Search results for: X-ray output

Authors: Gunjita Shami, Noopur Anand

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The pilot run of 50 days was undertaken to test employability potential of people with visual and hearing & speech impairment. Various roles in an apparel manufacturing set up like spreading of fabric for cutting, folding, sealing and labeling cartons, pasting size barcode stickers on packed garments, removing tickets from the garments in the finishing stage were studied. Their performance was quantified basis timesheets for all the days and improvement per day was quantified. Their final day output was compared to that of the able-bodied worker. For example in the carton making activity on day one visually impaired worker was making one box every three minutes which improved to four boxes per minute on day 28 displaying 91.6% improvement compared or an improvement of 3.6% per day which was comparable to the able-bodied seasoned workers, who were making 5 boxes per minute. The performance of persons with hearing and speech impairment in the finishing department was 10% higher than that of able-bodied seasoned workers in the same process. Overall in all the activities the differently abled showed day to day improvement of 65% while able bodied displayed improvement of 52%. On the first day performance of able-bodied worker was 75% better than that of differently abled while on the 50th day it was only 20% better. Therefore the performance of persons with disabilities was found comparable to the able bodied person. The results, though on a small scale, showed a big promise of employment of persons with disability in the apparel industry. Armed with the promising result a full-scale study has been undertaken to identify the roles suitable for certain kind of disability in apparel production, work-aids required to assist the differently abled to improve performance and measures to be undertaken to make production floor 'friendlier' for them. The results have been discussed in this paper which opens doors for integrating differently abled into the world projected and assumed for only able-bodied.

Keywords: apparel sector, differently abled, employability, performance, work-aid

Procedia PDF Downloads 149

Authors: Alireza Vahid, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh, Thomas Dorin

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Aluminum is the preferred material for lightweight applications and its alloys are constantly improving. The high strength 7xxx alloys have been extensively used for structural components in aerospace and automobile industries for the past 50 years. In the next decade, a great number of airplanes will be retired, providing an obvious source of valuable used metals and great demand for cost-effective methods to re-use these alloys. The design of proper aerospace alloys is primarily based on optimizing strength and ductility, both of which can be improved by controlling the additional alloying elements as well as heat treatment conditions. In this project, we explore the design of high-performance alloys with 7xxx as a base material. These designed alloys have to be optimized and improved to compare with modern 7xxx-series alloys and to remain competitive for aircraft manufacturing. Aerospace alloys are extremely complex with multiple alloying elements and numerous processing steps making optimization often intensive and costly. In the present study, we used Bayesian optimization algorithm, a well-known adaptive design strategy, to optimize this multi-variable system. An Al alloy was proposed and the relevant heat treatment schedules were optimized, using the tensile yield strength as the output to maximize. The designed alloy has a maximum yield strength and ultimate tensile strength of more than 730 and 760 MPa, respectively, and is thus comparable to the modern high strength 7xxx-series alloys. The microstructure of this alloy is characterized by electron microscopy, indicating that the increased strength of the alloy is due to the presence of a high number density of refined precipitates.

Keywords: aluminum alloys, Bayesian optimization, heat treatment, tensile properties

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

Procedia PDF Downloads 69

Authors: Makda Yeshitela Kifele

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Hair treatment prevents the hair from loss of volume, changing colour, and damaging its properties of the hair. Hair is the beauty of human beings that makes people beautiful and takes the other hearts to see them and to give them an appreciation for their effort to treat their hair and save it from damage. There are different methods to protect human hair from loss and damage that influence human psychology better than the problems. Chemicals products are available in the world that keeps safely the hair and provide beauty for the hair. But chemical products have side effects and are not cost-effective. Even some of the chemicals are allergic for users and left some changes in the hair. Indigenous hair treatment is an effective method that reduces the bad effects and the problems of the chemical that are lefts in human being’slife. Indigenous hair treatment can treat the hair safely and effectively that does not have much effect or spots in the human hair the users rather, it improves some attributes of the hair such that shine, quality, quantity improvements, length, and flexibility can be modified by these indigenous treatments. Rate is the local plant that plays a significant role in hair treatment. Rate is the local plant that can be available everywhere in the country, and anybody can be used for hair treatments. For this research, 50 women are identified as sample populations with different hair characteristics. The treatments were collected from the fields and squeezed into the pots to be prepared as specimens. The squeezed plants were deposited in the refrigerator for three days with some amounts of salts to prevent some bacteria. Chemical analysis has been done to sort out some detrimental substances. So the result showed that there are no detrimental substances that affect the hair properties and the health of the users. The sample population used the oil for one month without any other oily cosmetics that disturbs the treatment. The output is very effective and brings shining the hair, preventing greying of the hair, showing fast-growing, increasing the volume of the hair, and becoming flexible and curly, straight hair, thicker, and with no allergic effects.

Keywords: indigenous, chemicals, curly, treatment

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Authors: Liqiang Duan, Ma Jingkai, Lv Zhipeng, Haifan Cai

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The integrated solar combined cycle (ISCC) system has a series of advantages such as increasing the system power generation, reducing the cost of solar power generation, less pollutant and CO₂ emission. In this paper, the parabolic trough collectors with direct steam generation (DSG) technology are considered to replace the heat load of heating surfaces in heat regenerator steam generation (HRSG) of a conventional natural gas combined cycle (NGCC) system containing a PG9351FA gas turbine and a triple pressure HRSG with reheat. The detailed model of the NGCC system is built in ASPEN PLUS software and the parabolic trough collectors with DSG technology is modeled in EBSILON software. ISCC-DSG systems with the replacement of single, two, three and four heating surfaces are studied in this paper. Results show that: (1) the ISCC-DSG systems with the replacement heat load of HPB, HPB+LPE, HPE2+HPB+HPS, HPE1+HPE2+ HPB+HPS are the best integration schemes when single, two, three and four stages of heating surfaces are partly replaced by the parabolic trough solar energy collectors with DSG technology. (2) Both the changes of feed water flow and the heat load of the heating surfaces in ISCC-DSG systems with the replacement of multi-stage heating surfaces are smaller than those in ISCC-DSG systems with the replacement of single heating surface. (3) ISCC-DSG systems with the replacement of HPB+LPE heating surfaces can increase the solar power output significantly. (4) The ISCC-DSG systems with the replacement of HPB heating surfaces has the highest solar-thermal-to-electricity efficiency (47.45%) and the solar radiation energy-to-electricity efficiency (30.37%), as well as the highest exergy efficiency of solar field (33.61%).

Keywords: HRSG, integration scheme, parabolic trough collectors with DSG technology, solar power generation

Procedia PDF Downloads 253

Authors: Sunday Nanosi Ndovi, Patrick Albert Chikumba

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In Malawi, smallholder dairy farmers transport unprocessed milk to sell at Milk Bulking Groups (MBGs). MBGs store and chill the milk while awaiting collection by processors. The farmers deliver milk using various modes of transportation such as foot, bicycle, and motorcycle. As a perishable food, milk requires timely transportation to avoid deterioration. In other instances, some farmers bypass the nearest MBGs for facilities located further away. Untimely delivery worsens quality and results in rejection at MBG. Subsequently, these rejections lead to revenue losses for dairy farmers. Therefore, the objective of this study was to optimize routes when transporting milk by selecting the shortest route using time as a cost attribute in Geographic Information Systems (GIS). A spatially organized transport system impedes milk deterioration while promoting profitability for dairy farmers. A transportation system was modeled using Route Analysis and Closest Facility network extensions. The final output was to find the quickest routes and identify the nearest milk facilities from incidents. Face-to-face interviews targeted leaders from all 48 MBGs in the study area and 50 farmers from Namahoya MBG. During field interviews, coordinates were captured in order to create maps. Subsequently, maps supported the selection of optimal routes based on the least travel times. The questionnaire targeted 200 respondents. Out of the total, 182 respondents were available. Findings showed that out of the 50 sampled farmers that supplied milk to Namahoya, only 8% were nearest to the facility, while 92% were closest to 9 different MBGs. Delivering milk to the nearest MBGs would minimize travel time and distance by 14.67 hours and 73.37 km, respectively.

Keywords: closest facility, milk, route analysis, spatial transport

Procedia PDF Downloads 58

Authors: Svanik Garg

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Static Test Pads are stationary mechanisms that hold a solid rocket motor, measuring the different parameters of its operation including thrust and temperature to better calibrate it for launch. This paper outlines a specific STP designed to test high powered rocket motors with a thrust upwards of 4000N and limited to 6500N. The design includes a specific portable mechanism with cost an integral part of the design process to make it accessible to small scale rocket developers with limited resources. Using curved surfaces and an ergonomic design, the STP has a delicately engineered façade/case with a focus on stability and axial calibration of thrust. This paper describes the design, operation and working of the STP and its widescale uses given the growing market of aviation enthusiasts. Simulations on the CAD model in Fusion 360 provided promising results with a safety factor of 2 established and stress limited along with the load coefficient A PCB was also designed as part of the test pad design process to help obtain results, with visual output and various virtual terminals to collect data of different parameters. The circuitry was simulated using ‘proteus’ and a special virtual interface with auditory commands was also created for accessibility and wide-scale implementation. Along with this description of the design, the paper also emphasizes the design principle behind the STP including a description of its vertical orientation to maximize thrust accuracy along with a stable base to prevent micromovements. Given the rise of students and professionals alike building high powered rockets, the STP described in this paper is an appropriate option, with limited cost, portability, accuracy, and versatility. There are two types of STP’s vertical or horizontal, the one discussed in this paper is vertical to utilize the axial component of thrust.

Keywords: static test pad, rocket motor, thrust, load, circuit, avionics, drag

Procedia PDF Downloads 380

Authors: Fatemeh Abbasi, Sahand Daneshvar

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Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.

Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index

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Authors: Daniel O. Johnson, Abiodun A. Ogunseye, Aaron Aransiola, Majors Samuel

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Power Inverter is a very important device in renewable energy use particularly for solar photovoltaic power application because it is the effective interface between the DC power generator and the load or the grid. Transformerless inverter is getting more and more preferred to the power converter with galvanic isolation transformer and may eventually supplant it. Transformerless inverter offers advantages of improved DC to AC conversion and power delivery efficiency; and reduced system cost, weight and complexity. This work presents thorough analysis of the design and prototyping of 3KVA grid-tie transformerless inverter. The inverter employs electronic switching method with minimised heat generation in the system and operates based on the principle of pulse-width modulation (PWM). The design is such that it can take two inputs, one from PV arrays and the other from Battery Energy Storage BES and addresses the safety challenge of leakage current. The inverter system was designed around microcontroller system, modeled with Proteus® software for simulation and testing of the viability of the designed inverter circuit. The firmware governing the operation of the grid-tied inverter is written in C language and was developed using MicroC software by Mikroelectronica® for writing sine wave signal code for synchronization to the grid. The simulation results show that the designed inverter circuit performs excellently with very high efficiency, good quality sinusoidal output waveform, negligible harmonics and gives very stable performance under voltage variation from 36VDC to 60VDC input. The prototype confirmed the simulated results and was successfully synchronized with the utility supply. The comprehensive analyses of the circuit design, the prototype and explanation on overall performance will be presented.

Keywords: grid-tied inverter, leakage current, photovoltaic system, power electronic, transformerless inverter

Procedia PDF Downloads 291

Authors: Alonggot Limcharoen, Jintana Wannarat, Vorawat Panich

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This study aims to investigate the balancing of the number of operators (Line Balancing technique) in the production line of hard disk drive components in order to increase efficiency. At present, the trend of using hard disk drives has continuously declined leading to limits in a company’s revenue potential. It is important to improve and develop the production process to create market share and to have the ability to compete with competitors with a higher value and quality. Therefore, an effective tool is needed to support such matters. In this research, the Arena program was applied to analyze the results both before and after the improvement. Finally, the precedent was used before proceeding with the real process. There were 14 work stations with 35 operators altogether in the RA production process where this study was conducted. In the actual process, the average production time was 84.03 seconds per product piece (by timing 30 times in each work station) along with a rating assessment by implementing the Westinghouse principles. This process showed that the rating was 123% underlying an assumption of 5% allowance time. Consequently, the standard time was 108.53 seconds per piece. The Takt time was calculated from customer needs divided by working duration in one day; 3.66 seconds per piece. Of these, the proper number of operators was 30 people. That meant five operators should be eliminated in order to increase the production process. After that, a production model was created from the actual process by using the Arena program to confirm model reliability; the outputs from imitation were compared with the original (actual process) and this comparison indicated that the same output meaning was reliable. Then, worker numbers and their job responsibilities were remodeled into the Arena program. Lastly, the efficiency of production process enhanced from 70.82% to 82.63% according to the target.

Keywords: hard disk drive, line balancing, ECRS, simulation, arena program

Procedia PDF Downloads 225

Authors: Cornelius Michael Ekenta, Aderonke Bashirat Mohammed, Sefi Ahmed

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The research examined the impact of flooding on food calorie intake and health challenges among smallholder farm households in Koton Karfe Local Government Area of Kogi State, Nigeria. Purposive and random sampling techniques were used to select 130 farm households in selected villages in the area. Primary data were generated through the administration of a well-structured questionnaire. Data were analyzed with descriptive statistics, Double Difference Estimator (DDE), Calorie Intake Estimation Function, t-test, and multiple regressions. The result shows that farm households lost an average of 132, 950kg of selected crops amounting to about N20m ($56, 542) loose in income. Food daily calorie intake indicates a loss of an average of 715.18Kcal, showing a significant difference in calorie intake before and after flooding (t = 2.0629) at 5% probability. Furthermore, the health challenges most prevalent during flooding were malaria fever, typhoid fever, cholera, and dysentery. The determinants of daily calorie intake were age, household size, level of income, flooding, health challenges, and food price. The study concluded that flooding had negative impacts on crop output and income, daily food calorie intact, and health challenges of a farm household in the study area. It was recommended that the State Government should make adequate and proper arrangements to relocate residents of the area at the warning of possible flooding by the National Metrological Centre and should, through the State Emergency Management Agency (SEMA), provide relieve items to the residents to cushion the effects of the flooding.

Keywords: calorie, cholera, flooding, health challenges, impact

Procedia PDF Downloads 144

Authors: H. Fuad Usman, M. Rafay Khan Sial, Shahzaib Hamid

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The trend of renewable energy resources has been amplified due to global warming and other environmental related complications in the 21st century. Recent research has very much emphasized on the generation of electrical power through renewable resources like solar, wind, hydro, geothermal, etc. The use of the photovoltaic cell has become very public as it is very useful for the domestic and commercial purpose overall the world. Although a single cell gives the low voltage output but connecting a number of cells in a series formed a complete module of the photovoltaic cells, it is becoming a financial investment as the use of it fetching popular. This also reduced the prices of the photovoltaic cell which gives the customers a confident of using this source for their electrical use. Photovoltaic cell gives the MPPT at single specific point of operation at a given temperature and level of solar intensity received at a given surface whereas the focal point changes over a large range depending upon the manufacturing factor, temperature conditions, intensity for insolation, instantaneous conditions for shading and aging factor for the photovoltaic cells. Two improved algorithms have been proposed in this article for the MPPT. The widely used algorithms are the ‘Incremental Conductance’ and ‘Perturb and Observe’ algorithms. To extract the maximum power from the source to the load, the duty cycle of the convertor will be effectively controlled. After assessing the previous techniques, this paper presents the improved and reformed idea of harvesting maximum power point from the photovoltaic cells. A thoroughly go through of the previous ideas has been observed before constructing the improvement in the traditional technique of MPP. Each technique has its own importance and boundaries at various weather conditions. An improved technique of implementing the use of both ‘Perturb and Observe’ and ‘Incremental Conductance’ is introduced.

Keywords: duty cycle, MPPT (Maximum Power Point Tracking), perturb and observe (P&O), photovoltaic module

Procedia PDF Downloads 176

Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

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The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: building information management, BIM, economic order quantity, EOQ, fixed order point, FOP, BIM 4D, BIM 5D

Procedia PDF Downloads 172

Authors: Pedro Miguel Cardoso Carneiro, Ricardo André Nunes Borges, João Pedro Soares Loureiro, Hermínio Maio Graça Fernandes

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Wind energy has been exponentially growing over the last years and will allow countries to progress regarding the decarbonization objective. In parallel, the maintenance activities have also been increasing in consequence of ageing and deterioration of the wind farms. The time available for wind blade maintenance is given by the weather window that is based upon weather conditions. Most of the wind blade repair and maintenance activities require a narrow window of temperature and humidity. Due to this limitation, the current weather windows result only on approximately 35% days/year are used for maintenance, that takes place mostly during summertime. This limitation creates large economic losses in the energy production of the wind towers, since they can be inoperative or with the energy production output reduced for days or weeks due to existing damages. Another important aspect is that the maintenance costs are higher due to the high standby time and seasonality imposed on the technicians. To reduce the relevant maintenance costs of blades and energy loses some technological developments were carried out to significantly improve this reality. The focus of this activity was to develop a series of key developments to have in the near future a suspended access equipment that can operate in harsh conditions, wind rain, cold/hot environment. To this end we have identified key areas that need to be revised and require new solutions to be found; a habitat system, multi-configurable roof and floor, roof and floor interface to blade, secondary attachment solutions to the blade and to the tower. On this paper we will describe the advances produced during a national R&D project made in partnership with an end-user (Onrope) and a test center (ISQ).

Keywords: wind turbine maintenance, cost reduction, technological innovations, wind turbine blade

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Authors: Charles Iledun Oyewole

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The daunting challenge that the ‘man with the hoe’ is going to face in the coming decades will be complex and interwoven. With global population already above 7 billion people, it has been estimated that food (crop) production must more than double by 2050 to meet up with the world’s food requirements. Nigeria population is also expected to reach over 240 million people by 2050, at the current annual population growth of 2.61 per cent. The country’s farming population is estimated at over 65 per cent, but the country still depends on food importation to complement production. The small scale farmer, who depends on simple hand tools: hoes and cutlasses, remains the centre of agricultural production, accounting for 90 per cent of the total agricultural output and 80 per cent of the market flow. While the hoe may have been a tool for sustainable development at a time in human history, this role has been smothered by population growth, which has brought too many mouths to be fed (over 170 million), as well as many industries to fuel with raw materials. It may then be argued that the hoe is unfortunately not a tool for the coming challenges and that agricultural mechanization should be the focus. However, agriculture as an enterprise is a ‘complete wheel’ which does not work when broken, particularly, in respect to mechanization. Generally, mechanization will prompt increase production, where land is readily available; increase production, will require post-harvest handling mechanisms, crop processing and subsequent storage. An important aspect of this is readily available and favourable markets for such produce; fuel by good agricultural policies. A break in this wheel will lead to the process of mechanization crashing back to subsistence production, and probably reversal to the hoe. The focus of any agricultural policy should be to chart a course for sustainable mechanization that is environmentally friendly, that may ameliorate Nigeria’s food and raw material gaps. This is the focal point of this article.

Keywords: Crop production, Farmer, Hoes, Mechanization, Policy framework, Population, Growth, Rural areas

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

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Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: database, forensic genetics, genetic analysis, sample management, software solution

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Authors: Meng-Jie Hsiao, Cam Nguyen

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Wide-band devices in Ku band (12-18 GHz) and K band (18-27 GHz) have received significant attention for high-data-rate communications and high-resolution sensing. Especially, devices operating around 24 GHz is attractive due to the 24-GHz unlicensed applications. One of the most important components in RF systems is power amplifier (PA). Various PAs have been developed in the Ku and K bands on GaAs, InP, and silicon (Si) processes. Although the PAs using GaAs or InP process could have better power handling and efficiency than those realized on Si, it is very hard to integrate the entire system on the same substrate for GaAs or InP. Si, on the other hand, facilitates single-chip systems. Hence, good PAs on Si substrate are desirable. Especially, Si-based PA having good linearity is necessary for next generation communication protocols implemented on Si. We report a 16.5 to 25.5 GHz Si-based PA having flat saturated power of 19.5 ± 1.5 dBm, output 1-dB power compression (OP1dB) of 16.5 ± 1.5 dBm, and 15-23 % power added efficiency (PAE). The PA consists of a drive amplifier, two main amplifiers, and lump-element Wilkinson power divider and combiner designed and fabricated in TowerJazz 0.18µm SiGe BiCMOS process having unity power gain frequency (fMAX) of more than 250 GHz. The PA is realized as a cascode amplifier implementing both heterojunction bipolar transistor (HBT) and n-channel metal–oxide–semiconductor field-effect transistor (NMOS) devices for gain, frequency response, and linearity consideration. Particularly, a body-floating technique is utilized for the NMOS devices to improve the voltage swing and eliminate parasitic capacitances. The developed PA has measured flat gain of 20 ± 1.5 dB across 16.5-25.5 GHz. At 24 GHz, the saturated power, OP1dB, and maximum PAE are 20.8 dBm, 18.1 dBm, and 23%, respectively. Its high performance makes it attractive for use in Ku/K-band, especially 24 GHz, communication and radar systems. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: power amplifiers, amplifiers, communication systems, radar systems

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Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

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Authors: Amir Shahab Shahabi, Mohsen Hasirian

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Modern societies, marked by expansive Internet connectivity and the rise of e-commerce, are now integrated with digital platforms at an unprecedented level. The efficiency, speed, and accessibility of e-commerce have garnered a substantial consumer base. Against this backdrop, electronic banking has undergone rapid proliferation within the realm of online activities. However, this growth has inadvertently given rise to an environment conducive to illicit activities, notably electronic payment fraud, posing a formidable challenge to the domain of electronic banking. A pivotal role in upholding the integrity of electronic commerce and business transactions is played by electronic fraud detection, particularly in the context of credit cards which underscores the imperative of comprehensive research in this field. To this end, our study introduces an Attentional Bi-Stream Sequence Learner (AttBiSeL) framework that leverages attention mechanisms and recurrent networks. By incorporating bidirectional recurrent layers, specifically bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers, the proposed model adeptly extracts past and future transaction sequences while accounting for the temporal flow of information in both directions. Moreover, the integration of an attention mechanism accentuates specific transactions to varying degrees, as manifested in the output of the recurrent networks. The effectiveness of the proposed approach in automatic credit card fraud classification is evaluated on the European Cardholders' Fraud Dataset. Empirical results validate that the hybrid architectural paradigm presented in this study yields enhanced accuracy compared to previous studies.

Keywords: credit card fraud, deep learning, attention mechanism, recurrent neural networks

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Authors: Kayode Ilesanmi Ebenezer Bowale, Dominic Azuh, Busayo Aderounmu, Alfred Ilesanmi

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There has been a debate among scholars and policymakers about the effects of oil exploration and production on industrial development. In Nigeria, there were many reforms resulting in an increase in crude oil production in the recent past. There is a controversy on the importance of oil production in the development of the manufacturing sector in Nigeria. Some scholars claim that oil has been a blessing to the development of the manufacturing sector, while others regard it as a curse. The objective of the study is to determine if empirical analysis supports the presence of Dutch Disease and de-industrialisation in the Nigerian manufacturing sector between 2019- 2022. The study employed data that were sourced from World Development Indicators, Nigeria Bureau of Statistics, and the Central Bank of Nigeria Statistical Bulletin on manufactured exports, manufacturing employment, agricultural employment, and service employment in line with the theory of Dutch Disease using the unit root test to establish their level of stationarity, Engel and Granger cointegration test to check their long-run relationship. Autoregressive. Distributed Lagged bound test was also used. The Vector Error Correction Model will be carried out to determine the speed of adjustment of the manufacturing export and resource movement effect. The results showed that the Nigerian manufacturing industry suffered from both direct and indirect de-industrialisation over the period. The findings also revealed that there was resource movement as labour moved away from the manufacturing sector to both the oil sector and the services sector. The study concluded that there was the presence of Dutch Disease in the manufacturing industry, and the problem of de-industrialisation led to the crowding out of manufacturing output. The study recommends that efforts should be made to diversify the Nigerian economy. Furthermore, a conducive business environment should be provided to encourage more involvement of the private sector in the agriculture and manufacturing sectors of the economy.

Keywords: Dutch disease, resource movement, manufacturing sector performance, Nigeria

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Authors: Abdel-Monem Sayed Mohamed

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Egypt rapidly growing development is accompanied by increasing levels of standard living particular in its urban areas. However, there is a limited experience in quantifying the sources of risk management in Egypt and in designing efficient strategies to keep away serious impacts of earthquakes. From the historical point of view and recent instrumental records, there are some seismo-active regions in Egypt, where some significant earthquakes had occurred in different places. The special tectonic features in Egypt: Aswan, Greater Cairo, Red Sea and Sinai Peninsula regions are the territories of a high seismic risk, which have to be monitored by up-to date technologies. The investigations of the seismic events and interpretations led to evaluate the seismic hazard for disaster prevention and for the safety of the dense populated regions and the vital national projects as the High Dam. In addition to the monitoring of the recent crustal movements, the most powerful technique of satellite geodesy GPS are used where geodetic networks are covering such seismo-active regions. The results from the data sets are compared and combined in order to determine the main characteristics of the deformation and hazard estimation for specified regions. The final compiled output from the seismological and geodetic analysis threw lights upon the geodynamical regime of these seismo-active regions and put Aswan and Greater Cairo under the lowest class according to horizontal crustal strains classifications. This work will serve a basis for the development of so-called catastrophic models and can be further used for catastrophic risk management. Also, this work is trying to evaluate risk of large catastrophic losses within the important regions including the High Dam, strategic buildings and archeological sites. Studies on possible scenarios of earthquakes and losses are a critical issue for decision making in insurance as a part of mitigation measures.

Keywords: b-value, Gumbel distribution, seismic and GPS data, strain parameters

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Authors: Udayan Patankar, Shashwati Bhagat, Vilas Nitneware, Ants Koel

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An ISM band power amplifier is a type of electronic amplifier used to convert a low-power radio-frequency signal into a larger signal of significant power, typically used for driving the antenna of a transmitter. Due to drastic changes in telecommunication generations may lead to the requirements of improvements. Rapid changes in communication lead to the wide implementation of WLAN technology for its excellent characteristics, such as high transmission speed, long communication distance, and high reliability. Many applications such as WLAN, Bluetooth, and ZigBee, etc. were evolved with 2.4GHz to 5 GHz ISM Band, in which the power amplifier (PA) is a key building block of RF transmitters. There are many manufacturing processes available to manufacture a power amplifier for desired power output, but the major problem they have faced is about the power it consumed for its proper working, as many of them are fabricated on the GaN HEMT, Bi COMS process. In this paper we present a CMOS Base two stage cascode design of power amplifier working on 2.4GHz ISM frequency band. To lower the costs and allow full integration of a complete System-on-Chip (SoC) we have chosen 0.13µm low power CMOS technology for design. While designing a power amplifier, it is a real task to achieve higher power efficiency with minimum resources. This design showcase the Multi biased Cascode methodology to implement a two-stage CMOS power amplifier using ADS and LTSpice simulating tool. Main source is maximum of 2.4V which is internally distributed into different biasing point VB driving and VB driven as required for distinct stages of two stage RF power amplifier. It shows maximum power added efficiency near about 70.195% whereas its Power added efficiency calculated at 1 dB compression point is 44.669 %. Biased MOSFET is used to reduce total dc current as this circuit is designed for different wireless applications comes under 2.4GHz ISM Band.

Keywords: RFIC, PAE, RF CMOS, impedance matching

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Authors: Durjoy Lahiri, Vishal Madhukar Sawale, Ashwani Bhat, Souvik Dubey, Gautam Das, Biman Kanti Roy, Suparna Chatterjee, Goutam Gangopadhyay

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Crossed aphasia has been an area of considerable interest for cognitive researchers as it offers a fascinating insight into cerebral lateralization for language function. We conducted an observational study in the stroke unit of a tertiary care neurology teaching hospital in eastern India on subjects with crossed aphasia over a period of four years. During the study period, we detected twelve cases of crossed aphasia in strongly right-handed patients, caused by ischemic stroke. The age, gender, vernacular language and educational status of the patients were noted. Aphasia type and severity were assessed using Bengali version of Western Aphasia Battery (validated). Computed tomography, magnetic resonance imaging and angiography were used to evaluate the location and extent of the ischemic lesion in brain. Our series of 12 cases of crossed aphasia included 7 male and 5 female with mean age being 58.6 years. Eight patients were found to have Broca’s aphasia, 3 had trans-cortical motor aphasia and 1 patient suffered from global aphasia. Nine patients were having very severe aphasia and 3 suffered from mild aphasia. Mirror-image type of crossed aphasia was found in 3 patients, whereas 9 had anomalous variety. In our study crossed aphasia was found to be more frequent in males. Anomalous pattern was more common than mirror-image. Majority of the patients had motor-type aphasia and no patient was found to have pure comprehension deficit. We hypothesize that in Bengali-speaking right-handed population, lexical-semantic system of the language network remains loyal to the left hemisphere even if the phonological output system is anomalously located in the right hemisphere.

Keywords: aphasia, crossed, lateralization, language function, vascular

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Authors: Winncy Du, Jeremy Nguyen, Harpinder Dhillon, Reinardus Justin Halim, Clayton Haske, Trent Hughes, Marissa Ortiz, Rozy Saini

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Stroke often causes death or cerebro-vascular (CV) brain damage. Most patients with CV brain damage lost their motor control on their limbs. This paper focuses on developing a reliable, safe, and non-invasive EEG-based robot-assistant stroke rehabilitation system to help stroke survivors to rapidly restore their motor control functions for their limbs. An electroencephalogram (EEG) recording device (EPOC Headset) and was used to detect a patient’s brain activities. The EEG signals were then processed, classified, and interpreted to the motion intentions, and then converted to a series of robot motion commands. A six-axis articulated robot (AdeptSix 300) was employed to provide the intended motions based on these commends. To ensure the EEG device, the computer, and the robot can communicate to each other, an Arduino microcontroller is used to physically execute the programming codes to a series output pins’ status (HIGH or LOW). Then these “hardware” commends were sent to a 24 V relay to trigger the robot’s motion. A lookup table for various motion intensions and the associated EEG signal patterns were created (through training) and installed in the microcontroller. Thus, the motion intention can be direct determined by comparing the EEG patterns obtaibed from the patient with the look-up table’s EEG patterns; and the corresponding motion commends are sent to the robot to provide the intended motion without going through feature extraction and interpretation each time (a time-consuming process). For safety sake, an extender was designed and attached to the robot’s end effector to ensure the patient is beyond the robot’s workspace. The gripper is also designed to hold the patient’s limb. The test results of this rehabilitation system show that it can accurately interpret the patient’s motion intension and move the patient’s arm to the intended position.

Keywords: brain waves, EEG sensor, motion control, robot-assistant stroke rehabilitation

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Marco Naegele, Klaus Stoppel, Thomas Dekorsy

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Passively Q-switched microchip lasers enable the great potential for sophisticated LiDAR systems due to their compact overall system design, excellent beam quality, and scalable pulse energies. However, many near-infrared solid-state lasers show emitting wavelengths > 1000 nm, which are not compatible with state-of-the-art silicon detectors. Here we demonstrate a passively Q-switched microchip laser operating at 914 nm. The microchip laser consists of a 3 mm long Nd:YVO₄ crystal as a gain medium, while Cr⁴⁺:YAG with an initial transmission of 98% is used as a saturable absorber. Quasi-continuous pumping enables single pulse operation, and low duty cycles ensure low overall heat generation and power consumption. Thus, thermally induced instabilities are minimized, and operation without active cooling is possible while ambient temperature changes are compensated by adjustment of the pump laser current only. Single-emitter diode pumping at 808 nm leads to a compact overall system design and robust setup. Utilization of a microchip cavity approach ensures single-longitudinal mode operation with spectral bandwidths in the picometer regime and results in short laser pulses with pulse durations below 10 ns. Beam quality measurements reveal an almost diffraction-limited beam and enable conclusions concerning the thermal lens, which is essential to stabilize the plane-plane resonator. A 7% output coupler transmissivity is used to generate pulses with energies in the microjoule regime and peak powers of more than 600 W. Long-term pulse duration, pulse energy, central wavelength, and spectral bandwidth measurements emphasize the excellent system stability and facilitate the utilization of this laser in the context of a LiDAR system.

Keywords: diode-pumping, LiDAR system, microchip laser, Nd:YVO4 laser, passively Q-switched

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Authors: Richard Adu Antwako

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Coastal wetland destruction and its consequences have recently taken the center stage of global discussions. This phenomenon is no gray area to humanity as coastal wetland-human interaction seems inevitably ingrained in the earliest civilizations, amidst the demanding use of its resources to meet their necessities. The severity of coastal wetland destruction parallels with growing civilizations, and it is against this backdrop that, this paper interrogated the causes of coastal wetland destruction in Harper City in Liberia, compared the degree of coastal wetland stressors to the non-equilibrium thermodynamic scale as well as suggested an integrated coastal zone management to address the problems. Literature complemented the primary data gleaned via global positioning system devices, field observation, questionnaire, and interviews. Multi-sampling techniques were used to generate data from the sand miners, institutional heads, fisherfolk, community-based groups, and other stakeholders. Non-equilibrium thermodynamic theory remains vibrant in discerning the ecological stability, and it would be employed to further understand the coastal wetland destruction in Harper City, Liberia and to measure the coastal wetland stresses-amplitude and elasticity. The non-equilibrium thermodynamics postulates that the coastal wetlands are capable of assimilating resources (inputs), as well as discharging products (outputs). However, the input-output relationship exceedingly stretches beyond the thresholds of the coastal wetlands, leading to coastal wetland disequilibrium. Findings revealed that the sand mining, mangrove removal, and crude dumping have transformed the coastal wetlands, resulting in water pollution, flooding, habitat loss and disfigured beaches in Harper City in Liberia. This paper demonstrates that the coastal wetlands are converted into developmental projects and agricultural fields, thus, endangering the future society against nature.

Keywords: amplitude, crude dumping, elasticity, non-equilibrium thermodynamics, wetland destruction

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