitum one of the three diets, fresh and clean water was provided ad libitum. After an adaptation period of 7d, feces were collected for 4d. Collected feces were frozen and stored for further analysis. The chemical composition of TSOC shows that it is a rich fiber raw material since it contains (%DM): 6% of CP; 7.4% of EE; 78.7% of NDF; 55.4% of ADF and 24.3% of ADL. The inclusion of TSOC at 20% of basal diet reduced the digestibility coefficient of organic matter, crude protein and NDF from 67.8 to 55.3%, 80.4 to 75.3% and from 31.5 to 18.4% (p < 0.001) respectively. The digestible energy and digestible protein content of the three-stage olive cake estimated by regression was 2.94 ± 0.52MJ DE/kg DM and 22.4 ± 6 g DP/kg DM respectively. In conclusion, based on the results of the present experiment, the three-stage olive cake can be used as a fibre source for rabbit.

Keywords: digestibility, nutritive value, olive cake, rabbit

Procedia PDF Downloads 149
652 Assembly Solution for Modular Buildings: Development of a Plug-In Self-Locking Device Designed for Light-Framed Structures

Authors: Laurence Picard, André Bégin-Drolet, Pierre Blanchet

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The prefabricated construction industry has been operating in North America for several years now and differs from traditional construction by its much shorter project timelines, lower costs, and increased build quality. Faced with the global housing crisis, prefabrication should be the first choice for erecting buildings quickly and at a low cost. However, the reality is quite different; manufacturers focus their operations mainly on single-home construction. This is explained by the lack of a suitable and efficient assembly solution for erecting large-scale buildings. Indeed, it is difficult to maintain the coveted advantages of prefabrication with a laborious on-site assembly and a colossal load of additional operations such as the installation of fasteners and the internal finishing. In the desire to maximize the benefits of prefabrication and make it a smart choice even for large buildings, an automated connection solution is developed. The plug-in self-locking device was developed accordingly to the product design phases: on-site observations, the definition of the problem and product requirements, solution generation, prototyping, fabricating and testing.

Keywords: assembly solution, automation, construction productivity, modular connection, modular buildings, plug-in device, self-lock mechanism

Procedia PDF Downloads 163
651 Image Segmentation with Deep Learning of Prostate Cancer Bone Metastases on Computed Tomography

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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650 User-Friendly Task Creation Using a CAD Integrated Robotic System on a Real Workcell

Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz

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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.

Keywords: robotic, automated, production, offline programming, CAD

Procedia PDF Downloads 382
649 Convolutional Neural Network and LSTM Applied to Abnormal Behaviour Detection from Highway Footage

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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648 Effect of Peganum harmala Seeds on Blood Factors, Immune Response and Intestinal Selected Bacterial Population in Broiler Chickens

Authors: Majid Goudarzi

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This experiment was designed to study the effects of feeding different levels of Peganum harmala seeds (PHS) and antibiotic on serum biochemical parameters, immune response and intestinal microflora composition in Ross broiler chickens. A total of 240 one-d-old unsexed broiler chickens were randomly allocated to each of the four treatment groups, each with four replicate pens of 15 chicks. The dietary treatments included of control (C) - without PHS and antibiotic - the diet contains 300 mg/kg Lincomycin 0.88% (A) and the diets contain 2 g/kg (H1) and 4 g/kg (H2) PHS. The chicks were raised on floor pens and received diets and water ad libitum for six weeks. Blood samplings were performed for the determination of antibody titer against Newcastle disease on 14 and 21 days and for biochemical parameters on 42 days of age. The populations of Lactobacilli spp. and Escherichia coli were enumerated in ileum by conventional microbiological techniques using selective agar media. Inclusion of PHS in diet resulted in a significant decrease in total cholesterol and significant increase in HDL relative to the control and antibiotic groups. Antibody titer against NDV was not affected by experimental treatments. E. coli population in birds supplemented with antibiotic and PHS was significantly lower than control, but Lactobacilli spp. population increased only by antibiotic and not by PHS. In conclusion, the results of this study showed that addition of PHS powder seem to have a positive influence on some biochemical parameters and gastrointestinal microflora.

Keywords: antibiotic, biochemical parameters, immune system, Peganum harmala

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647 Composition and Acaricidal Activity of Elettaria cardamomum Essential Oil Against Oligonychus afrasiaticus

Authors: Abid Hussain, Muhammad Rizwan-ul-Haq, Hassan Al-Ayedh, Ahmed M. Al-Jabr

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Oligonychus afrasiaticus, is an important pest that devastates date palms (Phoenix dactylifera). They caused serious damage to date palm fruits. They start feeding on dates at Kimri stage (greenish color dates with high sugar and moisture level) resulting severe fruit losses and rendering them unfit for human consumption. Currently, acaricides are the only tool available to Saudi growers to prevent O. afrasiaticus damage. Many acaricides are available in the Saudi markets in order to control the mites on date palm trees but their efficacy against O. afrasiaticus is questionable. The intensive use of acaricides has led to resistance in many mite species around the globe and their control becomes exceedingly challenging. The current investigation explored for the first time the acaricidal potential of Elettaria cardamomum essential oil for the environmentally safe management of date mites in the laboratory. E. cardamomum exhibited acaricidal activities in a dose dependent manner. GC-MS fractionation of E. cardamomum detected numerous compounds. Among the identified compounds, Guaniol caused 100% mortality compared to other identified compounds including (+)-α-Pinene, Camphene, (-)-B-Pinene, 3-Carene, (R)-(+)-Limonene, and Citral. Our laboratory results showed that E. cardamomum and its constituents especially Guaniol are promising for the eco-friendly management of date mites, O. afrasiaticus, although their field efficacy remains to be evaluated.

Keywords: cardamom, old world date mite, natural acaricide, toxicity

Procedia PDF Downloads 308
646 Analysis of the AZF Region in Slovak Men with Azoospermia

Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

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Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome

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645 Automatic Music Score Recognition System Using Digital Image Processing

Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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644 Covid-19, Diagnosis with Computed Tomography and Artificial Intelligence, in a Few Simple Words

Authors: Angelis P. Barlampas

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Target: The (SARS-CoV-2) is still a threat. AI software could be useful, categorizing the disease into different severities and indicate the extent of the lesions. Materials and methods: AI is a new revolutionary technique, which uses powered computerized systems, to do what a human being does more rapidly, more easily, as accurate and diagnostically safe as the original medical report and, in certain circumstances, even better, saving time and helping the health system to overcome problems, such as work overload and human fatigue. Results: It will be given an effort to describe to the inexperienced reader (see figures), as simple as possible, how an artificial intelligence system diagnoses computed tomography pictures. First, the computerized machine learns the physiologic motives of lung parenchyma by being feeded with normal structured images of the lung tissue. Having being used to recognizing normal structures, it can then easily indentify the pathologic ones, as their images do not fit to known normal picture motives. It is the same way as when someone spends his free time in reading magazines with quizzes, such as <> and <>. General conclusion: The AI mimics the physiological processes of the human mind, but it does that more efficiently and rapidly and provides results in a few seconds, whereas an experienced radiologist needs many days to do that, or even worse, he is unable to accomplish such a huge task.

Keywords: covid-19, artificial intelligence, automated imaging, CT, chest imaging

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643 Estimation of Serum Levels of Calcium and Inorganic Phosphorus in Breast Cancer Patients

Authors: Safa Safdar

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Breast cancer is a type of cancer which is developed by the formation of a tumor on the breast. This tumor invades and causes different electrolyte imbalance. The present study was designed to measure the serum calcium and inorganic phosphorous levels and to check the frequency of hypercalcemia and hypophosphatemia in breast cancer patients. Serum calcium and phosphorous levels of fifty breast cancer women of 18-70 years of age group and fifty healthy women of same age group were measured by using semi-automated chemistry analyzer ( Humalyzer 3000, Human, Germany ). Significant variation in these levels was observed. The mean calcium value in BC patients was higher 9.398 mg/dl as compared to controls which were 8.694 mg/dl. Whereas the mean value of inorganic phosphorus level was lower 4.060 mg/dl in BC patients as compared to controls having 4.456 mg/dl. In this study, the frequency of hypercalcemia in Breast cancer patients was 10% i.e. only 10 out of 50 Breast cancer patients were suffering from hypercalcemia. Whereas the frequency of hypophosphatemia in this study was only 2 % i.e. only 1 out of 50 patients was suffering from hypophosphatemia. Thus it is concluded that there is a significant change in serum calcium and inorganic phosphorous levels in Breast cancer patients as the disease progresses. So, this study will be helpful for the clinicians to maintain serum calcium and phosphorous levels in Breast cancer patients and also preventing them from further complications.

Keywords: serum analysis, calcium, inorganic phosphorus, hpercalcemia hypophosphatemia

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642 Investigation of Influence of Maize Stover Components and Urea Treatment on Dry Matter Digestibility and Fermentation Kinetics Using in vitro Gas Techniques

Authors: Anon Paserakung, Chaloemphon Muangyen, Suban Foiklang, Yanin Opatpatanakit

Abstract:

Improving nutritive values and digestibility of maize stover is an alternative way to increase their utilization in ruminant and reduce air pollution from open burning of maize stover in the northern Thailand. The present study, 2x3 factorial arrangements in completely randomized design was conducted to investigate the effect of maize stover components (whole and upper stover; cut above 5th node). Urea treatment at levels 0, 3, and 6% DM on dry matter digestibility and fermentation kinetics of maize stover using in vitro gas production. After 21 days of urea treatment, results illustrated that there was no interaction between maize stover components and urea treatment on 48h in vitro dry matter digestibility (IVDMD). IVDMD was unaffected by maize stover components (P > 0.05), average IVDMD was 55%. However, using whole maize stover gave higher cumulative gas and gas kinetic parameters than those of upper stover (P<0.05). Treating maize stover by ensiling with urea resulted in a significant linear increase in IVDMD (P<0.05). IVDMD increased from 42.6% to 53.9% when increased urea concentration from 0 to 3% and maximum IVDMD (65.1%) was observed when maize stover was ensiled with 6% urea. Maize stover treated with urea at levels of 0, 3, and 6% linearly increased cumulative gas production at 96h (31.1 vs 50.5 and 59.1 ml, respectively) and all gas kinetic parameters excepted the gas production from the immediately soluble fraction (P<0.50). The results indicate that maize stover treated with 6% urea enhance in vitro dry matter digestibility and fermentation kinetics. This study provides a practical approach to increasing utilization of maize stover in feeding ruminant animals.

Keywords: maize stover, urea treatment, ruminant feed, gas production

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641 Nourishing the Hive: The Interplay of Nutrition, Gene Expression, and Queen Egg-Laying in Honeybee Colonies

Authors: Damien P. Fevre, Peter K. Dearden

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Honeybee population sustainability is a critical concern for environmental stability and human food security. The success of a colony relies heavily on the egg-laying capacity of the queen, as it determines the production of thousands of worker bees who, in turn, perform essential functions in foraging and transforming food to make it digestible for the colony. The main sources of nutrition for honeybees are nectar, providing carbohydrates, and pollen, providing protein. This study delves into the impact of the proportion of these macronutrients on the food consumption patterns of nurse bees responsible for feeding the queen and how it affects the characteristics of the eggs produced. Using nutritional geometry, qRT-PCR, and RNA-seq analysis, this study sheds light on the pivotal role of nutrition in influencing gene expression in nurse bees, honeybee queen egg-laying capacity and embryonic development. Interestingly, while nutrition is crucial, the queen's genotype plays an even more significant role in this complex relationship, highlighting the importance of genotype-by-environment interactions. Understanding the interplay between genotype and nutrition is key to optimizing beekeeping management and strategic queen breeding practices. The findings from this study have significant implications for beekeeping practices, emphasizing the need for an appropriate nutrition to support the social nutrition of Apis mellifera. Implementing these insights can lead to improved colony health, increased productivity, and sustainable honeybee conservation efforts.

Keywords: honeybee, egg-laying, nutrition, transcriptomics

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640 Factors Associated with Mammography Screening Behaviors: A Cross-Sectional Descriptive Study of Egyptian Women

Authors: Salwa Hagag Abdelaziz, Naglaa Fathy Youssef, Nadia Abdellatif Hassan, Rasha Wesam Abdelrahman

Abstract:

Breast cancer is considered as a substantial health concern and practicing mammography screening [MS] is important in minimizing its related morbidity. So it is essential to have a better understanding of breast cancer screening behaviors of women and factors that influence utilization of them. The aim of this study is to identify the factors that are linked to MS behaviors among the Egyptian women. A cross-sectional descriptive design was carried out to provide a snapshot of the factors that are linked to MS behaviors. A convenience sample of 311 women was utilized and all eligible participants admitted to the Women Imaging Unit who are 40 years of age or above, coming for mammography assessment, not pregnant or breast feeding and who accepted to participate in the study were included. A structured questionnaire was developed by the researchers and contains three parts; Socio-demographic data; Motivating factors associated with MS; and association between MS and model of behavior change. The analyzed data indicated that most of the participated women (66.6 %) belonged to the age group of 40-49.A high proportion of participants (58.1%) of group having previous MS influenced by their neighbors to practice MS, whereas 32.7 % in group not having previous MS were influenced by family members which indicated significant differences (P <0.05). Doctors and media are shown to be the least influence of others to practice MS. Women with intention to have a future mammogram had higher OR (1.404) for practicing MS compared with women with no intention. Further studies are needed to examine the relation between Trans-theoretical Model [TTM] and practicing MS.

Keywords: breast cancer, mammography, screening behaviors, morbidity

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639 Dietary Effect of Probiotic Bacteria, Bacillus amyloliquefaciens JFP-2 Isolate from Jeju Island`s Traditional Fermented Food, on Innate Immune Response of Oplegnathus fasciatus Challenged with Vibrio anguillarum

Authors: Dong Hwi Kim, Dharaneedharan Subramanian, So Hyun Park, Ha-Ri Choi, Ji-Hyung Kim, Dong-Hoon Lee, Moon Soo Heo

Abstract:

The present study was performed to evaluate the use of Bacillus amyloliquefaciens JFP-2 isolated from a traditional fermented sea food, as probiotic bacteria in the diets for Rock-bream, Oplegnathus faciatus. A total of 180 fish (187.4 ± 2.7 g) were divided into two groups, control (C) and probiotic (P) group (90 fish per group) in triplicate. C group was fed with basal diet without probiotic, while P group was fed with B. amyloliquefaciens spores at concentration of 1.4 x 106 colony forming units per gram (CFU/g) of feed. After two months of feeding experiments, P group fish showed significant improvements in body weight (BW), weight gain (WG), specific growth rate (SGR) and food conversion ratio (FCR) compared with C group. Also, bi-weekly assessment of serum protein, glucose, fatty acid profile showed a significant increase in probiotic fed fish than that of control fish group. Similar increase in serum antioxidant and lysozyme activity was found in probiotic fed fish group. Twenty days challenge experiment shows decrease mortality in probiotic fed fish group when compared with that of control group. Hence, these results indicate that the use of B. amyloliquefaciens JFP-2 as a feed supplement, is beneficial to improve the health status of Oplegnathus fasciatus challenged with Vibrio anguillarum.

Keywords: Bacillus amyloliquefaciens, Oplegnathus fasciatus, probiotic feed, rock bream

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638 Analysis Of Fine Motor Skills in Chronic Neurodegenerative Models of Huntington’s Disease and Amyotrophic Lateral Sclerosis

Authors: T. Heikkinen, J. Oksman, T. Bragge, A. Nurmi, O. Kontkanen, T. Ahtoniemi

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Motor impairment is an inherent phenotypic feature of several chronic neurodegenerative diseases, and pharmacological therapies aimed to counterbalance the motor disability have a great market potential. Animal models of chronic neurodegenerative diseases display a number deteriorating motor phenotype during the disease progression. There is a wide array of behavioral tools to evaluate motor functions in rodents. However, currently existing methods to study motor functions in rodents are often limited to evaluate gross motor functions only at advanced stages of the disease phenotype. The most commonly applied traditional motor assays used in CNS rodent models, lack the sensitivity to capture fine motor impairments or improvements. Fine motor skill characterization in rodents provides a more sensitive tool to capture more subtle motor dysfunctions and therapeutic effects. Importantly, similar approach, kinematic movement analysis, is also used in clinic, and applied both in diagnosis and determination of therapeutic response to pharmacological interventions. The aim of this study was to apply kinematic gait analysis, a novel and automated high precision movement analysis system, to characterize phenotypic deficits in three different chronic neurodegenerative animal models, a transgenic mouse model (SOD1 G93A) for amyotrophic lateral sclerosis (ALS), and R6/2 and Q175KI mouse models for Huntington’s disease (HD). The readouts from walking behavior included gait properties with kinematic data, and body movement trajectories including analysis of various points of interest such as movement and position of landmarks in the torso, tail and joints. Mice (transgenic and wild-type) from each model were analyzed for the fine motor kinematic properties at young ages, prior to the age when gross motor deficits are clearly pronounced. Fine motor kinematic Evaluation was continued in the same animals until clear motor dysfunction with conventional motor assays was evident. Time course analysis revealed clear fine motor skill impairments in each transgenic model earlier than what is seen with conventional gross motor tests. Motor changes were quantitatively analyzed for up to ~80 parameters, and the largest data sets of HD models were further processed with principal component analysis (PCA) to transform the pool of individual parameters into a smaller and focused set of mutually uncorrelated gait parameters showing strong genotype difference. Kinematic fine motor analysis of transgenic animal models described in this presentation show that this method isa sensitive, objective and fully automated tool that allows earlier and more sensitive detection of progressive neuromuscular and CNS disease phenotypes. As a result of the analysis a comprehensive set of fine motor parameters for each model is created, and these parameters provide better understanding of the disease progression and enhanced sensitivity of this assay for therapeutic testing compared to classical motor behavior tests. In SOD1 G93A, R6/2, and Q175KI mice, the alterations in gait were evident already several weeks earlier than with traditional gross motor assays. Kinematic testing can be applied to a wider set of motor readouts beyond gait in order to study whole body movement patterns such as with relation to joints and various body parts longitudinally, providing a sophisticated and translatable method for disseminating motor components in rodent disease models and evaluating therapeutic interventions.

Keywords: Gait analysis, kinematic, motor impairment, inherent feature

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637 Violence Detection and Tracking on Moving Surveillance Video Using Machine Learning Approach

Authors: Abe Degale D., Cheng Jian

Abstract:

When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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636 A Multi-Arm Randomized Trial Comparing the Weight Gain of Very Low Birth Weight Neonates: High Glucose versus High Protein Intake

Authors: Farnaz Firuzian, Farhad Choobdar, Ali Mazouri

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As Very Low Birth Weight (VLBW) neonates cannot tolerate enteral feeding, parenteral nutrition (PN) must be administered shortly after birth. To find an optimal combination of nutrition, in this study, we compare administering high glucose versus high protein intake as a component of total parenteral nutrition (TPN) to test their effect on birth weight (BW) regain in VLBW. This study employs a multi-arm randomized trial: 145 newborns with BW < 1500 g were randomized to control (C) or experimental groups: high glucose (G) or high protein (P). All samples in each group received the same TPN regimens except glucose and protein intake: Glocuse was provided by dextrose water (DW) serum: 7-15 g/kg/d (10% DW) in groups C and P versus 8.75-18.75 g/kg/d (12.5% DW) in group G. Protein provided by amino acids 3 g/kg/d for groups C and G versus 4 g/kg/d for group P. Outcomes (weight, height, and head circumference) was monitored on a daily basis until the BW was regained. Data has been gathered recently and is being processed. We hypothesize that neonates with higher amino acid intake will result in sooner BW regain than other groups. The result will be presented at the conference. The findings of this study not only can help optimize nutrition, cost reduction, and shorter NICU admission of VLBW neonates at the hospital level but eventually contribute to reduced healthcare-associated infections (HAIs) and an improved health economy.

Keywords: very low birth weight neonates, weight gain, parenteral nutrition, glucose, amino acids

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