Search results for: module development

Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Ítalo de Pontes Oliveira

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This paper presents a analysis of performance the Received Strength Signal Indicator (RSSI) to Wireless Sensor Networks, with a finality of investigate a behavior of ZigBee devices operating into real environments. The test of performance was realize using two Series 1 ZigBee Module and two modules of development Arduino Uno R3, evaluating in this form a measurements of RSSI into environments like places of sports, preservation forests and water reservoir.

Keywords: wireless sensor networks, RSSI, Arduino, environments

Procedia PDF Downloads 584

Authors: M. Maleczek, Leszek Bogdan, Kazimierz Drabczyk, Agnieszka Iwan

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Crystalline silicon (Si) solar cells are the main product in the market among the various photovoltaic technologies concerning such advantages as: material richness, high carrier mobilities, broad spectral absorption range and established technology. However, photovoltaic technology on the stiff substrates are heavier, more fragile and less cost-effective than devices on the flexible substrates to be applied in special applications. The main goal of our work was to incorporate silicon solar cells into various fabric, without any change of the electrical and mechanical parameters of devices. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. In our work, the polyamide or polyester fabrics were used as a flexible substrate in the created devices. Applied fabrics differ in tensile and tear strength. All investigated polyamide fabrics are resistant to weathering and UV, while polyester ones is resistant to ozone, water and ageing. The examined fabrics are tight at 100 cm water per 2 hours. In our work, commercial silicon solar cells with the size 156 × 156 mm were cut into nine parts (called single solar cells) by diamond saw and laser. Gap and edge after cutting of solar cells were checked by transmission electron microscope (TEM) to study morphology and quality of the prepared single solar cells. Modules with the size of 160 × 70 cm (containing about 80 single solar cells) were created and investigated by electrical and mechanical methods. Weight of constructed module is about 1.9 kg. Three types of solar cell architectures such as: -fabric/EVA/Si solar cell/EVA/film for lamination, -backsheet PET/EVA/Si solar cell/EVA/film for lamination, -fabric/EVA/Si solar cell/EVA/tempered glass, were investigated taking into consideration type of fabric and lamination process together with the size of solar cells. In investigated devices EVA, it is ethylene-vinyl acetate, while PET - polyethylene terephthalate. Depend on the lamination process and compatibility of textile with solar cell an efficiency of investigated flexible silicon solar cells was in the range of 9.44-16.64 %. Multi folding and unfolding of flexible module has no impact on its efficiency as was detected by Instron equipment. Power (P) of constructed solar module is 30 W, while voltage about 36 V. Finally, solar panel contains five modules with the polyamide fabric and tempered glass will be produced commercially for different applications (dual use).

Keywords: flexible devices, mechanical properties, silicon solar cells, textiles

Procedia PDF Downloads 150

Authors: Jun Sung Go, Jong Kang Park, Jong Tae Kim

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As semi-conductor manufacturing technology evolves; the single event transient problem becomes more significant issue. Single event transient has a critical impact on both combinational and sequential logic circuits, so it is important to evaluate the soft error tolerance of the circuits at the design stage. In this paper, we present a soft error detecting simulation using scan chain. The simulation model generates a single event transient randomly in the circuit, and detects the soft error during the execution of the test patterns. We verified this model by inserting a scan chain in an 8051 microprocessor using 65 nm CMOS technology. While the test patterns generated by ATPG program are passing through the scan chain, we insert a single event transient and detect the number of soft errors per sub-module. The experiments show that the soft error rates per cell area of the SFR module is 277% larger than other modules.

Keywords: scan chain, single event transient, soft error, 8051 processor

Procedia PDF Downloads 315

Authors: Babak Kamrani, Nozar Kishi

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Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

Procedia PDF Downloads 269

Authors: Abu Afree Andalib, Rafiur Rahman, Md Mezbah Uddin

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The main objective of this work is to anatomize on the various parameters of AGM 88 missile anatomized using FSI module in Ansys. Computational fluid dynamics is used for the study of fluid flow pattern and fluidic phenomenon such as drag, pressure force, energy dissipation and shockwave distribution in water. Using finite element analysis module of Ansys, structural parameters such as stress and stress density, localization point, deflection, force propagation is determined. Separate analysis on structural parameters is done on Abacus. State of the art coupling module is used for FSI analysis. Fine mesh is considered in every case for better result during simulation according to computational machine power. The result of the above-mentioned parameters is analyzed and compared for two phases using graphical representation. The result of Ansys and Abaqus are also showed. Computational Fluid Dynamics and Finite Element analyses and subsequently the Fluid-Structure Interaction (FSI) technique is being considered. Finite volume method and finite element method are being considered for modelling fluid flow and structural parameters analysis. Feasible boundary conditions are also utilized in the research. Significant change in the interaction and interference pattern while the impact was found. Theoretically as well as according to simulation angled condition was found with higher impact.

Keywords: FSI (Fluid Surface Interaction), impact, missile, high viscous fluid, CFD (Computational Fluid Dynamics), FEM (Finite Element Analysis), FVM (Finite Volume Method), fluid flow, fluid pattern, structural analysis, AGM-88, Ansys, Abaqus, meshing, k-omega, turbulence model

Procedia PDF Downloads 440

Authors: Alessandra Chiara Maraschin, Estelle Trengove

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In South Africa, only 23% of engineering students attain their degrees in the minimum time of 4 years. This begs the question: Why is the 4-year throughput rate so low? Improving the throughput rate is crucial in assisting students to the shortest possible path to completion. The Electrical Engineering programme has a fixed curriculum and students must pass all courses in order to graduate. In South Africa, as is the case in several other countries, many students rely on external funding such as bursaries from companies in industry. If students fail a course, they often lose their bursaries, and most might not be able to fund their 'repeating year' fees. It is thus important to improve the throughput rate, since for many students, graduating from university is a way out of poverty for an entire family. In Electrical Engineering, it has been found that the Software Development I course (an introduction to C++ programming) is a significant hurdle course for students and has been found to have a low pass rate. It has been well-documented that students struggle with this type of course as it introduces a number of new threshold concepts that can be challenging to grasp in a short time frame. In an attempt to mitigate this situation, a part-time night-school for Software Development I was introduced in 2015 as an intervention measure. The course includes all the course material from the Software Development I module and allows students who failed the course in first semester a second chance by repeating the course through taking the night-school course. The purpose of this study is to determine whether the introduction of this intervention course could be considered a success. The success of the intervention is assessed in two ways. The study will first look at whether the night-school course contributed to improving the pass rate of the Software Development I course. Secondly, the study will examine whether the intervention contributed to improving the overall throughput from the 2nd year to the 3rd year of study at a South African University. Second year academic results for a sample of 1216 students have been collected from 2010-2017. Preliminary results show that the lowest pass rate for Software Development I was found to be in 2017 with a pass rate of 34.9%. Since the intervention course's inception, the pass rate for Software Development I has increased each year from 2015-2017 by 13.75%, 25.53% and 25.81% respectively. To conclude, the preliminary results show that the intervention course is a success in improving the pass rate of Software Development I.

Keywords: academic performance, electrical engineering, engineering education, intervention course, low pass rate, software development course, throughput

Procedia PDF Downloads 137

Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

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It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

Procedia PDF Downloads 26

Authors: Arpan Dwivedi, Yogesh Pahariya

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In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off-grid, PV module

Procedia PDF Downloads 214

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

Procedia PDF Downloads 95

Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins's problem, double-input rule module, fuzzy inference model, obstacle avoidance, single-input rule module

Procedia PDF Downloads 327

Authors: Doo Ki Lee, Man Young Kim

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The Urea-Selective Catalytic Reduction (SCR) system is considered to be the most promising technology to fulfill the stringent emission regulation. In the Urea-SCR system, the urea solutions are used as the reducing agent, which is a eutectic composition (32.5wt% of urea). The advantage of this eutectic compositions is that it has a low freezing point approximately at -11 ℃, however, the problem of freezing occurs at low-temperature levels below that freezing point. To prevent freezing of urea solutions, we need heating systems that can melt by heating the frozen urea solutions in urea storage tank at low-temperature environment. In this study, therefore, a numerical investigation of three-dimensional unsteady heating problems analyzed to find the melting characteristics of the urea solutions on melting process. In this work, it can be found that the urea melting initiated by heat conduction from the heater is enhanced by the natural convection inside the melted liquid urea solutions due to the temperature difference. Also, liquid urea solutions are initially concentrated on the upper parts of the urea sender module.

Keywords: urea solution, melting, heat conduction, natural convection, liquid fraction, phase change

Procedia PDF Downloads 240

Authors: M. A. Moghaddas, M. Short, N. Wiley, A. Y. Yi, K. F. Graff

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The application of ultrasonic vibrations to machining processes has a long history, ranging from slurry-based systems able to drill brittle materials, to more recent developments involving low power ultrasonics for high precision machining, with many of these at the research and laboratory stages. The focus of this development is the application of high levels of ultrasonic power (1,000’s of watts) to standard, heavy duty machine tools – drilling being the immediate focus, with developments in milling in progress – with the objective of dramatically increasing system productivity through faster feed rates, this benefit arising from the thrust force reductions obtained by power ultrasonic vibrations. The presentation will describe development of an advanced drilling system based on a special, acoustically designed, rugged drill module capable of functioning under heavy duty production conditions, and making use of standard tool holder means, and able to obtain thrust force reductions while maintaining or improving surface finish and drilling accuracy. The characterization of the system performance will be described, and results obtained in drilling several materials (Aluminum, Stainless steel, Titanium) presented.

Keywords: dimensional accuracy, machine tool, productivity, surface roughness, thrust force, ultrasonic vibrations, ultrasonic-assisted drilling

Procedia PDF Downloads 252

Authors: Vilma Deltuvaitė

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Comparisons of financial development across countries are central to answering many of the questions on factors leading to economic development. For this reason this study analyzes the implications of financial system’s development on country’s economic development. The aim of the article: to analyze the impact of financial system’s development on economic development. The following research methods were used: systemic, logical and comparative analysis of scientific literature, analysis of statistical data, time series model (Autoregressive Distributed Lag (ARDL) Model). The empirical results suggest about positive short and long term effect of stock market development on GDP per capita.

Keywords: banking sector, economic development, financial system’s development, stock market, private bond market

Procedia PDF Downloads 350

Authors: K. Drabczyk, Z. Starowicz, S. Maleczek, P. Zieba

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The army, police and fire brigade commonly use dedicated equipment based on special textile materials. The properties of these textiles should ensure human life and health protection. Equally important is the ability to use electronic equipment and this requires access to the source of electricity. Photovoltaic cells integrated with such textiles can be solution for this problem in the most of outdoor circumstances. One idea may be to laminate the cells to textile without changing their properties. The main goal of this work was analyzed lamination quality of special designed semi-flexible solar module with special textile materials as a backsheet. In the first step of investigation, the quality of lamination was determined using device equipped with dynamometer. In this work, the crystalline silicon solar cells 50 x 50 mm and thin chemical tempered glass - 62 x 62 mm and 0.8 mm thick - were used. The obtained results showed the correlation between breaking force and type of textile weave and fiber. The breaking force was in the ranges: 4.5-5.5 N, 15-20 N and 30-33 N depending on the type of wave and fiber type. To verify these observations the microscopic and FTIR analysis of fibers was performed. The studies showed the special textile can be used as a backsheet of semi-flexible solar modules. This work presents a new composition of solar module with special textile layer which, to our best knowledge, has not been published so far. Moreover, the work presents original investigations on adhesion of EVA (ethylene-vinyl acetate) polymer to textile with respect to fiber structure of laminated substrate. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management.

Keywords: flexible solar modules, lamination process, solar cells, textile for photovoltaics

Procedia PDF Downloads 332

Authors: C. Ah Gang Getrude, Iqbal Hashmi Shazia, Mohd Nawi Nurul Hudani

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This study examined the effectiveness of a Traffic Psychology Workshop in enhancing positive attitudes towards road safety awareness among youths. We predicted that youths’ attitudes towards road safety would be more positive after they participated in the one-day workshop. We examined their attitudes towards road safety awareness before and after they attended a one-day workshop. There were 21 participants who completed the pre and post-studies (9 males & 12 females, mean age 22.86, SD=2.03). A Wilcoxon signed-ranks test showed that the mean for post-test ranks for students’ attitudes towards road safety awareness was higher than the mean pre-test ranks, z =-3.16, p = .00. The study showed that the Traffic Psychology Module which focuses on the three elements: i) personality & emotion; Sensation, perception and visual; and mental workload could have positive effects on youths’ attitudes towards road safety awareness. We believe that the Traffic Psychology Module could be used as a guide by relevant authorities, such as the Sabah Road Safety Department, in implementing road safety awareness workshops and programs for the public, particularly road-users.

Keywords: attitude, road safety, traffic psychology, youth

Procedia PDF Downloads 291

Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

Procedia PDF Downloads 102

Authors: Shyam, G. N. Tiwari

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Energy matrices of flate plate water collectors partially covered by PV module have been estimated in the present study. Photovoltaic thermal (PVT) water collector assembly is consisting of 5 water collectors having 2 m^2 area which are partially covered by photovoltaic module at its lower portion (inlet) and connected in series. The annual overall thermal energy and exergy are computed by using climatic data of New Delhi provided by Indian Meteorological Department (IMD) Pune, India. The Energy payback time on overall thermal and exergy basis are found to be 1.6 years and 17.8 years respectively. For 25 years of life time of system the energy production factor and life cycle conversion efficiency are estimated to be 15.8 and 0.04 respectively on overall thermal energy basis whereas for the same life time the energy production factor and life cycle conversion efficiency on exergy basis are obtained as 1.4 and 0.001.

Keywords: overall thermal energy, exergy, energy payback time, PVT water collectors

Procedia PDF Downloads 355

Authors: Jay P. Sipani, Riki H. Patel, Trushit Upadhyaya

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Today there is a demand to monitor environmental factors almost in all research institutes and industries and even for domestic uses. The analog data measurement requires manual effort to note readings, and there may be a possibility of human error. Such type of systems fails to provide and store precise values of parameters with high accuracy. Analog systems are having drawback of storage/memory. Therefore, there is a requirement of a smart system which is fully automated, accurate and capable enough to monitor all the environmental parameters with utmost possible accuracy. Besides, it should be cost-effective as well as portable too. This paper represents the Wireless Sensor (WS) data communication using DHT11, Arduino, SIM900A GSM module, a mobile device and Liquid Crystal Display (LCD). Experimental setup includes the heating arrangement of DHT11 and transmission of its data using Arduino and SIM900A GSM shield. The mobile device receives the data using Arduino, GSM shield and displays it on LCD too. Heating arrangement is used to heat and cool the temperature sensor to study its characteristics.

Keywords: wireless communication, Arduino, DHT11, LCD, SIM900A GSM module, mobile phone SMS

Procedia PDF Downloads 254

Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

Procedia PDF Downloads 166

Authors: S. Hammoudeh, S. Ghuloum, A. Abdelhakam, A. AlMujalli, M. Opler, Y. Hani, A. Yehya, S. Mari, R. Elsherbiny, Z. Mahfoud, H. Al-Amin

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Introduction: Suicidal ideation and attempts are very common in patients with schizophrenia and still contributes to the high mortality in this population. The InterSePT Scale for Suicidal Thinking (ISST) is a validated tool used to assess suicidal ideation in patients with schizophrenia. This research aims to validate the Arabic version of the ISST among the Arabs residing in Qatar. Methods: Patients diagnosed with schizophrenia were recruited from the department of Psychiatry, Rumailah Hospital, Doha, Qatar. Healthy controls were recruited from the primary health care centers in Doha, Qatar. The validation procedures including professional and expert translation, pilot survey and back translation of the ISST were implemented. Diagnosis of schizophrenia was confirmed using the validated Arabic version of Mini International Neuropsychiatric Interview (MINI 6, module K) for schizophrenia. The gold standard was the module B on suicidality from MINI 6 also. This module was administered by a rater who was blinded to the results of ISST. Results: Our sample (n=199) was composed of 98 patients diagnosed with schizophrenia (age 36.03 ± 9.88 years; M/F is 2/1) and 101 healthy participants (age 35.01 ± 8.23 years; M/F is 1/2). Among patients with schizophrenia: 26.5% were married, 17.3% had a college degree, 28.6% were employed, 9% had committed suicide once, and 4.4% had more than 4 suicide attempts. Among the control group: 77.2% were married, 57.4% had a college degree, and 99% were employed. The mean score on the ISST was 2.36 ± 3.97 vs. 0.47 ± 1.44 for the schizophrenia and control groups, respectively. The overall Cronbach’s alpha was 0.91. Conclusions: This is the first study in the Arab world to validate the ISST in an Arabic-based population. The psychometric properties indicate that the Arabic version of the ISST is a valid tool to assess the severity of suicidal ideation in Arabic speaking patients diagnosed with schizophrenia.

Keywords: mental health, Qatar, schizophrenia, suicide

Procedia PDF Downloads 529

Authors: Wei Zhao, Yuxuan Yao, Hao Chen

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In order to find out the mechanical properties and failure behavior of lithium-ion batteries, drop hammer impact experiments and finite element simulations are carried out on batteries with different packed angles. Firstly, a drop hammer impact experiment system, which is based on the DHR-1808 drop hammer and oscilloscope, is established, and then a drop test of individual batteries and packed angles of 180 ° and 120 ° are carried out. The image of battery deformation, force-time curve and voltage-time curve are recorded. Secondly, finite element models of individual batteries and two packed angles are established, and the results of the test and simulation are compared. Finally, the mechanical characteristics and failure behavior of lithium-ion battery modules with the packed arrangement of 6 * 6 and packing angles of 180 °, 120 °, 90 ° and 60 ° are analyzed under the same velocity with different battery packing angles, and the same impact energy with different impact velocity and different packing angles. The result shows that the individual battery is destroyed completely in the drop hammer impact test with an initial impact velocity of 3m/s and drop height of 459mm, and the voltage drops to close to 0V when the test ends. The voltage drops to 12V when packed angle of 180°, and 3.6V when packed angle of 120°. It is found that the trend of the force-time curve between simulation and experiment is generally consistent. The difference in maximum peak value is 3.9kN for a packing angle of 180° and 1.3kN for a packing angle of 120°. Under the same impact velocity and impact energy, the strain rate of the battery module with a packing angle of 180° is the lowest, and the maximum stress can reach 26.7MPa with no battery short-circuited. The research under our experiment and simulation shows that the lithium-ion battery module with a packing angle of 180 ° is the least likely to be damaged, which can sustain the maximum stress under the same impact load.

Keywords: battery module, finite element simulation, power battery, packing angle

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Authors: Madiha Zahid, Afifa Khanam

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The present study aims to investigate the effect of reflective teaching practices on prospective teachers’ performance. Reflective teaching practice helps teachers to plan, implement and improve their performance by rethinking about their strengths and weaknesses. An action research was conducted by the researcher. All prospective teachers of sixth semester in a women university’s teacher education program were the population of the study. From 40 students, 20 students were taken as experimental group, and the rest of 20 students were taken as control group. During the action research a cyclic process of producing a module, training teachers for the reflective practices and then observing them during their class for reflective practice was done by the researchers. The research used a set of rubrics and checklists for assessing prospective teachers’ performance during their class. Finally, the module was modified with the help of findings. It was found that the training has improved the performance of teachers as they revised and modified their teaching strategies through reflective practice. However, they were not able to train their students for reflective practice as per expectation. The study has implications for teacher training programs to include reflective practice modules as part of their course work for making them better teachers.

Keywords: reflective practices, prospective teacher, effect, performance

Procedia PDF Downloads 153

Authors: Eric Bates

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Higher education is recognised as being of critical importance in Ireland and has been linked as a vital factor to national well-being. Statistics show that Ireland has one of the highest rates of higher education participation in Europe. However, student retention and progression, especially in Institutes of Technology, is becoming an issue as rates on non-completion rise. Both within Ireland and across Europe student retention is seen as a key performance indicator for higher education and with these increasing rates the Irish higher education system needs to be flexible and adapt to the situation it now faces. The author is a Programme Chair on a Level 6 full time undergraduate programme and experience to date has shown that the first year undergraduate students take some time to identify themselves as a group within the setting of a higher education institute. Despite being part of a distinct class on a specific programme some individuals can feel isolated as he or she take the first step into higher education. Such feelings can contribute to students eventually dropping out. This paper reports on an ongoing initiative that aims to accelerate the bonding experience of a distinct group of first year undergraduates on a programme which has a high rate of non-completion. This research sought to engage the students in dynamic interactions with their peers to quickly evolve a group sense of coherence. Two separate modules – a Research Module and a Communications module - delivered by the researcher were linked across two semesters. Students were allocated into random groups and each group was given a topic to be researched. There were six topics – essentially the six sub-headings on the DIT Graduate Attribute Statement. The research took place in a computer lab and students also used the library. The output from this was a document that formed part of the submission for the Research Module. In the second semester the groups then had to make a presentation of their findings where each student spoke for a minimum amount of time. Presentation workshops formed part of that module and students were given the opportunity to practice their presentation skills. These presentations were video recorded to enable feedback to be given. Although this was a small scale study preliminary results found a strong sense of coherence among this particular cohort and feedback from the students was very positive. Other findings indicate that spreading the initiative across two semesters may have been an inhibitor. Future challenges include spreading such Initiatives College wide and indeed sector wide.

Keywords: first year experience, student retention, group work, presentation workshops

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Authors: Pei-Chun Chen, Chi-Ting Tseng, Lih-Chi Chen, Kai-Hsiang Yang

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Introduction: The pharmacist is responsible for encouraging adverse drug reaction (ADR) reporting. In a local center in Northern Taiwan, promotion and rewarding of ADR reporting have continued for over six years but failed to bring significant changes. This study aims to find a solution to increase ADR reporting. Research question or hypothesis: We hypothesized that under-reporting is due to the inconvenience of the reporting system. Reports were made conventionally through printed sheets. We proposed that reports made per month will increase if they were computerized. Study design: An ADR reporting platform was established in April 2015, before which was defined as the first stage of this study (January-March, 2015) and after which the second stage. The third stage commenced in November, 2015, after adding a reporting module to physicians prescription system. ADRs could be reported simultaneously when documenting drug allergies. Methods: ADR report rates during the three stages of the study were compared. Effects of the information platform on reporting were also analyzed. Results: During the first stage, the number of ADR reports averaged 6 per month. In the second stage, the number of reports per month averaged 1.86. Introducing the information platform had little effect on the monthly number of ADR reports. The average number of reports each month during the third stage of the study was 11±3.06, with 70.43% made electronically. Reports per month increased significantly after installing the reporting module in November, 2015 (P<0.001, t-test). In the first two stages, 29.03% of ADR reports were made by physicians, as compared to 70.42% of cases in the third stage of the study. Increased physician reporting possibly account for these differences. Conclusion: Adding a reporting module to the prescription system significantly increased ADR reporting. Improved accessibility is likely the cause. The addition of similar modules to computer systems of other healthcare professions may be considered to encourage spontaneous ADR reporting.

Keywords: adverse drug reactions, adverse drug reaction reporting systems, regional hospital, prescription system

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Nalinee Sophatsathit

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This paper presents a variation of navigation systems which tallies every node along the shortest path from start to destination nodes. The underlying technique rests on the well-established Dijkstra Algorithm. The ultimate goal is to serve as a user navigation guide that furnishes stop over cost of every node along this shortest path, whereby users can decide whether or not to visit any specific nodes. The output is an implementable module that can be further refined to run on the Internet and smartphone technology. This will benefit large organizations having physical installations spreaded over wide area such as hospitals, universities, etc. The savings on service personnel, let alone lost time and unproductive work, are attributive to innovative navigation system management.

Keywords: navigation systems, shortest path, smartphone technology, user navigation guide

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Authors: Gizachew Belay Adugna

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Perovskite solar cells (PSCs) shows rapid development as an emerging photovoltaic material; however, the fast device degradation due to the organic nature, mainly hole transporting material (HTM) and lack of robust and reliable upscaling process for photovoltaic module hindered its commercialization. Herein, HTM molecules with/without fluorine-substituted cyclopenta[2,1-b;3,4-b’]dithiophene derivatives (HYC-oF, HYC-mF, and HYC-H) were developed for PSCs application. The fluorinated HTM molecules exhibited better hole mobility and overall charge extraction in the devices mainly due to strong molecular interaction and packing in the film. Thus, the highest power conversion efficiency (PCE) of 19.64% with improved long stability was achieved for PSCs based on HYC-oF HTM. Moreover, the fluorinated HYC-oF demonstrated excellent film processability in a larger-area substrate (10 cm×10 cm) prepared sequentially with the absorption perovskite underlayer via a scalable bar coating process in ambient air and owned a higher PCE of 18.49% compared to the conventional spiro-OMeTAD (17.51%). The result demonstrates a facile development of HTM towards stable and efficient PSCs for future industrial-scale PV modules.

Keywords: perovskite solar cells, upscaling film coating, power conversion efficiency, solution processing

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Authors: Yong Chen

Abstract:

To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

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Authors: Tayab D. Memon, Shahji Farooque, Marvi Deshi, Imtiaz Hussain Kalwar, B. S. Chowdhry

Abstract:

Recently single-bit ternary FIR-like filter (SBTFF) hardware synthesize in FPGA is reported and compared with multi-bit FIR filter on similar spectral characteristics. Results shows that SBTFF dominates upon multi-bit filter overall. In this paper, an optimized adder module for ternary quantized sigma-delta modulated signal is presented. The adder is simulated using ModelSim for functional verification the area-performance of the proposed adder were obtained through synthesis in Xilinx and compared to conventional adder trees. The synthesis results show that the proposed adder tree achieves higher clock rates and lower chip area at higher inputs to the adder block; whereas conventional adder tree achieves better performance and lower chip area at lower number of inputs to the same adder block. These results enhance the usefulness of existing short word length DSP algorithms for fast and efficient mobile communication.

Keywords: short word length (SWL), DSP algorithms, FPGA, SBTFF, VHDL

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