Search results for: RLS identification algorithm

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

Procedia PDF Downloads 129

Authors: Colin S. Chen, Chien-Jung Tien, Hsin-Jan Huang

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For weathering studies, the change of chemical constituents by biodegradation effect in diesel-contaminated soils are important factors to be considered, especially when there is a prolonged period of weathering processes. The objective was to evaluate biodegradation effects onto hydrocarbon fingerprinting and distribution patterns of diesel fuels, fuel source screening and differentiation, source-specific marker compounds, and diagnostic ratios of diesel fuel constituents by laboratory and field studies. Biodegradation processes of diesel contaminated soils were evaluated by experiments lasting for 15 and 12 months, respectively. The degradation of diesel fuel in top soils was affected by organic carbon content and biomass of microorganisms in soils. Higher depletion of total petroleum hydrocarbon (TPH), n-alkanes, and polynuclear aromatic hydrocarbons (PAHs) and their alkyl homologues was observed in soils containing higher organic carbon content and biomass. Decreased ratio of selected isoprenoids (i.e., pristane (Pr) and phytane (Ph)) including n-C17/pristane and n-C18/phytane was observed. The ratio of pristane/phytane was remained consistent for a longer period of time. At the end of the experimental period, a decrease of pristane/phytane was observed. Biomarker compounds of bicyclic sesquiterpanes (BS) were less susceptible to the effects of biodegradation. The ratios of characteristic factors such as C15 sesquiterpane/ 8β(H)-drimane (BS3/BS5), C15 sesquiterpane/ 8β(H)-drimane (BS4/BS5), 8β(H)-drimane/8β(H)-homodrimane (BS5/BS10), and C15 sesquiterpane/8β(H)-homodrimane (BS3/BS10) could be adopted for source identification of diesel fuels in top soil. However, for biodegradation processes lasted for six months but shorter than nine months, only BS3/BS5 and BS3/BS10 could be distinguished in two diesel fuels. In subsoil experiments (contaminated soil located 50 cm below), the ratios of characteristic factors including BS3/BS5, BS4/BS5, and BS5/BS10 were valid for source identification of two diesel fuels for nine month biodegradation. At the early stage of contamination, biomass of soil decreased significantly. However, 6 and 7 dominant species were found in soils in top soil experiments, respectively. With less oxygen and nutrients in subsoil, less biomass of microorganisms was observed in subsoils. Only 2 and 4 diesel-degrading species of microorganisms were identified in two soils, respectively. Parameters of double ratio such as fluorene/C1-fluorene: C2-phenanthrene/C3-phenanthrene (C0F/C1F:C2P/C3P) in both top and subsoil, C2-naphthalene/C2-phenanthrene: C1-phenanthrene/C3-phenanthrene (C2N/C2P:C1P/C3P), and C1-phenanthrene/C1-fluorene: C3-naphthalene/C3-phenanthrene (C1P/C1F:C3N/C3P) in subsoil could serve as forensic indicators in diesel contaminated sites. BS3/BS10:BS4/BS5 could be used in 6 to 9 months of biodegradation processes. Results of principal component analysis (PCA) indicated that source identification of diesel fuels in top soil could only be perofrmed for weathering process less than 6 months. For subsoil, identification can be conducted for weathering process less than 9 months. Ratio of isoprenoids (pristane and phytane) and PAHs might be affected by biodegradation in spilled sites. The ratios of bicyclic sesquiterpanes could serve as forensic indicators in diesel-contaminated soils. Finally, source identification was attemped for samples collected from different fuel contaminated sites by using the unique pattern of sesquiterpanes. It was anticipated that the information generated from this study would be adopted by decision makers to evaluate the liability of cleanup in diesel contaminated sites.

Keywords: biodegradation, diagnostic ratio, diesel fuel, environmental forensics

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Authors: Ersan Aktas, Eren Turanoğuz

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In this study, the quad-electrical rotor driven unmanned aerial vehicle system is designed and modeled using fundamental dynamic equations. After that, mechanical, electronical and control system of the air vehicle are designed and implemented. Brushless motor speeds are altered via electronic speed controllers in order to achieve desired controllability. The vehicle's fundamental Euler angles (i.e., roll angle, pitch angle, and yaw angle) are obtained via AHRS sensor. These angles are provided as an input to the control algorithm that run on soft the processor on the electronic card. The vehicle control algorithm is implemented in the electronic card. Controller is designed and improved for each Euler angles. Finally, flight tests have been performed to observe and improve the flight characteristics.

Keywords: quadrotor, UAS applications, control architectures, PID

Procedia PDF Downloads 365

Authors: M. M. Othman, Walid El-Khattam, Y. G. Hegazy, A. Y. Abdelaziz

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This paper presents a method for finding the optimal location and capacity of dispatchable DGs connected to the distribution feeders for optimal planning for a specified power loss without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37-nodes feeder. The results that are validated by comparing it with results obtained from other competing methods show the effectiveness, accuracy and speed of the proposed method.

Keywords: distributed generators, firefly technique, optimization, power loss

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Authors: Khaleel Saleh Al-Rababah

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Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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Authors: Neslihan Ozman Say, Jim Gilmour, Pratik Desai, William Zimmerman

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Landfill leachate treatment has been attracting researchers recently for various environmental and economical reasons. Leachate discharge to receiving waterbodies without treatment causes serious detrimental effects including partial oxygen depletion due to high biological oxygen demand (BOD) and chemical oxygen demand (COD) concentrations besides toxicity of heavy metals it contains and high ammonia concentrations. In this study, it is aimed to show microalgal ammonia removal performances of a wild microalgae consortia as an alternative treatment method and determine the dominant leachate tolerant species for this consortia. For the microalgae species identification experiments a microalgal consortium which has been isolated from a local pond in Sheffield inoculated in %5 diluted raw landfill leachate and acclimated to the leachate by batch feeding for a month. In order to determine the most tolerant microalgal consortium, four different untreated landfill leachate samples have been used as diluted in four different ratios as 5%, 10%, 20%, and 40%. Microalgae cell samples have been collected from all experiment sets and have been examined by using 18S rDNA sequencing and specialised gel electrophoresis which are adapted molecular biodiversity methods. The best leachate tolerant algal consortium is being used in order to determine ammonia removal performances of the culture in a microbubble assisted photobioreactor (PBR). A porous microbubble diffuser which is supported by a fluidic oscillator is being used for dosing CO₂ and air mixture in the PBR. It is known that high mass transfer performance of microbubble technology provides a better removal efficiency and a better mixing in the photobioreactor. Ammonia concentrations and microalgal growth are being monitored for PBR currently. It is aimed to present all the results of the study in final paper submission.

Keywords: ammonia removal from leachate, landfill leachate treatment, microalgae species identification, microbubble assisted photobioreactors

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Saule Mussabekova

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A number of chemical elements widely presented in the nature is seldom met in people and vice versa. This is a peculiarity of accumulation of elements in the body, and their selective use regardless of widely changed parameters of external environment. Microelemental identification of human hair and particularly dead body is a new step in the development of modern forensic medicine which needs reliable criteria while identifying the person. In the condition of technology-related pressing of large industrial cities for many years and specific for each region multiple-factor toxic effect from many industrial enterprises it’s important to assess actuality and the role of researches of human hair while assessing degree of deposition with specific pollution. Hair is highly sensitive biological indicator and allows to assess ecological situation, to perform regionalism of large territories of geological and chemical methods. Besides, monitoring of concentrations of chemical elements in the regions of Kazakhstan gives opportunity to use these data while performing forensic medical identification of dead bodies of unknown persons. Methods based on identification of chemical composition of hair with further computer processing allowed to compare received data with average values for the sex, age, and to reveal causally significant deviations. It gives an opportunity preliminary to suppose the region of residence of the person, having concentrated actions of policy for search of people who are unaccounted for. It also allows to perform purposeful legal actions for its further identification having created more optimal and strictly individual scheme of personal identity. Hair is the most suitable material for forensic researches as it has such advances as long term storage properties with no time limitations and specific equipment. Besides, quantitative analysis of micro elements is well correlated with level of pollution of the environment, reflects professional diseases and with pinpoint accuracy helps not only to diagnose region of temporary residence of the person but to establish regions of his migration as well. Peculiarities of elemental composition of human hair have been established regardless of age and sex of persons residing on definite territories of Kazakhstan. Data regarding average content of 29 chemical elements in hair of population in different regions of Kazakhstan have been systemized. Coefficients of concentration of studies elements in hair relative to average values around the region have been calculated for each region. Groups of regions with specific spectrum of elements have been emphasized; these elements are accumulated in hair in quantities exceeding average indexes. Our results have showed significant differences in concentrations of chemical elements for studies groups and showed that population of Kazakhstan is exposed to different toxic substances. It depends on emissions to atmosphere from industrial enterprises dominating in each separate region. Performed researches have showed that obtained elemental composition of human hair residing in different regions of Kazakhstan reflects technogenic spectrum of elements.

Keywords: analysis of elemental composition of hair, forensic medical research of hair, identification of unknown dead bodies, microelements

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Authors: Abla A. Ali, Heba A. Abd El Razik, Nadia A. Kotb, Amany A. Bayoumi, Laila A. Rashed

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The detection of human skin through mRNA-based profiling is a very useful tool for forensic investigations. The aim of this study was definitive identification of human skin at different time intervals using an mRNA marker late cornified envelope gene 1C. Ten middle-aged healthy volunteers of both sexes were recruited for this study. Skin samples controlled with blood samples were taken from the candidates to test for the presence of our targeted mRNA marker. Samples were kept at dry dark conditions to be tested at different time intervals (24 hours, one week, three weeks and four weeks) for detection and relative quantification of the targeted marker by RT PCR. The targeted marker could not be detected in blood samples. The targeted marker showed the highest mean value after 24 hours (11.90 ± 2.42) and the lowest mean value (7.56 ± 2.56) after three weeks. No marker could be detected at four weeks. This study verified the high specificity and sensitivity of mRNA marker in the skin at different storage times up to three weeks under the study conditions.

Keywords: human skin, late cornified envelope gene 1C, mRNA marker, time intervals

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Authors: G. Shabib, Esam H. Abd-Elhameed, G. Magdy

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In this paper, a comparison of discrete time PID, PSS controllers is presented through small signal stability of power system comprising of one machine connected to infinite bus system. This comparison achieved by using a new approach of discretization which converts the S-domain model of analog controllers to a Z-domain model to enhance the damping of a single machine power system. The new method utilizes the Plant Input Mapping (PIM) algorithm. The proposed algorithm is stable for any sampling rate, as well as it takes the closed loop characteristic into consideration. On the other hand, the traditional discretization methods such as Tustin’s method is produce satisfactory results only; when the sampling period is sufficiently low.

Keywords: PSS, power system stabilizer PID, proportional-integral-derivative PIM, plant input mapping

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Authors: Xinli Chen, Xue Su

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In the urban rail transit CBTC system, interlocking is considered one of the most basic sys-tems, which has the characteristics of logical complexity and high-security requirements. The development and verification of traditional interlocking subsystems are entirely manual pro-cesses and rely too much on the designer, which often hides many uncertain factors. In order to solve this problem, this article is based on the multi-template nib tracking algorithm for model construction and verification, achieving the main safety attributes and using SCADE for formal verification. Experimental results show that this method helps to improve the quality and efficiency of interlocking software.

Keywords: computer interlocking subsystem, penpoint tracking, communication-based train control system, multi-template tip tracking

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Authors: Waad Al Saleemi, Badriya Al Adawi, Zaaima Al Jabri, Sahim Al Ghafri, Jalila Al Hadhramia

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Objectives: Using standard lab methods, a positive blood culture requires a minimum of two days (two occasions of overnight incubation) to obtain a final identification (ID) and antimicrobial susceptibility results (AST) report. In this study, we aimed to evaluate the accuracy and precision of identification and antimicrobial susceptibility testing of an alternative method (direct method) that will reduce the turnaround time by 24 hours. This method involves the direct inoculation of positive blood culture broths into the Phoenix system using serum separation tubes (SST). Method: This prospective study included monomicrobial-positive blood cultures obtained from January 2022 to May 2023 in SQUH. Blood cultures containing a mixture of organisms, fungi, or anaerobic organisms were excluded from this study. The result of the new “direct method” under study was compared with the current “standard method” used in the lab. The accuracy and precision were evaluated for the ID and AST using Clinical and Laboratory Standards Institute (CLSI) recommendations. The categorical agreement, essential agreement, and the rates of very major errors (VME), major errors (ME), and minor errors (MIE) for both gram-negative and gram-positive bacteria were calculated. Passing criteria were set according to CLSI. Result: The results of ID and AST were available for a total of 158 isolates. Of 77 isolates of gram-negative bacteria, 71 (92%) were correctly identified at the species level. Of 70 isolates of gram-positive bacteria, 47(67%) isolates were correctly identified. For gram-negative bacteria, the essential agreement of the direct method was ≥92% when compared to the standard method, while the categorical agreement was ≥91% for all tested antibiotics. The precision of ID and AST were noted to be 100% for all tested isolates. For gram-positive bacteria, the essential agreement was >93%, while the categorical agreement was >92% for all tested antibiotics except moxifloxacin. Many antibiotics were noted to have an unacceptable higher rate of very major errors including penicillin, cotrimoxazole, clindamycin, ciprofloxacin, and moxifloxacin. However, no error was observed in the results of vancomycin, linezolid, and daptomycin. Conclusion: The direct method of ID and AST for positive blood cultures using SST is reliable for gram negative bacteria. It will significantly decrease the turnaround time and will facilitate antimicrobial stewardship.

Keywords: bloodstream infection, oman, direct ast, blood culture, rapid identification, antimicrobial susceptibility, phoenix, direct inoculation

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Authors: Rajamani Doraiswami, Lahouari Cheded

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Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Joseph Marae Djouda, Ashraf Kasmi, François Hild

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Fused filament fabrication is one of the most widespread additive manufacturing techniques because of its low-cost implementation. Its initial development was based on part fabrication with thermoplastic materials. The influence of the manufacturing parameters such as the filament orientation through the nozzle, the deposited layer thickness, or the speed deposition on the mechanical properties of the parts has been widely experimentally investigated. It has been recorded the remarkable variations of the anisotropy in the function of the filament path during the fabrication process. However, there is a lack in the development of constitutive models describing the mechanical properties. In this study, integrated digital image correlation (I-DIC) is used for the identification of mechanical constitutive parameters of two configurations of ABS samples: +/-45° and so-called “oriented deposition.” In this last, the filament was deposited in order to follow the principal strain of the sample. The identification scheme based on the gap reduction between simulation and the experiment directly from images recorded from a single sample (single edge notched tension specimen) is developed. The macroscopic and mesoscopic analysis are conducted from images recorded in both sample surfaces during the tensile test. The elastic and elastoplastic models in isotropic and orthotropic frameworks have been established. It appears that independently of the sample configurations (filament orientation during the fabrication), the elastoplastic isotropic model gives the correct description of the behavior of samples. It is worth noting that in this model, the number of constitutive parameters is limited to the one considered in the elastoplastic orthotropic model. This leads to the fact that the anisotropy of the architectured 3D printed ABS parts can be neglected in the establishment of the macroscopic behavior description.

Keywords: elastic anisotropy, fused filament fabrication, Acrylonitrile butadiene styrene, I-DIC identification

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Authors: M. Ramadan, B. Salah

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This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.

Keywords: lean manufacturing, Industry 4.0, radio frequency identification, value stream mapping

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

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Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution.

Keywords: single machine scheduling, number of tardy jobs, heuristi, lower and upper bounds

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: genetic algorithm, rsm, biodiesel, karanja

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Authors: Bo-Huei Huang, Chih-Hsun Yang, Meng-Tsan Tsai

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Optical coherence tomography (OCT) enables to provide advantages of noninvasive imaging, high resolution, and high imaging speed. In this study, we integrated OCT and a CW laser for tumor diagnosis and treatment. The axial and transverse resolutions of the developed OCT system are 3 μm and 1 μm, respectively. The frame rate of OCT system is 30 frames/s. In this study, the tumor cells were implanted into the mice skin and scanned by OCT to observe the morphological and angiographic changes. With OCT imaging, 3D microstructures and skin angiography of mice skin can be simultaneously acquired, which can be utilized for identification of the tumor distribution. Then, the CW laser beam can be accurately controlled to expose on the center of the tumor, according to the OCT results. Moreover, OCT was used to monitor the induced photothermolysis and to evaluate the treatment outcome. The results showed that OCT-guided laser therapy could efficiently improve the treatment outcome and the extra damage induced by CW can be greatly reduced. Such OCT-guided laser therapy system could be a potential tool for dermatological applications.

Keywords: optical coherence tomography, laser therapy, skin tumor, position guide

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Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

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Authors: Waheeda Jabbar, Ali Gul, Rida Noor, Sania Kurd, Saba Gulzar

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Hundreds of miners die from mining accidents each year due to poisonous gases found underground mining areas. This paper proposed an idea to protect the precious lives of mining workers. A supervising system is designed which is based on ZigBee wireless technique along with the smart protective helmets to detect real-time surveillance and it gives early warnings on presence of different poisonous gases in order to save mineworkers from any danger caused by these poisonous gases. A wireless sensor network is established using ZigBee wireless technique by integrating sensors on the helmet, apart from this helmet have embedded heartbeat sensor to detect the pulse rate and be aware of the physical or mental strength of a mineworker to increase the potential safety. Radio frequency identification (RFID) technology is used to find the location of workers. A ZigBee based base station is set-upped to control the communication. The idea is implemented and results are verified through experiment.

Keywords: Arduino, gas sensor (MQ7), RFID, wireless ZigBee

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

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Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: foreign direct investments, methods, statistics, analysis

Procedia PDF Downloads 331

Authors: Weizhi Zhong, Xiaoyi Lu, Lei Xu

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In order to solve the problem of inaccurate synchronization for distributed multiple-input multiple-output (MIMO) system in multipath environment, a golay pair aided timing synchronization method is proposed in this paper. A new synchronous training sequence based on golay pair is designed. By utilizing the aperiodic auto-correlation complementary property of the new training sequence, the fine timing point is obtained at the receiver. Simulation results show that, compared with the tradition timing synchronization approaches, the proposed algorithm can provide high accuracy in synchronization, especially under multipath condition.

Keywords: distributed MIMO system, golay pair, multipath, synchronization

Procedia PDF Downloads 247

Authors: Wafa’ Alsharafat, Khalid Batiha, Alaa Kassab

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Wireless sensor network (WSN) is comprised of a huge number of small and cheap devices known as sensor nodes. Usually, these sensor nodes are massively and deployed randomly as in Ad-hoc over hostile and harsh environment to sense, collect and transmit data to the needed locations (i.e., base station). One of the main advantages of WSN is that the ability to work in unattended and scattered environments regardless the presence of humans such as remote active volcanoes environments or earthquakes. In WSN expanding network, lifetime is a major concern. Clustering technique is more important to maximize network lifetime. Nature-inspired algorithms are developed and optimized to find optimized solutions for various optimization problems. We proposed Energy Efficient Firefly Algorithm to improve network lifetime as long as possible.

Keywords: wireless network, SN, Firefly, energy efficiency

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

Abstract:

Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: offshore fields of hydrocarbons of the Baltic Sea, development of offshore oil and gas fields, optimization of the field development scheme, solution of multicriteria tasks in oil and gas complex, quality management in oil and gas complex

Procedia PDF Downloads 200

Authors: Zahra Safaeian, Shila Goldasteh, Rouhollah Radjabi

Abstract:

Flowerflies of Syrphidae family is one of the largest families among the Diptera order that due to predatory habit of some species in larva stage has an important role for controlling aphids of the fields. In the present study, flowerflies fauna in the alfalfa fields of the north of Khouzestan were studied during 2012-2013. The species of the family were collected using appropriate methods including insect collecting sweeping net and Malaise traps. According to the fact that the shape of male genitalia in the male insect is important in identification of these species the male genitalia was separated from the body and microscopical slide was prepared then species identification was done considering the male genitalia, the patterns and figures on the abdomen and using available keys. Based on the finding four species of Sphaerophoria scripta, Sphaerophoria turkmenica, Melanostoma mellinu, Sphaerophoria ruppelli were collected and according to the abundance frequency of the collected species the most abundance was related to Sphaerophoria scripta, then Sphaerophoria turkmenica had the most abundance and the least abundance was related to Sphaerophoria ruppelli.

Keywords: syrphidae, fauna, alfalfa, Iran

Procedia PDF Downloads 394

Authors: Nanjiang Chen

Abstract:

In the backdrop of expanding urban landscapes, accurately assessing spatial openness is critical. Traditional visibility analysis methods grapple with discretization errors and inefficiencies, creating a gap in truly capturing the human experi-ence of space. Addressing these gaps, this paper introduces a distinct continuous visibility algorithm, a leap in measuring urban spaces from a human-centric per-spective. This study presents a methodological breakthrough by applying this algorithm to urban visibility analysis. Unlike conventional approaches, this tech-nique allows for a continuous range of visibility assessment, closely mirroring hu-man visual perception. By eliminating the need for predefined subdivisions in ray casting, it offers a more accurate and efficient tool for urban planners and architects. The proposed algorithm not only reduces computational errors but also demonstrates faster processing capabilities, validated through a case study in Bei-jing's urban setting. Its key distinction lies in its potential to benefit a broad spec-trum of stakeholders, ranging from urban developers to public policymakers, aid-ing in the creation of urban spaces that prioritize visual openness and quality of life. This advancement in urban analysis methods could lead to more inclusive, comfortable, and well-integrated urban environments, enhancing the spatial experience for communities worldwide.

Keywords: visual openness, spatial continuity, ray-tracing algorithms, urban computation

Procedia PDF Downloads 46