Search results for: computer assisted classification

Authors: Srinidhi. A, Naveed Ahmed, Twinkle Hareendran, Vriksha Prakash

Abstract:

This work reviews some of the advanced image processing techniques for deep learning applications. Object detection by template matching, image denoising, edge detection, and super-resolution modelling are but a few of the tasks. The paper looks in into great detail, given that such tasks are crucial preprocessing steps that increase the quality and usability of image datasets in subsequent deep learning tasks. We review some of the methods for the assessment of image quality, more specifically sharpness, which is crucial to ensure a robust performance of models. Further, we will discuss the development of deep learning models specific to facial emotion detection, age classification, and gender classification, which essentially includes the preprocessing techniques interrelated with model performance. Conclusions from this study pinpoint the best practices in the preparation of image datasets, targeting the best trade-off between computational efficiency and retaining important image features critical for effective training of deep learning models.

Keywords: image processing, machine learning applications, template matching, emotion detection

Procedia PDF Downloads 14

Authors: McClain Thiel

Abstract:

Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

Procedia PDF Downloads 139

Authors: Cristian Pauna

Abstract:

With few steps away from the 2020, investments in financial markets is a common activity nowadays. In the electronic trading environment, the automated investment software has become a major part in the business intelligence system of any modern financial company. The investment decisions are assisted and/or made automatically by computers using mathematical algorithms today. The complexity of these algorithms requires computer assistance in the investment process. This paper will present several investment strategies that can be automated with algorithmic trading for Deutscher Aktienindex DAX30. It was found that, based on several price action mathematical models used for high-frequency trading some investment strategies can be optimized and improved for automated investments with good results. This paper will present the way to automate these investment decisions. Automated signals will be built using all of these strategies. Three major types of investment strategies were found in this study. The types are separated by the target length and by the exit strategy used. The exit decisions will be also automated and the paper will present the specificity for each investment type. A comparative study will be also included in this paper in order to reveal the differences between strategies. Based on these results, the profit and the capital exposure will be compared and analyzed in order to qualify the investment methodologies presented and to compare them with any other investment system. As conclusion, some major investment strategies will be revealed and compared in order to be considered for inclusion in any automated investment system.

Keywords: Algorithmic trading, automated investment systems, limit conditions, trading principles, trading strategies

Procedia PDF Downloads 194

Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

Abstract:

This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

Procedia PDF Downloads 178

Authors: M. Salama, K. Haggag, H. El-Sayed

Abstract:

An environmentally and ecologically acceptable method for eradication of wool fabrics based on microwave irradiation (MWI) was described. The process would be a suitable alternative for mothproofing of wool using toxic degradative chemical or biological methods. The effect of microwave irradiation and exposure time on the extent of eradication of wool fabrics from moth larvae was monitored. The inherent properties of the MW-irradiated wool fabrics; viz. tensile properties, alkali solubility, and yellowing index, were not adversely altered.

Keywords: microwave, wool, fabric, moth, eradication, resistance

Procedia PDF Downloads 457

Authors: Eva Tvrdá, Marek Halenár, Hana Greifová, Alica Mackovich, Faridullah Hashim, Norbert Lukáč

Abstract:

Oxidative stress associated with semen cryopreservation may result in lipid peroxidation (LPO), DNA damage and apoptosis, leading to decreased sperm motility and fertilization ability. Curcumin (CUR), a natural phenol isolated from Curcuma longa Linn. has been presented as a possible supplement for a more effective semen cryopreservation because of its antioxidant properties. This study focused to evaluate the effects of CUR on selected oxidative stress parameters in cryopreserved bovine semen. 20 bovine ejaculates were split into two aliquots and diluted with a commercial semen extender containing CUR (50 μmol/L) or no supplement (control), cooled to 4 °C, frozen and kept in liquid nitrogen. Frozen straws were thawed in a water bath for subsequent experiments. Computer assisted semen analysis was used to evaluate spermatozoa motility, and reactive oxygen species (ROS) generation was quantified by using luminometry. Superoxide generation was evaluated with the NBT test, and LPO was assessed via the TBARS assay. CUR supplementation significantly (P<0.001) increased the spermatozoa motility and provided a significantly higher protection against ROS (P<0.001) or superoxide (P<0.01) overgeneration caused by semen freezing and thawing. Furthermore, CUR administration resulted in a significantly (P<0.01) lower LPO of the experimental semen samples. In conclusion, CUR exhibits significant ROS-scavenging activities which may prevent oxidative insults to cryopreserved spermatozoa and thus may enhance the post-thaw functional activity of male gametes.

Keywords: bulls, cryopreservation, curcumin, lipid peroxidation, reactive oxygen species, spermatozoa

Procedia PDF Downloads 267

Authors: Mukesh Singh Boori, Vít Voženílek

Abstract:

Olomouc is a unique and complex landmark with widespread forestation and land use. This research work was conducted to assess important and complex land use change trajectories in Olomouc region. Multi-temporal satellite data from 1991, 2001 and 2013 were used to extract land use/cover types by object oriented classification method. To achieve the objectives, three different aspects were used: (1) Calculate the quantity of each transition; (2) Allocate location based landscape pattern (3) Compare land use/cover evaluation procedure. Land cover change trajectories shows that 16.69% agriculture, 54.33% forest and 21.98% other areas (settlement, pasture and water-body) were stable in all three decade. Approximately 30% of the study area maintained as a same land cove type from 1991 to 2013. Here broad scale of political and socio-economic factors was also affect the rate and direction of landscape changes. Distance from the settlements was the most important predictor of land cover change trajectories. This showed that most of landscape trajectories were caused by socio-economic activities and mainly led to virtuous change on the ecological environment.

Keywords: remote sensing, land use/cover, change trajectories, image classification

Procedia PDF Downloads 404

Authors: Madhuri S. Ghate, Rahul P. Chavhan, Shriya S. Nahar

Abstract:

Learning objective: •To describe Magnetic Resonance Imaging (MRI) imaging appearances of typical and atypical uterine fibroids with emphasis on differentiating it from other similar conditions. •To classify uterine fibroids according to International Federation of Gynecology and Obstetrics (FIGO) Sub-classifications system and emphasis on its clinical significance. •To show cases with atypical imaging appearances atypical fibroids Material and methods: MRI of Pelvis had been performed in symptomatic women of child bearing age group on 1.5T and 3T MRI using T1, T2, STIR, FAT SAT, DWI sequences. Contrast was administered when degeneration was suspected. Imaging appearances of Atypical fibroids and various degenerations in fibroids were studied. Fibroids were classified using FIGO Sub-classification system. Its impact on surgical decision making and clinical outcome were also studied qualitatively. Results: Intramural fibroids were most common (14 patients), subserosal 7 patients, submucosal 5 patients . 6 patients were having multiple fibroids. 7 were having atypical fibroids. (1 hyaline degeneration, 1 cystic degeneration, 1 fatty, 1 necrosis and hemorrhage, 1 red degeneration, 1 calcification, 1 unusual large bilobed growth). Fibroids were classified using FIGO system. In uterus conservative surgeries, the lesser was the degree of myometrial invasion of fibroid, better was the fertility outcome. Conclusion: Relationship of fibroid with mucosal and serosal layers is important in the management of symptomatic fibroid cases. Risk to fertility involved in uterus conservative surgeries in women of child bearing age group depends on the extent of myometrial invasion of fibroids. FIGO system provides better insight into the degree of myometrial invasion. Knowledge about the atypical appearances of fibroids is important to avoid diagnostic confusion and untoward treatment.

Keywords: degeneration, FIGO sub-classification, MRI pelvis, uterine fibroids

Procedia PDF Downloads 92

Authors: Ghaem Zamani, Farveh Aghaye Nezhad, Amin Barari

Abstract:

The installation process of caissons has usually been a challenging step in the design phase, especially in the case of suction-assisted installation. The engineering practice for estimating the caisson penetration resistance is primarily controlled by the resistance governed by inner and outer skirt friction and the tip resistance. Different methods have been proposed in the literature to evaluate the above components, while the CPT-based methodology has attained notable popularity among others. In this method, two empirical coefficients are suggested, k𝒻 and kp, which relate the frictional resistance and tip resistance to the cone penetration resistance (q𝒸), respectively. A series of jacking installation and uninstallation experiments for different soil densities were carried out in the offshore geotechnical laboratory of Aalborg University, Denmark. The main goal of these tests was to find appropriate values for empirical coefficients of the CPT-based method for the buckets with large embedment ratio (i.e., d/D=1, where d is the skirt length and D is the diameter) and increased tip area penetrated into dense sand deposits. The friction resistance effects were isolated during the pullout experiments; hence, the k𝒻 was back-measured from the tests in the absence of tip resistance. The actuator force during jacking installation equals the sum of frictional resistance and tip resistance. Therefore, the tip resistance of the bucket is calculated by subtracting the back-measured frictional resistance from penetration resistance; hence the relevant coefficient kp would be achieved. The cone penetration test was operated at different points before and after each installation attempt to measure the cone penetration resistance (q𝒸), and the average value of q𝒸 is used for calculations. The experimental results of the jacking installation tests indicated that a larger friction area considerably increased the penetration resistance; however, this effect was completely diminished when foundation suction-assisted penetration was used. Finally, the values measured for the empirical coefficient of the CPT-based method are compared with the highest expected and most probable values suggested by DNV(1992) for uniform thickness buckets.

Keywords: suction caisson, offshore geotechnics, cone penetration test, wind turbine foundation

Procedia PDF Downloads 84

Authors: Maha Shamseddine, Amjad Nusayr, Wassim Itani

Abstract:

In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.

Keywords: privacy enforcement, platform-as-a-service privacy awareness, cloud computing privacy

Procedia PDF Downloads 227

Authors: Pelin Yilmaz, Gizemnur Yildiz Uysal, Elcin Demirhan, Belma Ozbek

Abstract:

The edible fig plant, Ficus carica Linn, belongs to the Moraceae family, and the leaves are mainly considered agricultural waste after harvesting. It has been demonstrated in the literature that fig leaves contain appealing properties such as high vitamins, fiber, amino acids, organic acids, and phenolic or flavonoid content. The extraction of these valuable products has gained importance. Microwave-assisted extraction (MAE) is a method using microwave energy to heat the solvents, thereby transferring the bioactive compounds from the sample to the solvent. The main advantage of the MAE is the rapid extraction of bioactive compounds. In the present study, the MAE was applied to extract the bioactive compounds from Ficus carica L. leaves, and the effect of microwave power (180-900 W), extraction time (60-180 s), and solvent to sample amount (mL/g) (10-30) on the antioxidant property of the leaves. Then, the volatile organic component profile was determined at the specified extraction point. Additionally, antimicrobial studies were carried out to determine the minimum inhibitory concentration of the microwave-extracted leaves. As a result, according to the data obtained from the experimental studies, the highest antimicrobial properties were obtained under the process parameters such as 540 W, 180 s, and 20 mL/g concentration. The volatile organic compound profile showed that isobergapten, which belongs to the furanocoumarins family exhibiting anticancer, antioxidant, and antimicrobial activity besides promoting bone health, was the main compound. Acknowledgments: This work has been supported by Yildiz Technical University Scientific Research Projects Coordination Unit under project number FBA-2021-4409. The authors would like to acknowledge the financial support from Tubitak 1515 - Frontier R&D Laboratory Support Programme.

Keywords: Ficus carica Linn leaves, volatile organic component, GC-MS, microwave extraction, isobergapten, antimicrobial

Procedia PDF Downloads 80

Authors: Linghui Meng, James Atlas, Deborah Munro

Abstract:

There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.

Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers

Procedia PDF Downloads 30

Authors: Monika Paleczna, Barbara Szmigielska

Abstract:

Adolescence is a developmental period, covering the period from 10 to 20 years of age, in which young people face many challenges. One of the most important tasks of the adolescence period is getting a structured identity. The development of identity is possible by undertaking various activities. Nowadays, virtual activities are very common among young people. One of the main adolescents’ activities in the online environment is playing computer games. The main aim of this work is to answer the question about the relationship between the identity style of adolescents and immersion, -a phenomenon often observed while playing computer games. The concept of identity created by Berzonsky is considered as one of the best-defined concepts of identity. He defines identity as both a structure and a process and distinguishes three styles of identity: informational, normative, and diffuse/avoidant. Immersion is a concept that can be applied in a broad context, but in the game environment, it is a specific psychological experience of being involved in a computer game. It refers to the relocation of the attention resources to the game world, with a limited or impossible perception of stimuli from reality. Considering how much time adolescents spend playing computer games, the question about the relationship between their identity and the immersion in the game seems to be extremely interesting. Fifty adolescents aged 15-17 participated in the study. They played a computer game and completed the Identity Style Inventory and the Immersion Questionaire.

Keywords: identity, immersion, computer games, adolescence

Procedia PDF Downloads 273

Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

Abstract:

Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

Procedia PDF Downloads 226

Authors: Parul Garg

Abstract:

Bouveret Syndrome is a rare presentation described as Gastric Outlet Obstruction secondary to Gallstone Ileus. Here we describe the 3-year progression of disease from cholelithiasis to gallstone ileus with relevant imaging findings. The patient was treated under an Upper Gastrointestinal Surgery service with surgical intervention in the form of a laparoscopic assisted procedure with midline laparotomy. She recovered well and was discharged 1 week post operatively. No complications occurred.

Keywords: Cholelithiasis, Bouveret syndrome, Gallstone Ileus, gastric outlet obstruction

Procedia PDF Downloads 120

Authors: R. Pargas, M. Reba

Abstract:

Since 2006, the School of Computing and the Department of Mathematical Sciences have collaborated on several industry and NSF grants to develop new uses of technology in teaching and learning. Clemson University’s Creative Inquiry Program allowed computer science and mathematics students to earn credit each semester for participating in seminars which introduced them to new areas for independent research. We will discuss how the development of three interactive instructional apps for Calculus resulted not only in a useful product, but also in unique educational benefits for both the computer science students and the mathematics students, graduate and undergraduate, involved in the development process.

Keywords: calculus, apps, programming, mathematics

Procedia PDF Downloads 404

Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

Abstract:

This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

Procedia PDF Downloads 441

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

Abstract:

Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 163

Authors: Ki Hyun Park, Hye Min Park, Jeong Ho Kim, Chan Jong Park, Koan Sik Joo

Abstract:

In the modern days, the use of radioactive substances is on the rise in the areas like chemical weaponry, industrial usage, and power plants. Although there are various technologies available to detect and monitor radioactive substances in the air, the technologies to detect underwater radioactive substances are scarce. In this study, computer simulation of the underwater detection system measuring beta-ray, a radioactive substance, has been done through MCNP. CaF₂, YAP(Ce) and YAG(Ce) have been used in the computer simulation to detect beta-ray as scintillator. Also, the source used in the computer simulation is Sr-90 and Y-90, both of them emitting only pure beta-ray. The distance between the source and the detector was shifted from 1mm to 10mm by 1 mm in the computer simulation. The result indicated that Sr-90 was impossible to measure below 1 mm since its emission energy is low while Y-90 was able to be measured up to 10mm underwater. In addition, the detector designed with CaF₂ had the highest efficiency among 3 scintillators used in the computer simulation. Since it was possible to verify the detectable range and the detection efficiency according to modeling through MCNP simulation, it is expected that such result will reduce the time and cost in building the actual beta-ray detector and evaluating its performances, thereby contributing the research and development.

Keywords: Beta-ray, CaF₂, detector, MCNP simulation, scintillator

Procedia PDF Downloads 510

Authors: Wisam Ismail, Brendan Wooler, Penelope McManus

Abstract:

Introduction: The public perception of implants has been damaged in the wake of recent negative publicity and increasingly we are finding patients wanting to avoid them. Planned lipo-modelling to enhance the volume of a Latissimus dorsi flap is a viable alternative to silicone implants and maintains a Totally Autologous Technique (TAT). Here we demonstrate that when compared to an Implant Assisted Technique (IAT), a TAT offers patients many benefits that offset the requirement of more operations initially, with reduced short and long term complications, reduced symmetrisation surgery and reduced revision rates. Methods. Data was collected prospectively over 7 years. The minimum follows up was 3 years. The technique was generally standardized in the hand of one surgeon. All flaps were extended LD flaps (ELD). Lipo-modelling was performed using standard techniques. Outcome measures were unplanned secondary procedures, complication rates, and contralateral symmetrisation surgery rates. Key Results Were: Lower complication rates in the TAT group (18.5% vs. 33.3%), despite higher radiotherapy rates (TAT=49%, IAT=36.8%), TAT was associated with lower subsequent symmetrisation rates (30.6% vs. 50.9%), IAT had a relative risk of 3.1 for subsequent unplanned procedure, Autologous patients required an average of 1.76 sessions of lipo-modelling, Conclusions: Using lipo-modelling to enable totally autologous LD reconstruction offers significant advantages over an implant assisted technique. We have shown a lower subsequent unplanned procedure rate, lower revision surgery, and less contralateral symmetrisation surgery. We anticipate that a TAT will be supported by patient satisfaction surveys and long-term patient-reported cosmetic outcome data and intended to study this.

Keywords: breast, Latissimus dorsi, lipomodelling, reconstruction

Procedia PDF Downloads 335

Authors: Gianne Bianca P. Manalo, Ernesto A. Martin, Vanessa V. Velasco

Abstract:

The laying performance, egg quality, egg classification, and income over feed cost of Improved Philippine Mallard duck (Itik Pinas) were examined as influenced by garlic powder in drinking water. A total of 48 ducks (42 females and 6 males) were used in the study. The ducks were allocated into two treatments - with garlic powder (GP) and without garlic powder (control) in drinking water. Each treatment had three replicates with eight ducks (7 females and 1 male) per replication. The results showed that there was a significant (P = 0.03) difference in average egg weight where higher values were attained by ducks with GP (77.67 g ± 0.64) than the control (75.64 g ± 0.43). The supplementation of garlic powder in drinking water, however, did not affect the egg production, feed intake, FCR, egg mass, livability, egg quality and egg classification. The Itik Pinas with GP in drinking water had numerically higher income over feed cost than those without. GP in drinking water can be considered in raising Itik Pinas. Further studies on increasing level of GP and long feeding duration also merit consideration to substantiate the findings.

Keywords: phytogenic, garlic powder, Itik-Pinas, egg weight, egg production

Procedia PDF Downloads 84

Authors: Damian Czubak

Abstract:

The Białowieża Forest is a very valuable natural area, included in the World Natural Heritage at UNESCO, where, due to infestation by the bark beetle (Ips typographus), norway spruce (Picea abies) have deteriorated. This catastrophic scenario led to an increase in fire danger. This was due to the occurrence of large amounts of dead wood and grass cover, as light penetrated to the bottom of the stands. These factors in a dry state are materials that favour the possibility of fire and the rapid spread of fire. One of the objectives of the study was to monitor the quantitative and qualitative changes of combustible material on the permanent decay plots of spruce stands from 2012-2022. In addition, the size of the area with highly flammable vegetation was monitored and a classification of the stands of the Białowieża Forest by flammability classes was made. The key factor that determines the potential fire hazard of a forest is combustible material. Primarily its type, quantity, moisture content, size and spatial structure. Based on the inventory data on the areas of forest districts in the Białowieża Forest, the average fire load and its changes over the years were calculated. The analysis was carried out taking into account the changes in the health status of the stands and sanitary operations. The quantitative and qualitative assessment of fallen timber and fire load of ground cover used the results of the 2019 and 2021 inventories. Approximately 9,000 circular plots were used for the study. An assessment was made of the amount of potential fuel, understood as ground cover vegetation and dead wood debris. In addition, monitoring of areas with vegetation that poses a high fire risk was conducted using data from 2019 and 2021. All sub-areas were inventoried where vegetation posing a specific fire hazard represented at least 10% of the area with species characteristic of that cover. In addition to the size of the area with fire-prone vegetation, a very important element is the size of the fire load on the indicated plots. On representative plots, the biomass of the land cover was measured on an area of 10 m2 and then the amount of biomass of each component was determined. The resulting element of variability of ground covers in stands was their flammability classification. The classification developed made it possible to track changes in the flammability classes of stands over the period covered by the measurements.

Keywords: classification, combustible material, flammable vegetation, Norway spruce

Procedia PDF Downloads 93

Authors: Aldé Belgard Tchicaya Loemba, Baraka Kichonge, Thomas Kivevele, Juma Rajabu Selemani

Abstract:

Plants used for medicinal purposes are extremely perishable, owing to moisture-enhanced enzymatic and microorganism activity, climate change, and improper handling and storage. Experiments have shown that drying the medicinal plant without affecting the active nutrients and controlling the moisture content as much as possible can extend its shelf life. Different traditional and modern drying techniques for preserving medicinal plants have been developed, with some still being improved in Sub-Saharan Africa. However, many of these methods fail to address the most common issues encountered when drying medicinal plants, such as nutrient loss, long drying times, and a limited capacity to dry during the evening or cloudy hours. Heat pump drying is an alternate drying method that results in no nutritional loss. Furthermore, combining a heat pump dryer with a solar energy storage system appears to be a viable option for all-weather drying without affecting the nutritional values of dried products. In this study, a solar-assisted heat pump dryer integrated with thermal energy storage is developed for drying moringa leaves. The study also discusses the performance analysis of the developed dryer as well as the proximate analysis of the dried moringa leaves. All experiments were conducted from 11 a.m. to 4 p.m. to assess the dryer's performance in “daytime mode”. Experiment results show that the drying time was significantly reduced, and the dryer demonstrated high performance in preserving all of the nutrients. In 5 hours of the drying process, the moisture content was reduced from 75.7 to 3.3%. The average COP value was 3.36, confirming the dryer's low energy consumption. The findings also revealed that after drying, the content of protein, carbohydrates, fats, fiber, and ash greatly increased.

Keywords: heat pump dryer, efficiency, moringa leaves, proximate analysis

Procedia PDF Downloads 82

Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

Abstract:

In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

Procedia PDF Downloads 461

Authors: Rajasekar Elangopandian, Anand Shanmugam

Abstract:

In order to reduce the cost of launching satellite and payloads to the orbit this project envisages some immense combined technology. This new technology in space odyssey contains literally four concepts. The first mode in this innovation is flight mission characteristics which, says how the mission will induct. The conventional technique of magnetic levitation will help us to produce the initial thrust. The name states reusable launch vehicle shows its viability of reuseness. The flight consists miniature rocket which produces the required thrust and the two JATO (jet assisted takeoff) boosters which gives the initial boost for the vehicle. The vehicle ostensibly looks like an airplane design and will be located on the super conducting rail track. When the high power electric current given to the rail track, the vehicle starts floating as per the principle of magnetic levitation. If the flight reaches the particular takeoff distance the two boosters gets starts and will give the 48KN thrust each. Obviously it`ll follow the vertical path up to the atmosphere end/start to space. As soon as it gets its speed the two boosters will cutoff. Once it reaches the space the inbuilt spacecraft keep the satellite in the desired orbit. When the work finishes, the apogee motors gives the initial kick to the vehicle to come in to the earth’s atmosphere with 22N thrust and automatically comes to the ground by following the free fall, the help of gravitational force. After the flying region it makes the spiral flight mode then gets landing where the super conducting levitated rail track located. It will catch up the vehicle and keep it by changing the poles of magnets and varying the current. Initial cost for making this vehicle might be high but for the frequent usage this will reduce the launch cost exactly half than the now-a-days technology. The incorporation of such a mechanism gives `hybrid` and the reusability gives `reusable launch vehicle` and ultimately Hybrid reusable launch vehicle.

Keywords: the two JATO (jet assisted takeoff) boosters, magnetic levitation, 48KN thrust each, 22N thrust and automatically comes to the ground

Procedia PDF Downloads 427

Authors: Richard Ayobayowa Foyewa

Abstract:

This work examined the application of ICT in the teaching and learning of English language in Nigerian secondary schools. The definition of ICT was given briefly before areas in which the ICT could be applied in teaching and learning of English language were observed. Teachers’ attitudes towards the use of the computer and Internet facilities were also observed. The conclusion drawn was that ICT is very relevant in the teaching and learning of English language in Nigerian secondary schools. It was therefore recommended that teachers who are not computer literate should go for the training without further delay; government should always employ English language teachers who are computer literates. Government should make fund available in schools for the training and re-training of English language teachers in various computer programmes and in making internet facilities available in secondary schools.

Keywords: ICT, Nigerian secondary schools, teaching and learning of English

Procedia PDF Downloads 318

Authors: Ameur Abdelkader, Abed Bouarfa Hafida

Abstract:

Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

Procedia PDF Downloads 142

Authors: Alberto Piatto, Zaza Nadja Lee Hansen, Peter Jacobsen

Abstract:

This paper examines the quantitative and qualitative factors influencing the buyer-supplier relationship. Understanding and acting on the right factors influencing supplier relationship management is crucial when a company outsource an important part of its business as it can be for engineering to order (ETO) company executing only the designing part in-house. Acting on these factors increase the quality of the relationship obtaining for both parties what they want and expect from an improved relationship. Best practices in supplier relationship management are considered and a case study of a large global company, called Cement A/S, operating in the cement business is carried out. One study is conducted including a large international company and hundreds of its suppliers. Data from the company is collected using semi-structured interviews and data from the suppliers is collected using a survey. Based on these inputs and an extensive literature review a classification of factors influencing the relationship buyer-supplier is presented and discussed. The results show that different managers among the company are assessing supplier from various perspectives, a standard approach to measure the performance of suppliers does not exist. The factors used nowadays in the company to measure performances of the suppliers are mostly related to time and cost. Quality is a key factor, but it has not been addressed properly since no data are available in the system. From a practical perspective, managers can learn from this paper which factors to consider when applying best practices of Supplier Relationship Management. Furthermore, from a theoretical perspective, this paper contributes with new knowledge in the area as limited research in collaboration with the company has been conducted. For this reason, a company, its suppliers and few studies for this type of industry have been conducted. For further research, it is suggested to define the correlation of factors to the profitability of the company and calculate its impact. When conducting this analysis it is important to focus on the efficient and effective use of factors that can be measurable and accepted from the supplier.

Keywords: buyer-supplier relationship, cement industry, classification of factors, ETO

Procedia PDF Downloads 282

Authors: Fabrice Setephin Atedjio, Jean-Pierre Lienou, Frederica F. Nelson, Sachin S. Shetty

Abstract:

Malicious users exploit vulnerabilities in computer systems, significantly disrupting their performance and revealing the inadequacies of existing protective solutions. Even machine learning-based approaches, designed to ensure reliability, can be compromised by adversarial attacks that undermine their robustness. This paper addresses two critical aspects of enhancing model reliability. First, we focus on improving model performance and robustness against adversarial threats. To achieve this, we propose a strategy by harnessing deep reinforcement learning. Second, we introduce an approach leveraging generative adversarial networks to counter adversarial attacks effectively. Our results demonstrate substantial improvements over previous works in the literature, with classifiers exhibiting enhanced accuracy in classification tasks, even in the presence of adversarial perturbations. These findings underscore the efficacy of the proposed model in mitigating intrusions and adversarial attacks within the machine learning landscape.

Keywords: machine learning, reliability, adversarial attacks, deep-reinforcement learning, robustness

Procedia PDF Downloads 9

Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

Abstract:

Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

Procedia PDF Downloads 191