Search results for: fault tree analysis (FTA)

Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

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Fault tolerance and data security are two important issues in modern communication systems. During the transmission of data between the sender and receiver, errors may occur frequently. Therefore, the sender must re-transmit the data to the receiver in order to correct these errors, which makes the system very feeble. To improve the scalability of the scheme, we present a proxy signature scheme with fault tolerance over an efficient and secure authenticated key agreement protocol based on the improved RSA system. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties.

Keywords: fault tolerance, improved RSA, key agreement, proxy signature

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Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

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This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

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Authors: Saba Arif, Anam Nadeem, Roman Kalvin, Muzaffar Ali, Burhan Ali, Juntakan Taweekun

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Globally transportation sector accounts for around 25% of energy demand and nearly 62% of oil consumed. Therefore, new energy sources are required to introduce for this huge demand replenishment of depleting conventional energy sources. Currently, biofuels such as Jatropha trees as an energy carrier for transportation sector are being utilized effectively round the globe. However, climate conditions at low altitudes with an average annual temperature above 20 degrees Celsius and rainfall of 300-1000mm are considered the most suitable environment for the efficient growth of Jatropha trees. The current study is providing a theoretical survey-based analysis to investigate the effect of rate of cultivation of jatropha trees on the reduction of fuel prices and its environmental benefits. The resulted study shows that jatropha tree’s 100 kg seeds give 80kg oil and the conversion process cost is very small as 890 PKR. Moreover, the extraction of oil from Jatropha tree is tax-free compared to other fuels. The analysis proved very essential for potential assessment of Jatropha regarding future energy fuel for transportation sector at global level. Additionally, it can be very beneficial for increment in the total amount of transportation fuel in Pakistan.

Keywords: jatropha tree, environmental impact, energy contents, theoretical survey

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Authors: Bendiabdellah Azzeddine, Cherif Bilal Djamal Eddine

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The three-phase power converter voltage structure is widely used in many power applications but its failure can lead to partial or total loss of control of the phase currents and can cause serious system malfunctions or even a complete system shutdown. To ensure continuity of service in all circumstances, effective and rapid techniques of detection and location of inverter fault is to be implemented. The present paper is dedicated to open-circuit fault detection in a three-phase two-level inverter fed induction motor. For detection purpose, the proposed contribution addresses the Park’s current vectors associated to a polar coordinates calculation tool to compute the exact value of the fault angle corresponding directly to the faulty IGBT switch. The merit of the proposed contribution is illustrated by experimental results.

Keywords: diagnosis, detection, Park’s vectors, polar coordinates, open-circuit fault, inverter, IGBT switch

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Authors: Ying Zhao, Xingyan Bin

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Semi-supervised clustering algorithms have been shown effective to improve clustering process with even limited supervision. However, semi-supervised hierarchical clustering remains challenging due to the complexities of expressing constraints for agglomerative clustering algorithms. This paper proposes novel semi-supervised agglomerative clustering algorithms to build a hierarchy based on a known reference tree. We prove that by enforcing distance constraints defined by a reference tree during the process of hierarchical clustering, the resultant tree is guaranteed to be consistent with the reference tree. We also propose a framework that allows the hierarchical tree generation be aware of levels of levels of the agglomerative tree under creation, so that metric weights can be learned and adopted at each level in a recursive fashion. The experimental evaluation shows that the additional cost of our contraint-based semi-supervised hierarchical clustering algorithm (HAC) is negligible, and our combined semi-supervised HAC algorithm outperforms the state-of-the-art algorithms on real-world datasets. The experiments also show that our proposed methods can improve clustering performance even with a small number of unevenly distributed labeled data.

Keywords: semi-supervised clustering, hierarchical agglomerative clustering, reference trees, distance constraints

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Authors: S. Masoud Barakati, Mohsen Rahmani Haredasht

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Recently, the use of T-type nested neutral point clamped (T-NNPC) converter has increased in medium voltage applications. However, the T-NNPC converter architecture's reliability and continuous operation are at risk by including semiconductor switches. Semiconductor switches are a prone option for open-circuit faults. As a result, fault-tolerant converters are required to improve the system's reliability and continuous functioning. This study's primary goal is to provide a fault-tolerant T-NNPC converter configuration. In the proposed design utilizing the cold reservation approach, a redundant phase is considered, which replaces the faulty phase once the fault is diagnosed in each phase. The suggested fault-tolerant configuration can be easily implemented in practical applications due to the use of a simple PWM control mechanism. The performance evaluation of the proposed configuration under different scenarios in the MATLAB-Simulink environment proves its efficiency.

Keywords: T-type nested neutral point clamped converter, reliability, continuous operation, open-circuit faults, fault-tolerant converters

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

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Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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Authors: I. A. Farhat, M. Bin Hasan

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A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

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Authors: Aymen Arfaoui, Abdelkader Soumaya, Ali Kadri, Noureddine Ben Ayed

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The Tunisian dorsal backland is located on the Eastern Atlas side of the Maghrebides (North Africa). The analysis of collected field data in the Rouas and Ruissate mountains area allowed us to develop new interpretations for its structural framework. Our kinematic analysis of fault-slip data reveals the presence of an extensional tectonic regime with NE-SW Shmin, characterizing the Mesozoic times. In addition, geophysical data shows that the synsedimentary normal faulting is accompanied by thickness variations of sedimentary sequences and Triassic salt movements. Then, after the Eurasia-Africa plate’s convergence during the Eocene, compressive tectonic deformations affected and reactivated the inherited NW-SE and N-S trending normal faults as dextral strike-slip and reverse faults, respectively. This tectonic inversion, with compression to the transpressional tectonic regime and NW-SE SHmax, continued during the successive shortening phases of the upper Miocene and Quaternary. The geometry of the Rouas and Ruissate belt is expressed as a fault propagation fold, affecting Jurassic and Cretaceous deposits. The Triassic evaporates constitute the decollement levels, facilitating the detachment and deformation of the sedimentary cover. The backland of this thrust belt is defined by NNE-SSW trending imbrication features that are controlled by a basement N-S fault.

Keywords: Tunisian dorsal backland, fault slip data; synsedimentary faults, tectonic inversion, decollement level, fault propagation fold

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Authors: Koushik Roy, Sourav Gur, Sudib K. Mishra

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Evidence of pulse type features in near-fault ground motions has raised serious concern to the structural engineering community, in view of their possible implications on the behavior of structures located on the fault regions. Studies in the recent past explore the effects of pulse type ground motion on the special structures, such as transmission towers in view of their high flexibility. Identically, long period sloshing of liquid in the storage tanks under dynamic loading might increase their failure vulnerability under near-fault pulses. Therefore, the behavior of the elevated liquid storage tank is taken up in this study. Simple lumped mass model is considered, with the bilinear force-deformation hysteresis behavior. Set of near-fault seismic ground acceleration time histories are adopted for this purpose, along with the far-field records for comparison. It has been demonstrated that pulse type motions lead to significant increase of the responses; in particular, sloshing of the fluid mass could be as high as 5 times, then the far field counterpart. For identical storage capacity, slender tanks are found to be more vulnerable than the broad ones.

Keywords: far-field motion, hysteresis, liquid storage tank, near fault earthquake, sloshing

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Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

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This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

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Authors: Abhimanyu Kumar, Chirag Gupta

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This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.

Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI

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Authors: Iman Nezamzadeh, Ali Faghih, Behnam Oveisi

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In order to reduce earthquake hazards in urban areas, it is necessary to perform comprehensive studies to understand the dynamics of the active faults and identify potentially high risk areas. The fault slip-rates in Late Quaternary sediment are critical indicators of seismic hazard and also provide valuable data to recognize young crustal deformations. To measure slip-rates accurately, is needed to displacement of geomorphic markers and ages of quaternary sediment samples of alluvial deposit that deformed by movements on fault. In this study we produced information about Intermediate term slip rate of Sabzpushan Fault Zone (SPF) within the central part of the Zagros Mountains of Iran using OSL dating technique to make better analysis of seismic hazard and seismic risk reduction for Shiraz city. For this purpose identifiable geomorphic fluvial surfaces help us to provide a reference frame to determine differential or absolute horizontal and vertical deformation. Optically stimulated luminescence (OSL) is an alternative and independent method of determining the burial age of mineral grains in Quaternary sediments. Field observation and satellite imagery show geomorphic markers that deformed horizontally along the Sabzpoushan Fault. Here, drag folds is forming because of evaporites material of Miocen Formation. We estimate 2.8±0.5 mm/yr (mm/y) horizontal slip rate along the Sabzpushan fault zone, where ongoing deformation is involve with drug folding. The Soltan synclinal structure, close to the Sabzpushan fault, shows slight uplift rate due to active core-extrousion.

Keywords: slip rate, active tectonics, OSL, geomorphic markers, Sabzpushan Fault Zone, Zagros, Iran

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Mehrdad Nouri Khajavi, Gollamhassan Payganeh, Mohsen Fallah Tafti

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Fault diagnosis is an important aspect of maintaining rotating machinery health and increasing productivity. Many researches has been done in this regards. Many faults such as unbalance, misalignment, looseness, bearing faults, etc. have been considered and diagnosed with different techniques. Most of the researches in fault diagnosis of rotating machinery deal with single fault. Where as in reality faults usually occur simultaneously and it is, therefore, necessary to recognize them at the same time. In this research, two of the most common faults namely unbalance and misalignment have been considered simultaneously with different intensity and then identified and classified with the use of Multi-Layer Perception Neural Network (MLPNN). Processed Vibration signals are used as the input to the MLPNN, and the class of mixed unbalancy, and misalignment is the output of the NN.

Keywords: unbalance, parallel misalignment, combined faults, vibration signals

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Authors: Mohamed Shaban, Ali Alfallah

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This paper describes an application for testing of a fault indicator but it could be used for other network protection testing. The application is created in the LabVIEW environment and consists of three parts. The first part of the application is determined for transient phenomenon generation and imitates voltage and current transient signal at ground fault originate. The second part allows to set sequences of trend for each current and voltage output signal, up to six trends for each phase. The last part of the application generates harmonic signal with continuously controllable amplitude of current or voltage output signal and phase shift of each signal can be changed there. Further any sub-harmonics and upper harmonics can be added to selected current output signal

Keywords: signal generator-fault indicator, harmonic signal generator, voltage output

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Authors: Sibongiseni Thabethe, Ian Korir

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The effective management of spent fuel pool (SFP) safety has been raised as one of the emerging issues to further enhance nuclear installation safety after the Fukushima accident on March 11, 2011. Before then, SFP safety-related issues have been mainly focused on (a) controlling the configuration of the fuel assemblies in the pool with no loss of pool coolants and (b) ensuring adequate pool storage space to prevent fuel criticality owing to chain reactions of the fission products and the ability for neutron absorption to keep the fuel cool. A probabilistic safety (PSA) assessment was performed using the systems analysis program for hands-on integrated reliability evaluations (SAPHIRE) computer code. Event and fault tree analysis was done to develop a PSA model for the Koeberg SFP. We present preliminary PSA results of events that lead to boiling and cause fuel uncovering, resulting in possible fuel damage in the Koeberg SFP.

Keywords: computer code, fuel assemblies, probabilistic risk assessment, spent fuel pool

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Authors: Thanh Nga Thai

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A major issue in air transportation is in flight safety. Recent developments in control engineering have an attractive potential for resolving new issues related to guidance, navigation, and control of flying vehicles. Many future atmospheric missions will require increased on board autonomy including fault diagnosis and the subsequent control and guidance recovery actions. To improve designing system diagnostic, an efficient FDI- fault detection and identification- methodology is necessary to achieve. Contribute to characteristic of different faults in sensor and actuator in the view of mathematics brings a lot of profit in some condition changes in the system. This research finds some profit to reduce a trade-off to achieve between fault detection and performance of the closed loop system and cost and calculated in simulation.

Keywords: fault detection and identification, sensor faults, actuator faults, flight control system

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Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

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Due to the rapid growth in modern communication systems, fault tolerance and data security are two important issues in a secure transaction. During the transmission of data between the sender and receiver, errors may occur frequently. Therefore, the sender must re-transmit the data to the receiver in order to correct these errors, which makes the system very feeble. To improve the scalability of the scheme, we present a secure proxy signature scheme with fault tolerance over an efficient and secure authenticated key agreement protocol based on RSA system. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties.

Keywords: proxy signature, fault tolerance, rsa, key agreement protocol

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Authors: Olatunde Sunday Eludoyin, Charles Obiechina Olisa

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The study examined the spatial interactions between earthworm abundance (EA) and tree growth characteristics in ecological belts of Western Niger Delta, Nigeria. Eight 20m x 20m quadrat were delimited in the natural vegetation in each of the rainforest (RF), mangrove (M), fresh water swamp (FWS), and guinea savanna (GS) ecological belts to gather data about the tree species (TS) characteristics which included individual number of tree species (IN), diversity (Di), density (De) and richness (Ri). Three quadrats of 1m x 1m were delineated in each of the 20m x 20m quadrats to collect earthworm species the topsoil (0-15cm), and subsoil (15-30cm) and were taken to laboratory for further analysis. Descriptive statistics and inferential statistics were used for data analysis. Findings showed that a total of 19 earthworm species was found, with 58.5% individual species recorded in the topsoil and 41.5% recorded in the subsoil. The total population ofEudriliuseugeniae was predominantly highest in both topsoil (38.4%) and subsoil (27.1%). The total population of individual species of earthworm was least in GS in the topsoil (11.9%) and subsoil (8.4%). A total of 40 different species of TS was recorded, of which 55.5% were recorded in FWS, while RF was significantly highest in the species diversity(0.5971). Regression analysis revealed that Ri, IN, DBH, Di, and De of trees explained 65.9% of the variability of EA in the topsoil, while 46.9 % of the variability of earthworm abundance was explained by the floristic parameters in the subsoil.Similarly, correlation statistics revealed that in the topsoil, EA is positively and significantly correlated with Ri (r=0.35; p<0.05), IN (r=0.523; p<0.05) and De (r=0.469; p<0.05) while DBH was negatively and significantly correlated with earthworm abundance (r=-0.437; p<0.05). In the subsoil, only Ri and DBH correlated significantly with EA. The study concluded that EA in the study locations was highly influenced by tree growth species especially Ri, IN, DBH, Di, and De. The study recommended that the TSabundance should be improved in the study locations to ensure the survival of earthworms for ecosystem functions.

Keywords: interactions, earthworm abundance, tree growth, ecological zones, western niger delta

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

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Authors: Madhu Jain, Rakesh Kumar Meena

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This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

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Authors: Henry Pariaman, Iwa Garniwa, Isti Surjandari, Bambang Sugiarto

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Availability of a complex system of thermal power plant is strongly influenced by the reliability of spare parts and maintenance management policies. A reliability-centered maintenance (RCM) technique is an established method of analysis and is the main reference for maintenance planning. This method considers the consequences of failure in its implementation, but does not deal with further risk of down time that associated with failures, loss of production or high maintenance costs. Risk-based maintenance (RBM) technique provides support strategies to minimize the risks posed by the failure to obtain maintenance task considering cost effectiveness. Meanwhile, condition-based maintenance (CBM) focuses on monitoring the application of the conditions that allow the planning and scheduling of maintenance or other action should be taken to avoid the risk of failure prior to the time-based maintenance. Implementation of RCM, RBM, CBM alone or combined RCM and RBM or RCM and CBM is a maintenance technique used in thermal power plants. Implementation of these three techniques in an integrated maintenance will increase the availability of thermal power plants compared to the use of maintenance techniques individually or in combination of two techniques. This study uses the reliability, risks and conditions-based maintenance in an integrated manner to increase the availability of thermal power plants. The method generates MPI (Priority Maintenance Index) is RPN (Risk Priority Number) are multiplied by RI (Risk Index) and FDT (Failure Defense Task) which can generate the task of monitoring and assessment of conditions other than maintenance tasks. Both MPI and FDT obtained from development of functional tree, failure mode effects analysis, fault-tree analysis, and risk analysis (risk assessment and risk evaluation) were then used to develop and implement a plan and schedule maintenance, monitoring and assessment of the condition and ultimately perform availability analysis. The results of this study indicate that the reliability, risks and conditions-based maintenance methods, in an integrated manner can increase the availability of thermal power plants.

Keywords: integrated maintenance techniques, availability, thermal power plant, MPI, FDT

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB / Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind power generation, back to back PWM converter, default switching

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Authors: Ramish, Farhan Khalique Awan

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Kinematic redundancy within the manipulators presents extended dexterity and manipulability to the manipulators. Redundant serial robotic manipulators are very popular in industries due to its competencies to keep away from singularities during normal operation and fault tolerance because of failure of one or more joints. Such fault tolerant manipulators are extraordinarily beneficial in applications where human interference for repair and overhaul is both impossible or tough; like in case of robotic arms for space programs, nuclear applications and so on. The design of this sort of fault tolerant serial 3 DoF manipulator is presented in this paper. This work was the extension of the author’s previous work of designing the simple 3R serial manipulator. This work is the realization of the previous design with optimizing the link lengths for incorporating the feature of fault tolerance. Various measures have been followed by the researchers to quantify the fault tolerance of such redundant manipulators. The fault tolerance in this work has been described in terms of the worst-case measure of relative manipulability that is, in fact, a local measure of optimization that works properly for certain configuration of the manipulators. An optimum fault tolerant Jacobian matrix has been determined first based on prescribed null space properties after which the link parameters have been described to meet the given Jacobian matrix. A solid model of the manipulator was then developed to realize the mathematically rigorous design. Further work was executed on determining the dynamic properties of the fault tolerant design and simulations of the movement for various trajectories have been carried out to evaluate the joint torques. The mathematical model of the system was derived via the Euler-Lagrange approach after which the same has been tested using the RoboAnalyzer© software. The results have been quite in agreement. From the CAD model and dynamic simulation data, the manipulator was fabricated in the workshop and Advanced Machining lab of NED University of Engineering and Technology.

Keywords: fault tolerant, Graham matrix, Jacobian, kinematics, Lagrange-Euler

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Authors: Jian Yang, Atsushi Yagi

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Tree-grass coexistence system is of great importance for forest ecology. Mathematical models are being proposed to study the dynamics of tree-grass coexistence and the stability of the systems. However, few of the models concentrates on spatial dynamics of the tree-grass coexistence. In this study, we modified an age-structured continuous-space population model for forests, obtaining an age-structured continuous-space population model for the tree-grass competition model. In the model, for thermal competitions, adult trees can out-compete grass, and grass can out-compete seedlings. We mathematically studied the model to make sure tree-grass coexistence solutions exist. Numerical experiments demonstrated that a fraction of area that trees or grass occupies can affect whether the coexistence is stable or not. We also tried regulating the mortality of adult trees with other parameters and the fraction of area trees and grass occupies were fixed; results show that the mortality of adult trees is also a factor affecting the stability of the tree-grass coexistence in this model.

Keywords: population-structured models, stabilities of ecosystems, thermal competitions, tree-grass coexistence systems

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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