Search results for: semiconductor production monitoring

Authors: Andrey V. Timofeev, Dmitry Egorov

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This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: C-OTDR monitoring system, bimodal processing, LPboost, SVM

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Authors: Vedant Subhash

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This paper discusses the physics of the detection of thermal neutrons using thin-film coated semiconductor detectors. The thermal neutron detection efficiency as a function of film thickness is calculated for the front and back irradiation detector devices coated with ¹⁰B, ⁶LiF, and pure Li thin films. The detection efficiency for back irradiation devices is 4.15% that is slightly higher than that for front irradiation detectors, 4.0% for ¹⁰B films of thickness 2.4μm. The theoretically calculated thermal neutron detection efficiency using ¹⁰B film thickness of 1.1 μm for the back irradiation device is 3.0367%, which has an offset of 0.0367% from the experimental value of 3.0%. The detection efficiency values are compared and proved consistent with the given calculations.

Keywords: detection efficiency, neutron detection, semiconductor detectors, thermal neutrons

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Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

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Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

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Authors: Tengku Nilam Baizura, Noor Zalina Mahmood

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In Malaysia, landfilling is the most preferred method and most of it does not have the proper leachate treatment system which can cause environmental problems. Leachate is the major factor to river water pollution since most landfills are located near the river which is the main water resource for the country. The study aimed to estimate leachate production from landfills in Selangor. A simple mathematical modelling was used for the calculation of annual leachate volume. The estimate of identified landfill area (A) using Google Earth was multiplied by the annual rainfall (R). The product is expressed as volume (V). The data indicate that the leachate production is high even it is fully closed. It is important to design the efficient landfill and proper leachate treatment processes especially for the old/closed landfill. Extensive monitoring will be required to predict future impact.

Keywords: landfill, leachate, municipal solid waste management, waste disposal

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Authors: Keiko Sakai

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In Japan, all stages of public education aim to foster a zest for life. ‘Zest’ implies solving problems by oneself, using acquired knowledge and skills. It is related to the self-regulation of metacognition. To enhance this, establishing good learning habits is important. Tardiness in undergraduate students should be examined based on self-regulation. Accordingly, we focussed on self-monitoring and self-planning strategies among self-regulated learning factors to examine the causes of tardiness. This study examines the impact of self-monitoring and self-planning learning skills on the degree and reason for tardiness in undergraduate students. A questionnaire survey was conducted, targeted to undergraduate students in University X in the autumn semester of 2018. Participants were 247 (average age 19.7, SD 1.9; 144 males, 101 females, 2 no answers). The survey contained the following items and measures: school year, the number of classes in the semester, degree of tardiness in the semester (subjective degree and objective times), active participation in and action toward schoolwork, self-planning and self-monitoring learning skills, and reason for tardiness (open-ended question). First, the relation between strategies and tardiness was examined by multiple regressions. A statistically significant relationship between a self-monitoring learning strategy and the degree of subjective and objective tardiness was revealed, after statistically controlling the school year and the number of classes. There was no significant relationship between a self-planning learning strategy and the degree of tardiness. These results suggest that self-monitoring skills reduce tardiness. Secondly, the relation between a self-monitoring learning strategy and the reason of tardiness was analysed, after classifying the reason for tardiness into one of seven categories: ‘overslept’, ‘illness’, ‘poor time management’, ‘traffic delays’, ‘carelessness’, ‘low motivation’, and ‘stuff to do’. Chi-square tests and Fisher’s exact tests showed a statistically significant relationship between a self-monitoring learning strategy and the frequency of ‘traffic delays’. This result implies that self-monitoring skills prevent tardiness because of traffic delays. Furthermore, there was a weak relationship between a self-monitoring learning strategy score and the reason-for-tardiness categories. When self-monitoring skill is higher, a decrease in ‘overslept’ and ‘illness’, and an increase in ‘poor time management’, ‘carelessness’, and ‘low motivation’ are indicated. It is suggested that a self-monitoring learning strategy is related to an internal causal attribution of failure and self-management for how to prevent tardiness. From these findings, the effectiveness of a self-monitoring learning skill strategy for reducing tardiness in undergraduate students is indicated.

Keywords: higher-education, self-monitoring, self-regulation, tardiness

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Authors: N. Seemuang, T. McLeay, T. Slatter

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Worn tools have a direct effect on the surface finish and part accuracy. Tool condition monitoring systems have been developed over a long period and used to avoid a loss of productivity resulting from using a worn tool. However, the majority of tool monitoring research has applied expensive sensing systems not suitable for production. In this work, the cutting sound in turning machine was studied using microphone. Machining trials using seven cutting conditions were conducted until the observable flank wear width (FWW) on the main cutting edge exceeded 0.4 mm. The cutting inserts were removed from the tool holder and the flank wear width was measured optically. A microphone with built-in preamplifier was used to record the machining sound of EN24 steel being face turned by a CNC lathe in a wet cutting condition using constant surface speed control. The sound was sampled at 50 kS/s and all sound signals recorded from microphone were transformed into the frequency domain by FFT in order to establish the frequency content in the audio signature that could be then used for tool condition monitoring. The extracted feature from audio signal was compared to the flank wear progression on the cutting inserts. The spectrogram reveals a promising feature, named as ‘spindle noise’, which emits from the main spindle motor of turning machine. The spindle noise frequency was detected at 5.86 kHz of regardless of cutting conditions used on this particular CNC lathe. Varying cutting speed and feed rate have an influence on the magnitude of power spectrum of spindle noise. The magnitude of spindle noise frequency alters in conjunction with the tool wear progression. The magnitude increases significantly in the transition state between steady-state wear and severe wear. This could be used as a warning signal to prepare for tool replacement or adapt cutting parameters to extend tool life.

Keywords: tool wear, flank wear, condition monitoring, spindle noise

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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: Kok Hong Tan, Hing Wah Lee, Jhih-Wei Chen, Chang Fu Dee, Chung-Lin Wu, Siang-Piao Chai, Wei Sea Chang

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Semiconductor photocatalyst is known as one of the key roles in developing clean and sustainable energy. However, most of the semiconductor only possesses photoactivity within the UV light region, and hence, decreases the overall photocatalyst efficiency. Generally, the overall effectiveness of the photocatalyst activity is determined by three critical steps: (i) light absorption efficiency and photoexcitation electron-hole pair generation, (ii) separation and migration of charge carriers to the surface of the photocatalyst, and (iii) surface reaction of the carriers with its environment. Much effort has been invested on optimizing hierarchical nanostructures of semiconductors for efficient photoactivity due to the fact that the visible light absorption capability and occurrence of the chemical reactions mostly depend on the dimension of photocatalysts. In this work, we incorporated zero-dimensional (0D) gold nanoparticles (AuNPs) and one dimensional (1D) Zinc Oxide (ZnO) nanorods (NRs) onto strontium titanate (STO) for efficient visible light absorption, charge transfer, and separation. We demonstrate that the electrical and optical properties of the photocatalyst can be tuned by controlling the dimensional structures of AuNPs and ZnO NRs. We found that smaller AuNPs sizes exhibited higher photoactivity because of Fermi level shifting toward the conductive band of STO, STO band gap narrowing and broadening of absorption spectrum to the visible light region. For ZnO NRs, it was found that the average ZnO NRs c-axis length must achieve of certain length to induce multiphoton absorption as a result of light reflection and trapping behavior in the free space between adjacent ZnO NRs hence broadening the absorption spectrum of ZnO from UV to visible light region. This work opens up a new way of broadening the absorption spectrum by incorporating controllable nanostructures of semiconductors, which is important in optimizing the solar water splitting process.

Keywords: gold nanoparticles, photoelectrochemical, PEC, semiconductor photocatalyst, zinc oxide nanorods

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Authors: Jonjaua Ranogajec, Ognjen Rudic, Snezana Pasalic, Snezana Vucetic, Damir Cjepa

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The paper involves a chain of activities from synthesis, establishment of the methodology for characterization and testing of novel protective materials through the pilot production and application on model supports. It summarizes the results regarding the development of the pilot production protocol for newly developed self-cleaning materials. The optimization of the production parameters was completed in order to improve the most important functional properties (mineralogy characteristics, particle size, self-cleaning properties and photocatalytic activity) of the newly designed nanocomposite material.

Keywords: pilot production, self-cleaning materials, compatibility, cultural heritage

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Authors: Yihua Wang, Yunru Lai

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Statistical process control has been successfully applied in a variety of industries. In some applications, the quality of a process or product is better characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. A collection of this type of data is called a profile. Profile monitoring is used to understand and check the stability of this relationship or curve over time. The independent assumption for the error term is commonly used in the existing profile monitoring studies. However, in many applications, the profile data show correlations over time. Therefore, we focus on a general linear regression model with a first-order autocorrelation between profiles in this study. We propose an exponentially weighted moving average charting scheme to monitor this type of profile. The simulation study shows that our proposed methods outperform the existing schemes based on the average run length criterion.

Keywords: autocorrelation, EWMA control chart, general linear regression model, profile monitoring

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Authors: H. D. Duong, J. I. Rhee

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In this work, gold nanoparticles in star shape (called gold nanostars, GNS) were synthesized and coated by N-(3-aminopropyl) methacrylamide hydrochloride (PA) and mercaptopropionic acid (MPA) for functionalizing their surface by amine and carboxyl groups and then investigated for ROS production. The GNS with big size and multi-tips seem to be superior in singlet oxygen production as compared with that of small GNS and less tips. However, the functioned GNS in small size could also enhance efficiency of singlet oxygen production about double as compared with that of the intact GNS. In combination with methylene blue (MB+), the functioned GNS could enhance the singlet oxygen production of MB+ after 1h of LED750 irradiation and no difference between small size and big size in this reaction was observed. In combination with 5-aminolevulinic acid (ALA), only GNS coated PA could enhance the singlet oxygen production of ALA and the small size of GNS coated PA was a little higher effect than that of the bigger size. However, GNS coated MPA with small size had strong effect on hydroxyl radical production of ALA.

Keywords: 5-aminolevulinic acid, gold nanostars, methylene blue, ROS production

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Ofoegbu Ositadinma Edward

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

Keywords: fuel pump, microcontroller, GUI, web

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Rhadinia Tayag-Relanes, Felina C. Young

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This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: production, continuous improvement, process, operations, PDCA

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Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

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Authors: Y. Benallou, K. Amara, O. Arbouche

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In this paper, we report a density functional study of the structural, electronic and elastic properties of the ordered phases of SrxPb1-xS ternary semiconductor alloys namely rocksalt compounds: PbS and SrS and the rocksalt-based compounds: SrPb3S4, SrPbS2, and Sr3PbS4. These First-principles calculations have been performed using the full potential linearized augmented plane wave method (FP-LAPW) within the Generalized Gradient Approximation developed by Perdew–Burke–Ernzerhor for solids (PBEsol). The calculated structural parameters like the lattice parameters, the bulk modulus B and their pressure derivative B' are in reasonable agreement with the available experimental and theoretical data. In addition, the elastic properties such as elastic constants (C11, C12, and C44), the shear modulus G, the Young modulus E, the Poisson’s ratio ν and the B/G ratio are also given. For the electronic properties calculations, the exchange and correlation effects were treated by the Tran-Blaha modified Becke-Johnson (TB-mBJ) potential to prevent the shortcoming of the underestimation of the energy gaps in both LDA and GGA approximations. The obtained results are compared to available experimental data and to other theoretical calculations.

Keywords: SrxPb1-xS, GGA-PBEsol+TB-MBJ, density functional, Perdew–Burke–Ernzerhor, FP-LAPW

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Authors: S. F. Wong, W. I. Ho, B. Lin, Q. Huang

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ERP has been used in many enterprises for management, the accuracy of the production forecasting module is vital to the decision making of the enterprise, and the profit is affected directly. Therefore, enhancing the accuracy of the production forecasting module can also increase the efficiency and profitability. To deal with a lot of data, a suitable, reliable and accurate statistics model is necessary. LSSVM and Grey System are two main models to be studied in this paper, and a case study is used to demonstrate how the combination model is effective to the result of forecasting.

Keywords: ERP, grey system, LSSVM, production forecasting

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Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

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Authors: Mamoon Masud, Suleman Mazhar

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Indus river basin’s irrigation system in Pakistan is extremely complex, spanning over 50,000 km. Maintenance and monitoring of this demands enormous resources. This paper describes the development of a streamlined and low-cost autonomous underwater vehicle (AUV) for the monitoring of irrigation canals including water quality monitoring and water theft detection. The vehicle is a hovering-type AUV, designed mainly for monitoring irrigation canals, with fully documented design and open source code. It has a length of 17 inches, and a radius of 3.5 inches with a depth rating of 5m. Multiple sensors are present onboard the AUV for monitoring water quality parameters including pH, turbidity, total dissolved solids (TDS) and dissolved oxygen. A 9-DOF Inertial Measurement Unit (IMU), GY-85, is used, which incorporates an Accelerometer (ADXL345), a Gyroscope (ITG-3200) and a Magnetometer (HMC5883L). The readings from these sensors are fused together using directional cosine matrix (DCM) algorithm, providing the AUV with the heading angle, while a pressure sensor gives the depth of the AUV. 2 sonar-based range sensors are used for obstacle detection, enabling the vehicle to align itself with the irrigation canals edges. 4 thrusters control the vehicle’s surge, heading and heave, providing 3 DOF. The thrusters are controlled using a proportional-integral-derivative (PID) feedback control system, with heading angle and depth being the controller’s input and the thruster motor speed as the output. A flow sensor has been incorporated to monitor canal water level to detect water-theft event in the irrigation system. In addition to water theft detection, the vehicle also provides information on water quality, providing us with the ability to identify the source(s) of water contamination. Detection of such events can provide useful policy inputs for improving irrigation efficiency and reducing water contamination. The AUV being low cost, small sized and suitable for autonomous maneuvering, water level and quality monitoring in the irrigation canals, can be used for irrigation network monitoring at a large scale.

Keywords: the autonomous underwater vehicle, irrigation canal monitoring, water quality monitoring, underwater line tracking

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Authors: Chia-Chen Wei, Pack Hsieh, Jeffrey Chen

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Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.

Keywords: big data analytics, Industry 4.0, SPI threshold setting, surface mount technology

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Authors: Donglan Zha, Jiansong Si

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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

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Authors: Manuel Rosales, Francisco Agrela, Julia Rosales

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The development of concrete pavements that include recycled waste with active and predictive safety features is a possible approach to mitigate the harmful impacts of the construction industry, such as CO2 emissions and the consumption of energy and natural resources during the construction and maintenance of road infrastructure. This study establishes the basis for formulating new smart materials for concrete pavements and carrying out the in-situ implementation of an experimental road section. To this end, a comprehensive recycled pavement solution is developed that combines eco-hybrid cement made with 25% mixed recycled aggregate powder (pMRA) and biomass bottom ash powder (pBBA) and a 30% substitution of natural aggregate by MRA and BBA. This work is grouped in three lines. 1) construction materials with high rates of use of recycled material, 2) production processes with efficient consumption of natural resources and use of cleaner energies, and 3) implementation and monitoring of road section with sustainable concrete made from waste. The objective of this study is to ensure satisfactory rheology, mechanical strength, durability, and CO2 capture of pavement concrete manufactured from waste and its subsequent application in real road section as well as its monitoring to establish the optimal range of recycled material. The concrete developed during this study are aimed at the reuse of waste, promoting the circular economy. For this purpose, and after having carried out different tests in the laboratory, three mixtures were established to be applied on the experimental road.

Keywords: biomass bottom ash, construction and demolition waste, recycled concrete pavements, full-scale experimental road, monitoring

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Authors: Hasan Vural

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The purpose of this study was to determine energy equivalents of inputs and output in tomato production in Bursa province. The data in this study were collected from tomato farms in Bursa province, Karacabey and Mustafakemalpasa district. Questionnaires were administered through face-to-face interview in 2011-2012. The results of the study show that diesel have the highest rate of energy equivalency of all the inputs used in tomato production at 60,07%. The energy equivalent rate of electricity is 4,26% and the energy equivalent rate of water is 0,87%. The energy equivalent rates for human power, machinery, chemicals and water for irrigation were determined to be low in tomato production. According to the output/input ratio calculated, the energy ratio is 1,50 in tomato production in the research area. This ratio implies that the inputs used in tomato production have not been used effectively. Ineffective use of these resources also causes environmental problems.

Keywords: Tomato production, energy ratio, energy input, Turkey

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Authors: Ajay Das, Sandip Basu

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Introduction: There is increasing recognition that diverse streams of knowledge can often be recombined in novel ways to generate new knowledge. However, knowledge recombination theory has not been applied to examine the effects of collaborator diversity on the quality of knowledge such collaborators produce. This is surprising because one would expect that a collaborative team with certain aspects of diversity should be able to recombine process elements related to knowledge development, which are relatively tacit, but also complementary because of the collaborator’s varying backgrounds. Theory and Hypotheses: We propose to examine two aspects of diversity in the environments of collaborative teams to try and capture such potential recombinations of relatively tacit, process knowledge. The first aspect of diversity in team members’ environments is geographical. Collaborators with more geographical distance between them (perhaps working in different countries) often have more autonomy in the processes they adopt for knowledge development. In the absence of overt monitoring, such collaborators are likely to adopt differing approaches to knowledge development. The sharing of such varying approaches among collaborators is likely to result in greater quality of the common collaborative pursuit. The second aspect is diversity in the work backgrounds of team members. Such diversity can also increase the potential for knowledge recombination. For example, if one or more members are from a manufacturing center (versus all of them being from a purely R&D center), such members will provide unique perspectives on the implementation of innovative ideas. Again, knowledge that has been evaluated from these diverse perspectives is likely to be of a higher quality. In addition to the above aspects of environmental diversity among team members, we also plan to examine the extent to which individual collaborators are in different environments from the primary innovation center of their employing firms. Proposed Methods: We will test our model on a sample of firms in the semiconductor industry. Our level of analysis will be individual patents generated by these firms and the teams involved in the generation of these. Information on manufacturing activities of our sample firms will be obtained from SEMI, a proprietary database of the semiconductor industry, as well as company 10-K reports. Conclusion: We believe that our results will represent a preliminary attempt to understand how various forms of diversity in collaborative teams impact the knowledge development process. Our dependent variable of knowledge quality is important to study since higher values of this variable can not only drive firm performance but the broader development of regions and societies through spillover impacts on future innovation. The results of this study will, therefore, inform future research and practice in innovation, geographical location, and vertical integration.

Keywords: innovation, manufacturing strategy, knowledge, diversity

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Authors: Tomas Vincze, Michal Micjan, Milan Pavuk, Martin Weis

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In recent years, alternative materials are gaining attention to replace polycrystalline and amorphous silicon, which are a standard for low requirement devices, where silicon is unnecessarily and high cost. For that reason, metal oxides are envisioned as the new materials for these low-requirement applications such as sensors, solar cells, energy storage devices, or field-effect transistors. Their most common way of layer growth is sputtering; however, this is a high-cost fabrication method, and a more industry-suitable alternative is the sol-gel method. In this group of materials, many oxides exhibit a semiconductor-like behavior with sufficiently high mobility to be applied as transistors. The sol-gel method is a cost-effective deposition technique for semiconductor-based devices. Copper oxides, as p-type semiconductors with free charge mobility up to 1 cm2/Vs., are suitable replacements for poly-Si or a-Si:H devices. However, to reach the potential of silicon devices, a fine-tuning of material properties is needed. Here we focus on the optimization of the electrical parameters of copper oxide-based field-effect transistors by modification of precursor solvent (usually 2-methoxy ethanol). However, to achieve solubility and high-quality films, a better solvent is required. Since almost no solvents have both high dielectric constant and high boiling point, an alternative approach was proposed with blend solvents. By mixing isopropyl alcohol (IPA) and 2-methoxy ethanol (2ME) the precursor reached better solubility. The quality of the layers fabricated using mixed solutions was evaluated in accordance with the surface morphology and electrical properties. The IPA:2ME solution mixture reached optimum results for the weight ratio of 1:3. The cupric oxide layers for optimal mixture had the highest crystallinity and highest effective charge mobility.

Keywords: copper oxide, field-effect transistor, semiconductor, sol-gel method

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

Abstract:

Ensuring accurate radiotherapy with carbon therapy requires precise monitoring of radiation dose distribution within the patient's body. This monitoring is essential for targeted tumor treatment, minimizing harm to healthy tissues, and improving treatment effectiveness while lowering side effects. In our investigation, we employed a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo simulations. Initially, Geant4 simulations were utilized to extract the initial positions of secondary particles formed during interactions between carbon ions and water. These particles included protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we studied the relationship between the carbon ion beam and these secondary particles. Interaction Vertex Imaging (IVI) is valuable for monitoring dose distribution in carbon therapy. It provides details about the positions and amounts of secondary particles, particularly protons. The IVI method depends on charged particles produced during ion fragmentation to gather information about the range by reconstructing particle trajectories back to their point of origin, referred to as the vertex. In our simulations regarding carbon ion therapy, we observed a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the target's unique elongated geometry, which hindered the straightforward transmission of forward-generated protons. Consequently, the limited protons that emerged mostly originated from points close to the target entrance. The trajectories of fragments (protons) were approximated as straight lines, and a beam back-projection algorithm, using recorded interaction positions in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitoring of radiation dose, interaction vertex imaging

Procedia PDF Downloads 61

Authors: Khawlh A. Alzubaidi, Khadijah B. Alziyadi, Amor M. Alsayari

Abstract:

The discovery of a dilute magnetic semiconductor (DMS) in which ferromagnetism is carrier-mediated and persists above room temperature is a major step toward the implementation of spintronic devices for processing, transferring, and storing of information. Among the many types of DMS materials which have been investigated, Mn-doped GaAs has become one of the best candidates for technological application. However, despite major developments over the last few decades, the maximum Curie temperature (~200 K) remains well below room temperature. In this work, we have studied the effect of Mn content and strain on the GaMnAs effective masses of electron, heavy and light holes calculated in the different crystallographic direction. Also, the Curie temperature in the DMS GaMnAs alloy is determined. Compilation of GaMnAs band parameters have been carried out using the 8-band k.p model based on Lowdin perturbation theory where spin orbit, sp-d exchange interaction, and biaxial strain are taken into account. Our results show that effective masses, calculated along the different crystallographic directions, have a strong dependence on strain, ranging from -2% (tensile strain) to 2% (compressive strain), and Mn content increased from 1 to 5%. The Curie temperature is determined within the mean-field approach based on the Zener model.

Keywords: diluted magnetic semiconductors, k.p method, effective masses, curie temperature, strain

Procedia PDF Downloads 81

Authors: Hyun-Woo Cho

Abstract:

Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

Procedia PDF Downloads 237

Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

Abstract:

Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

Procedia PDF Downloads 391