Search results for: angel vector coordinate system

Authors: Jimmy L. Caldoza, Erlito M. Albina

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Information Systems are increasingly being used to monitor and assess government projects as well as improve transparency and combat corruption. With reference to existing information systems relevant to monitoring and evaluation systems adopted by various government agencies from other countries, this research paper aims to help the Philippine government, particularly the Department of Agriculture, in assessing the impact of their programs and projects on their target beneficiaries through the development of the web-based Monitoring and Evaluation Information System with the application of a short messaging system (sms) technology.

Keywords: monitoring and evaluation system, web-based information system, short messaging system technology, database structure and management

Procedia PDF Downloads 145

Authors: Navneet Kaur, S. D. Tiwari

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Superparamagnetism is an interesting phenomenon and observed in small particles of magnetic materials. It arises due to a reduction in particle size. In the superparamagnetic state, as the thermal energy overcomes magnetic anisotropy energy, the magnetic moment vector of particles flip their magnetization direction between states of minimum energy. Superparamagnetic nanoparticles have been attracting the researchers due to many applications such as information storage, magnetic resonance imaging, biomedical applications, and sensors. For information storage, thermal fluctuations lead to loss of data. So that nanoparticles should have high blocking temperature. And to achieve this, nanoparticles should have a higher magnetic moment and magnetic anisotropy constant. In this work, the magnetic anisotropy constant of the antiferromagnetic nanoparticles system is determined. Magnetic studies on nanoparticles of NiO (nickel oxide) are reported well. This antiferromagnetic nanoparticle system has high blocking temperature and magnetic anisotropy constant of order 105 J/m3. The magnetic study of NiO nanoparticles in the superparamagnetic region is presented. NiO particles of two different sizes, i.e., 6 and 8 nm, are synthesized using the chemical route. These particles are characterized by an x-ray diffractometer, transmission electron microscope, and superconducting quantum interference device magnetometry. The magnetization vs. applied magnetic field and temperature data for both samples confirm their superparamagnetic nature. The blocking temperature for 6 and 8 nm particles is found to be 200 and 172 K, respectively. Magnetization vs. applied magnetic field data of NiO is fitted to an appropriate magnetic expression using a non-linear least square fit method. The role of particle size distribution and magnetic anisotropy is taken in to account in magnetization expression. The source code is written in Python programming language. This fitting provides us the magnetic anisotropy constant for NiO and other magnetic fit parameters. The particle size distribution estimated matches well with the transmission electron micrograph. The value of magnetic anisotropy constants for 6 and 8 nm particles is found to be 1.42 X 105 and 1.20 X 105 J/m3, respectively. The obtained magnetic fit parameters are verified using the Neel model. It is concluded that the effect of magnetic anisotropy should not be ignored while studying the magnetization process of nanoparticles.

Keywords: anisotropy, superparamagnetic, nanoparticle, magnetization

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Authors: Ilham ihoume, Rachid Tadili, Nora Arbaoui

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This study examines the manner in which a solar copper coil heating system performs in a North-South-oriented greenhouse environment. In order to retain heat during the day and release it back ‎into the greenhouse environment at night, this system relies on the circulation of water in a closed ‎loop under the roof of the greenhouse. Experimental research ‎was conducted to compare the results in two identical greenhouses. The first one has a heating system, whilst the second one ‎has not and is regarded as a control. We determined the mass of the heat transfer fluid, which ‎makes up the storage system, needed to heat the greenhouse during the night to be equivalent to ‎‎689 Kg using the heat balance of the greenhouse equipped with a heating system. The findings ‎demonstrated that when compared to a controlled greenhouse without a heating system, the climatic ‎conditions within the experimental greenhouse were greatly enhanced by the solar heating system. ‎‎

Keywords: renewable energy, storage, enviromental impact, heating, agricultural greenhouse

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

Procedia PDF Downloads 249

Authors: Xiaoyang Zhao, Kaiying Wang

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The choice of stocking density in poultry farming is a potential way for determining welfare level of poultry. However, it is difficult to measure stocking densities in poultry farming because of a lot of variables such as species, age and weight, feeding way, house structure and geographical location in different broiler houses. A method was proposed in this paper to measure the differences of young broilers reared under different stocking densities by sound analysis. Vocalisations of broilers were recorded and analysed under different stocking densities to identify the relationship between sounds and stocking densities. Recordings were made continuously for three-week-old chickens in order to evaluate the variation of sounds emitted by the animals at the beginning. The experimental trial was carried out in an indoor reared broiler farm; the audio recording procedures lasted for 5 days. Broilers were divided into 5 groups, stocking density treatments were 8/m², 10/m², 12/m² (96birds/pen), 14/m² and 16/m², all conditions including ventilation and feed conditions were kept same except from stocking densities in every group. The recordings and analysis of sounds of chickens were made noninvasively. Sound recordings were manually analysed and labelled using sound analysis software: GoldWave Digital Audio Editor. After sound acquisition process, the Mel Frequency Cepstrum Coefficients (MFCC) was extracted from sound data, and the Support Vector Machine (SVM) was used as an early detector and classifier. This preliminary study, conducted in an indoor reared broiler farm shows that this method can be used to classify sounds of chickens under different densities economically (only a cheap microphone and recorder can be used), the classification accuracy is 85.7%. This method can predict the optimum stocking density of broilers with the complement of animal welfare indicators, animal productive indicators and so on.

Keywords: broiler, stocking density, poultry farming, sound monitoring, Mel Frequency Cepstrum Coefficients (MFCC), Support Vector Machine (SVM)

Procedia PDF Downloads 159

Authors: Emin Gundogar, Aysegul Yilmaz

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Strategic performance control is a significant procedure in management. There are various methods to improve this procedure. This study introduces an information system that is developed to score performance for municipal management. The application of the system is clarified by exemplifying municipal processes.

Keywords: management information system, municipal management, performance control

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Authors: Jonghoon Kim, Gilwon Yoon

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A wrist-band type biosignal measurement system and its data transfer through human body communication (HBC) were investigated. An HBC method based on pulses of ultra-wide band instead of using frequency or amplitude modulations was studied and implemented since the system became very compact and it was more suited for personal or mobile health monitoring. Our system measured photo-plethysmogram (PPG) and measured PPG signals were transmitted through a finger to a monitoring PC system. The device was compact and low-power consuming. HBC communication has very strong security measures since it does not use wireless network. Furthermore, biosignal monitoring system becomes handy because it does not need to have wire connections.

Keywords: biosignal, human body communication, mobile health, PPG, ultrawide band

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Authors: Mohammad Amin Tutunchian, Pedram Roshani, Reza Rezvani, Julio Ángel Infante Sedano

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The highly recommended approach to design, known as the load and resistance factor design (LRFD) method, employs the geotechnical resistance factor (GRF) for shaping pile foundation designs. Within the standard process for designing pile foundations, geotechnical engineers commonly adopt a design strategy rooted in saturated soil mechanics (SSM), often disregarding the impact of unsaturated soil behavior. This oversight within the design procedure leads to the omission of the enhancement in shear strength exhibited by unsaturated soils, resulting in a more cautious outcome in design results. This research endeavors to present a methodology for fine-tuning the GRF used for axially loaded driven piles in Winnipeg, Canada. This is achieved through the application of a well-established probabilistic approach known as the first-order second moment (FOSM) method while also accounting for the influence of unsaturated soil behavior. The findings of this study demonstrate that incorporating the influence of unsaturated conditions yields an elevation in projected bearing capacity and recommends higher GRF values in accordance with established codes. Additionally, a novel factor referred to as phy has been introduced to encompass the impact of saturation conditions in the calculation of pile bearing capacity, as guided by prevalent static analysis techniques.

Keywords: unsaturated soils, shear strength, LRFD, FOSM, GRF

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Authors: Radoslaw Pytlak, Damian Suski

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The aim of the paper is to provide a computational tool for planning a haemodialysis process. It is shown that optimization methods can be used to obtain the most effective treatment focused on removing both urea and phosphorus during the process. In order to achieve that, the IV–compartment model of phosphorus kinetics is applied. This kinetics model takes into account a rebound phenomenon that can occur during haemodialysis and results in a hybrid model of the process. Furthermore, vector fields associated with the model equations are such that it is very likely that using the most intuitive objective functions in the planning problem could lead to solutions which include sliding motions. Therefore, building computational tools for solving the problem of planning a haemodialysis process has required constructing numerical algorithms for solving optimal control problems with hybrid systems. The paper concentrates on minimum time control of hybrid systems since this control objective is the most suitable for the haemodialysis process considered in the paper. The presented approach to optimal control problems with hybrid systems is different from the others in several aspects. First of all, it is assumed that a hybrid system can exhibit sliding modes. Secondly, the system’s motion on the switching surface is described by index 2 differential–algebraic equations, and that guarantees accurate tracking of the sliding motion surface. Thirdly, the gradients of the problem’s functionals are evaluated with the help of adjoint equations. The adjoint equations presented in the paper take into account sliding motion and exhibit jump conditions at transition times. The optimality conditions in the form of the weak maximum principle for optimal control problems with hybrid systems exhibiting sliding modes and with piecewise constant controls are stated. The presented sensitivity analysis can be used to construct globally convergent algorithms for solving considered problems. The paper presents numerical results of solving the haemodialysis planning problem.

Keywords: haemodialysis planning process, hybrid systems, optimal control, sliding motion

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Authors: N. Ullah, A. Haddad, F. Van Der Linde

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This paper investigates the effects of breaks in bonds, breaks in the earthing system and breaks in earth wire on the rise of the earth potential (EPR) in a substation and at the transmission tower bases using various models of an L6 tower. Different approaches were adopted to examine the integrity of the earthing system and the terminal towers. These effects were investigated to see the associated difference in the EPR magnitudes with respect to a healthy system at various locations. Comparisons of the computed EPR magnitudes were then made between the healthy and unhealthy system to detect any difference. The studies were conducted at power frequency for a uniform soil with different soil resistivities. It was found that full breaks in the double bond of the terminal towers increase the EPR significantly at the fault location, while they reduce EPR at the terminal tower bases. A fault on the isolated section of the grid can result in EPR values up to 8 times of those on a healthy system at higher soil resistivities, provided that the extended earthing system stays connected to the grid.

Keywords: bonding, earthing, EPR, integrity, system

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Authors: Tamil Chelvi Vadivelu, Nurazean Maarop, Rasimah Che Yusoff, Farhana Aini Saludin

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Implementing a remote healthcare system needs to consider many security features. Therefore, before any deployment of the remote healthcare system, a feasibility study from the security perspective is crucial. Remote healthcare system using WBAN technology has been used in other countries for medical purposes but in Malaysia, such projects are still not yet implemented. This study was conducted qualitatively. The interview results involving five healthcare practitioners are further elaborated. The study has addressed four important security features in order to incorporate remote healthcare system using WBAN in Malaysian government hospitals.

Keywords: remote healthcare, IT security, security features, wireless sensor application

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Authors: Mario Jose Paillacho Silva, José Ángel Pérez López

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This article delves into the critical role of circular economy principles in unlocking sustainable growth and addressing environmental inequalities in emerging markets. Circular economy practices, rooted in regenerative systems and resource conservation, offer a transformative pathway for dynamic economies to achieve prosperity while minimizing environmental impact. The article comprehensively explores the understanding of the circular economy in emerging markets, emphasizing its economic benefits, social implications, and environmental advantages. It highlights key challenges and opportunities faced by these markets and emphasizes the crucial role of governments in creating supportive policy frameworks. It emphasizes how circular economy practices empower local communities and promote social inclusion and equality. Furthermore, the article underscores how the adoption of circular economy practices can mitigate waste, pollution, and resource scarcity, thus contributing to climate change mitigation and adaptation. Integrating circular economy principles with the United Nations' sustainable development goals (SDGs), the article showcases the potential of circularity in fostering responsible consumption and production, sustainable economic growth, and environmental protection. Overall, the article advocates for cross-sector collaboration and knowledge sharing to overcome barriers and scale circular economy practices in emerging markets, ultimately leading to a more equitable, prosperous, and environmentally sustainable future.

Keywords: circular economy, sustainability, emerging markets, circularity

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Authors: Geetu Gahlawat

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The education system accustomed information on daily basis in term of variety i.e Multimedia channel. This can create a challenge to pedagogue to get hold on learner. Multimedia enhance the education system with its technology. Educators deliver their content effectively and beyond any limit through multimedia elements on another side it gives easy learning to learners and they are able to get their goals fast. This paper gives an overview of how multimedia reshape the Indian education system with its promises and pitfalls.

Keywords: multimedia, technology, techniques, development, pedagogy

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Authors: Sitti Nurani Sirajuddin, Muh. Aminawar, Siti Nurlaelah, Amidah Amrawaty

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This study aimed to determine the income of beef cattle breeders from the traditional profit-sharing system named Tesang. This study was conducted in the province of South Sulawesi start from April to July 2014, used quantitative methods and data analysis is of income. The population is all beef cattle breeders who perform for the traditional profit-sharing system (Tesang) in Barru Regency and Bone Regency, province of South Sulawesi. Samples are beef cattle breeders who breeding the cattle with the traditional profit-sharing system (Tesang) in Barru Regency and Bone Regency using breeding system and cattle enlargement system (expense) by fifty breeders. The results showed beef cattle breeder’s income from the profit-sharing system (Tesang) where enlargement system (expense) at6th month maintenance periods higher than the profit-sharing system (Tesang) with using breeding the cattle.

Keywords: income, beef cattle, profit-sharing system, Teseng

Procedia PDF Downloads 281

Authors: G. Valentis, Q. Berthelot

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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

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Authors: Bu Seog Ju, Ho Young Son, Yong Hee Ryu

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This study is focused on the evaluation of seismic fragility of multi-story piping system installed in critical structures, isolated with triple friction pendulum bearing. The concept of this study is to isolate the critical building structure as well as nonstructural component, especially piping system in order to mitigate the earthquake damage and achieve the reliable seismic design. Then, the building system and multi-story piping system was modeled in OpenSees. In particular, the triple friction pendulum isolator was accounted for the vertical and horizontal coupling behavior in the building system subjected to seismic ground motions. Consequently, in order to generate the seismic fragility of base-isolated multi-story piping system, 21 selected seismic ground motions were carried out, by using Monte Carlo Simulation accounted for the uncertainties in demand. Finally, the system-level fragility curves corresponding to the limit state of the piping system was conducted at each T-joint system, which was commonly failure points in piping systems during and after an earthquake. Additionally, the system-level fragilities were performed to the first floor and second floor level in critical structures.

Keywords: fragility, friction pendulum bearing, nonstructural component, seismic

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Authors: Nora Arbaoui, Rachid Tadili, Ilham Ihoume

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To improve the climatic conditions and increase production in the greenhouse during the winter season under the Mediterranean climate, this thesis project proposes a design of an integrated and autonomous solar system for heating, cooling, and conservation of production in an agricultural greenhouse. To study the effectiveness of this system, experiments are conducted in two similar agricultural greenhouses oriented north-south. The first greenhouse is equipped with an active solar system integrated into the double glazing of the greenhouse’s roof, while the second greenhouse has no system, it serves as a controlled greenhouse for comparing thermal and agronomic performance The solar system allowed for an average increase in the indoor temperature of the experimental greenhouse of 6°C compared to the outdoor environment and 4°C compared to the control greenhouse. This improvement in temperature has a favorable effect on the plants' climate and subsequently positively affects their development, quality, and production.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

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Authors: Lydia Novozhilova, Vladimir Urazhdin

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An optimization problem for reinforced thin-walled vessels under uniform external pressure is considered. The conventional approaches to optimization generally start with pre-defined geometric parameters of the vessels, and then employ analytic or numeric calculations and/or experimental testing to verify functionality, such as stability under the projected conditions. The proposed approach consists of two steps. First, the feasibility domain will be identified in the multidimensional parameter space. Every point in the feasibility domain defines a design satisfying both geometric and functional constraints. Second, an objective function defined in this domain is formulated and optimized. The broader applicability of the suggested methodology is maximized by implementing the Support Vector Machines (SVM) classification algorithm of machine learning for identification of the feasible design region. Training data for SVM classifier is obtained using the Simulation package of SOLIDWORKS®. Based on the data, the SVM algorithm produces a curvilinear boundary separating admissible and not admissible sets of design parameters with maximal margins. Then optimization of the vessel parameters in the feasibility domain is performed using the standard algorithms for the constrained optimization. As an example, optimization of a ring-stiffened closed cylindrical thin-walled vessel with semi-spherical caps under high external pressure is implemented. As a functional constraint, von Mises stress criterion is used but any other stability constraint admitting mathematical formulation can be incorporated into the proposed approach. Suggested methodology has a good potential for reducing design time for finding optimal parameters of thin-walled vessels under uniform external pressure.

Keywords: design parameters, feasibility domain, von Mises stress criterion, Support Vector Machine (SVM) classifier

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

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Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: Maryam Shayan

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Chemical Process Simulation (CPS) software has been generally utilized by chemical (process) designers to outline, test, advance, and coordinate process plants. It is relied upon that modern scientists to bring these same critical thinking advantages to the outline and operation of industrial ecosystems can utilize CPS. This paper gives modern environment researchers and experts with a prologue to CPS and a review of compound designing configuration standards. The paper highlights late research demonstrating that CPS can be utilized to model modern industrial ecosystems, and talks about the advantages of utilizing CPS to address a portion of the specialized difficulties confronting organizations partaking in an industrial ecosystem. CPS can be utilized to (i) quantitatively assess and analyze the potential ecological and monetary advantages of material and vitality linkages; (ii) unravel general plan, retrofit, or operational issues; (iii) help to distinguish complex and frequently irrational arrangements; and (iv) assess imagine a scenario in which situations. CPS ought to be a valuable expansion to the mechanical environment tool stash.

Keywords: chemical process simulation (CPS), process plants, industrial ecosystems, compound designing

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Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

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This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab®/Simulink® to simulate the results.

Keywords: solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation

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Authors: A. S. Zgalei, B. T. Al-Mabrouk

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With a particularly significant growth rate observed in the Libyan commercial and residential buildings coupled with a growth in energy demand, solar desiccant evaporative cooling offers energy savings and promises a good sharing for sustainable buildings where the availability of solar radiation matches with the cooling load demand. The paper presents a short introduction for the desiccant systems. A mathematical model of a selected system has been developed and a simulation has been performed in order to investigate the system performance at different working conditions and an optimum design of the system structure is established. The results showed a technical feasibility of the system working under the Libyan climatic conditions with a reasonable COP at temperatures that can be obtained through the solar reactivation system. Discussion of the results and the recommendations for future work are proposed.

Keywords: computer program, solar desiccant wheel cooling, system modelling, simulation, technical feasibility

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Authors: Kasirga Yildirak, Ismail Gur

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We propose a model to measure hail risk of an Agricultural Insurance portfolio. Hail is one of the major catastrophic event that causes big amount of loss to an insurer. Moreover, it is very hard to predict due to its strange atmospheric characteristics. We make use of parcel based claims data on apricot damage collected by the Turkish Agricultural Insurance Pool (TARSIM). As our ultimate aim is to compute the loadings assigned to specific parcels, we build a portfolio risk model that makes use of PD and the severity of the exposures. PD is computed by Spherical-Linear and Circular –Linear regression models as the data carries coordinate information and seasonality. Severity is mapped into integer brackets so that Probability Generation Function could be employed. Individual regressions are run on each clusters estimated on different criteria. Loss distribution is constructed by Panjer Recursion technique. We also show that one risk-one crop model can easily be extended to the multi risk–multi crop model by assuming conditional independency.

Keywords: hail insurance, spherical regression, circular regression, spherical clustering

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Authors: Sarah Abdourraziq, Rachid El Bachtiri

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The solar power source for pumping water is one of the most promising areas in photovoltaic applications. The implementation of these systems allows to protect the environment and reduce the CO₂ gas emission compared to systems trained by diesel generators. This paper presents a comparative study between the photovoltaic pumping system driven by DC motor, and AC motor to define the optimum design of this application. The studied system consists of PV array, DC-DC Boost Converter, inverter, motor-pump set and storage tank. The comparison was carried out to define the characteristics and the performance of each system. Each subsystem is modeled in order to simulate the whole system in MATLAB/ Simulink. The results show the efficiency of the proposed technique.

Keywords: photovoltaic water pumping system, DC motor-pump, AC motor-pump, DC-DC boost converter

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Authors: Bunthida Chunngam, Thanyanan Worasesthaphong

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This research had objective to develop of the website learning the local wisdom in Phra Nakhon Si Ayutthaya province and studied satisfaction of system user. This research sample was multistage sample for 100 questionnaires, analyzed data to calculated reliability value with Cronbach’s alpha coefficient method α=0.82. This system had 3 functions which were system using, system feather evaluation and system accuracy evaluation which the statistics used for data analysis was descriptive statistics to explain sample feature so these statistics were frequency, percentage, mean and standard deviation. This data analysis result found that the system using performance quality had good level satisfaction (4.44 mean), system feather function analysis had good level satisfaction (4.11 mean) and system accuracy had good level satisfaction (3.74 mean).

Keywords: website, learning, local wisdom, Phra Nakhon Si Ayutthaya province

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Authors: A. Harrouz, A. Benatiallah, O. Harrouz

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This paper presents the search for errors in the measurement instruments in a dynamic system of metering liquid or gas and sees the tolerance defined by the international standards and recommendations. We will implement a program on MATLAB/Simulink which is calculated based on the ISO-5167. This program will take the system parameters on considerations such as: the willingness plates, the size of the orifice, the given design conditions, reference conditions, find pressure drop for a given flow, or flow for a loss of given load. The results are considered very good and satisfactory because the errors identified of measuring instruments system are within the margin of error limit by the regulations.

Keywords: analyzing, control, gas, meters system

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Authors: Sogo Angel Olofinbiyi

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There have been widespread assumptions across the globe that the root cause of Boko Haram terrorism in Nigeria is religious rather than socio-economic. An investigation into this dichotomy allowed this study to fully demonstrate that the root cause of Boko Haram’s terrorist actions emanates from the non-fulfillment of socio-economic goals that are prompted by the violation of fundamental human rights, corruption, poverty, unconstitutional and undemocratic practices in the northern part of the Nigerian state. To achieve its aim of establishing the root cause of the terrorism crisis in the latter country, the study critically appraised the socio-economic context of the insurgency by adopting one-on-one in-depth interviews involving forty (40) participants to interrogate the phenomenon. Empirical evidence from the study demonstrated that the evolution of Boko Haram terrorism was a response to socio-economic phlebotomy, political and moral putrescence, and the dehumanization of people that stem from a combination of decades of mismanagement and pervasive corruption by various Nigerian leaders. The study concludes that, as long as the endemic socio-economic problems caused by global capitalism vis-a-vis unequal hegemonic power exchange as expressed in socio-political, ethno-religious and cultural forms persist in the Nigerian society, the terrorism insurgency will recur and remain an inevitable enterprise and indeed a normal social reaction to every undesirable state of affairs. Based on the findings, the study urges the need for the amelioration of the conditions of the vast majority of the Nigerian populace by making socio-economic facilities available to them through the political state.

Keywords: Boko Haram Terrorism, insurgency, socio-economic, religious injunctions

Procedia PDF Downloads 183