Search results for: machine monitoring

Authors: Rachita Lal

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Urban sprawl is a significant contributor to land use change in developing countries, where urbanization rates are high. The most important driver of environmental changes is also considered to be the shift in land use and land cover. Our local and regional land managers must carefully analyze urbanization and its effects on cities to make the best choices. This study uses satellite imagery to examine how urbanization affects the local ecosystem through geographic expansion. The following research focuses on the effects of city growth on the local environment, land use, and Land cover. The primary focus of this research is to study, To understand the role of urbanization on city expansion. To study the impact of spatial growth of urban areas on the Land cover. In this paper, the GIS tool will be used to analyze. For this purpose, four digital images are used for the years 2000, 2005, 2011, and 2019. The use of the approach in the Bhubaneswar Urban Core, one of the fastest developing and planned cities in India, has proved that it is highly beneficial and successful for monitoring urban sprawl. It offers a helpful tool for quantitative assessment, which is crucial for determining the spatial dynamics, variations, and changes of urban sprawl patterns in quickly increasing regions.

Keywords: LULC, urbanization, environment impact assessment, spatial growth

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Authors: Lojain Suliman, Xinrong Liu, Xiaohan Zhou

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Since most tunnels are built in crowded metropolitan settings, the excavation process must take place in highly condensed locations, including high-density cities. In this way, the tunnels are typically located close together, which leads to more interaction between the parallel existing tunnels, and this, in turn, leads to more settlement. This research presents an examination of the impact of a large-scale tunnel excavation on two forms of settlement: surface settlement and settlement surrounding the tunnel. Additionally, research has been done on the properties of interactions between two and three parallel tunnels. The settlement has been evaluated using three primary techniques: theoretical modeling, numerical simulation, and data monitoring. Additionally, a parametric investigation on how distance affects the settlement characteristic for parallel tunnels with short distances has been completed. Additionally, it has been observed that the sequence of excavation has an impact on the behavior of settlements. Nevertheless, a comparison of the model test and numerical simulation yields significant agreement in terms of settlement trend and value. Additionally, when compared to the FEM study, the suggested analytical solution exhibits reduced sensitivity in the settlement prediction. For example, the settlement of the small tunnel diameter does not appear clearly on the settlement curve, while it is notable in the FEM analysis. It is advised, however, that additional studies be conducted in the future employing analytical solutions for settlement prediction for parallel tunnels.

Keywords: settlement, FEM, analytical solution, parallel tunnels

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Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

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Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the work piece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: dexel, process stability, material removal, milling

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Authors: Thammarak Srimarut, Witthaya Mekhum

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This study analysed and developed a model for monk’s food bowl production on occupational health safety and environment at work for the encouragement of Rattanakosin local wisdom at Banbart Community. The process of blowpipe welding was necessary to produce the bowl which was very dangerous or 93.59% risk. After the employment of new sitting posture, the work risk was lower 48.41% or moderate risk. When considering in details, it was found that: 1) the traditional sitting posture could create work risk at 88.89% while the new sitting posture could create the work risk at 58.86%. 2) About the environmental pollution, with the traditional sitting posture, workers exposed to the polluted fume from welding at 61.11% while with the new sitting posture workers exposed to the polluted fume from welding at 40.47%. 3) On accidental risk, with the traditional sitting posture, workers exposed to the accident from welding at 94.44% while with the new sitting posture workers exposed to the accident from welding at 62.54%.

Keywords: occupational health safety, environment at work, Monk’s food bowl, machine intelligence

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Authors: Daniel Nieto, Ramiro Couceiro

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Microfluidic chips have demonstrated their significant application potentials in microbiological processing and chemical reactions, with the goal of developing monolithic and compact chip-sized multifunctional systems. Heat generation and thermal control are critical in some of the biochemical processes. The paper presents a laser direct-write technique for rapid prototyping and manufacturing of microheater chips and its applicability for perfusion cell culture outside a cell incubator. The aim of the microheater is to take the role of conventional incubators for cell culture for facilitating microscopic observation or other online monitoring activities during cell culture and provides portability of cell culture operation. Microheaters (5 mm × 5 mm) have been successfully fabricated on soda-lime glass substrates covered with aluminum layer of thickness 120 nm. Experimental results show that the microheaters exhibit good performance in temperature rise and decay characteristics, with localized heating at targeted spatial domains. These microheaters were suitable for a maximum long-term operation temperature of 120ºC and validated for long-time operation at 37ºC. for 24 hours. Results demonstrated that the physiology of the cultured SW480 adenocarcinoma of the colon cell line on the developed microheater chip was consistent with that of an incubator.

Keywords: laser microfabrication, microheater, bioengineering, cell culture

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Authors: Maryam Heidari, James H. Jones Jr.

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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Vakhtang Geladze, Nana Bolashvili, Nino Machavariani, Tamazi Karalashvili, Nino Chikhradze, Davit Kartvelishvili

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Fresh water deficit is one of the most important global problems today. In the countries with scarce water resources, they often become a reason of armed conflicts. The peaceful settlement of relations connected with management and water consumption issues within and beyond the frontiers of the country is an important guarantee of the region stability. The said problem is urgent in Georgia as well because of its water objects are located at the borders and the transit run-off that is 12% of the total one. Fresh water resources are the major natural resources of Georgia. Despite of this, water supply of population at its Eastern part is an acute issue. Southeastern part of the country has been selected to carry out the research. This region is notable for deficiency of water resources in the country. The region tends to desertification which aggravates fresh water problem even more and presumably may lead to migration of local population from the area. The purpose of study was creation geographical information system (GIS) of water resources. GIS contains almost all layers of different content (water resources, springs, channels, hydrological stations, population water supply, etc.). The results of work provide an opportunity to identify the resource potential of the mentioned region, control and manage it, carry out monitoring and plan regional economy.

Keywords: desertification, GIS, irrigation, water resources

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Authors: Ambra Giovannelli, Erika Maria Archilei

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The amount of the electrical power required by refrigeration systems is relevant worldwide. It is evaluated in the order of 15% of the total electricity production taking refrigeration and air-conditioning into consideration. For this reason, in the last years several energy saving techniques have been proposed to reduce the power demand of such plants. The paper deals with the development of an innovative internal recovery system for cryogenic cooling plants. Such a system consists in a Compressor-Expander Group (CEG) designed on the basis of the automotive turbocharging technology. In particular, the paper is focused on the design of the expander, the critical component of the CEG system. Due to the low volumetric flow entering the expander and the high expansion ratio, a commercial turbocharger expander wheel was strongly modified. It was equipped with a transonic nozzle, designed to have a radially inflow full admission. To verify the performance of such a machine and suggest improvements, two different set of nozzles have been designed and modelled by means of the commercial Ansys-CFX software. steady-state 3D CFD simulations of the second-generation prototype are presented and compared with the initial ones.

Keywords: vapour cCompression systems, energy saving, refrigeration plant, organic fluids, radial turbine

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Authors: Alexandru Gridan, Georgeta Ionescu, Ovidiu Ionescu, Ramon Jurj, George Sirbu, Mihai Fedorca

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The Brown Bear population size in Romania is approximately 7300-7600 individuals, which is projected to be 3000 individuals over the ecological carrying capacity. The Habitats Directive imposed certain protection rules on European Union (EU) Member States with Brown Bear populations. These however allow countries like Sweden, Croatia, Slovakia, Estonia to hunting as management tool, harvesting up to 10% of the surplus bear population annually. From the point Romania joined the EU to 2016, active conservation management has contributed to maintaining the highest and most genetically diverse Brown Bear population in Europe. Importantly, there has been good coexistence between people and bears and low levels of human-bear conflict. After social pressure and campaigning by some non-governmental organisations citing issues over monitoring, the environment minister decided in September 2016 to stop the use of hunting as a management tool for bears. Against this background, this paper provides a set of recommendations to resolve the current conflict in Romania. These include the need for collaborative decision-making to reduce conflicts between stakeholders and mechanisms to reduce current human-bear conflicts, which have increased by 50 percent in the past year.

Keywords: bear, bear population, bear management, wildlife conflict

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Authors: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

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Authors: Juliza Hidayati, Yesie M. Sinuhaji, Sawarni Hasibuan

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A company producing drinking water through many incompatibility issues that affect supply chain performance. The study was conducted to determine the factors that affect the performance of the supply chain and improve it. To obtain the dominant factors affecting the performance of the supply chain used Analytic Network Process, while to improve performance is done by using Kaizen. Factors affecting the performance of the supply chain to be a reference to identify the cause of the non-conformance. Results weighting using ANP indicates that the dominant factor affecting the level of performance is the precision of the number of shipments (15%), the ability of the fulfillment of the booking amount (12%), and the number of rejected products when signing (12%). Incompatibility of the factors that affect the performance of the supply chain are identified, so that found the root cause of the problem is most dominant. Based on the weight of Risk Priority Number (RPN) gained the most dominant root cause of the problem, namely the poorly maintained engine, the engine worked for three shifts, machine parts that are not contained in the plant. Improvements then performed using the Kaizen method of systematic and sustainable.

Keywords: analytic network process, booking amount, risk priority number, supply chain performance

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Authors: Shehu Usman Hassan

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Published accounting information in financial statements are required to provide various users - shareholders, employees, suppliers, creditors, financial analysts, stockbrokers and government agencies – with timely and reliable information useful for making prudent, effective and efficient decisions. The widespread failure in the financial information quality has created the need to improve the financial information quality and to strengthen the control of managers by setting up good firms structures. This paper investigates firm attributes from perspective of structure, monitoring, performance elements of listed deposit money banks in Nigeria. The study adopted correlational research design with balanced panel data of 14 banks as sample of the study using multiple regression as a tool of analysis. The result reveals that firms attributes (leverage, profitability, liquidity, bank size and bank growth) has as significant influence on earnings quality of listed deposit money banks in Nigeria after the adoption of IFRS, while the pre period shows that the selected firm attributes has no significant impact on earnings quality. It is therefore concluded that the adoption of IFRS is right and timely.

Keywords: earnings quality, firm attributes, listed deposit money bank, Nigeria

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Authors: K. K. A. Bakhti, D. Mottet, J. Froger, I. Laffont

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Background: After a cerebrovascular accident (or stroke), many patients use excessive trunk movements to move their paretic hand towards a target (while the elbow is maintained flexed) even though they can use the upper-limb when the trunk is restrained. This phenomenon is labelled learned non-use and is known to be detrimental to neuroplasticity and recovery. Objective: The aim of this study is to quantify learned non-use of the paretic upper limb during a hand reaching task using 3D movement analysis. Methods: Thirty-four participants post supratentorial stroke were asked to reach a cone placed in front of them at 80% of their arm length. The reaching movement was repeated 5 times with the paretic hand, and then 5 times with the less-impaired hand. This sequence was first performed with the trunk free, then with the trunk restrained. Learned non-use of the upper-limb (LNUUL) was obtained from the difference of the amount of trunk compensation between the free trunk condition and the restrained trunk condition. Results: LNUUL was significantly higher for the paretic hand, with individual values ranging from 1% to 43%, and one-half of the patients with an LNUUL higher than 15%. Conclusions: Quantification of LNUUL can be used to objectively diagnose patients who need trunk rehabilitation. It can be also used for monitoring the rehabilitation progress. Quantification of LNUUL may guide upper-limb rehabilitation towards more optimal motor recovery avoiding maladaptive trunk compensation and its consequences on neuroplasticity.

Keywords: learned non-use, rehabilitation, stroke, upper limb

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Authors: L. L. Ivy-Yap, H. A. Bekhet

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As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 periods. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationary of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modeled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO2 emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: co-integration, elasticity, granger causality, Malaysia, residential electricity consumption

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Authors: Ismail Seçer, Kerime Meryem Dereli̇oğlu

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This study is conducted to determine the effects of group counseling program on secondary school 9th grade students’ assertiveness skills. The study group was formed of 100 students who have received education in Erzurum Kültür Elementary School in 2015-2016 education years. RAE-Rathus Assertiveness Schedule developed by Voltan Acar was applied on this group to gather data. 40 students who got lower grades from the inventory were divided randomly into experimental and control groups. Each group is formed of 20 students. Group counseling program was carried out on the experimental group to improve the students’ assertiveness skills for 8 weeks. Single-way and two-way analysis of covariance (ANCOVA) were used in the analysis of the data. The data was analyzed by using the SPSS 19.00. The results of the study show that assertiveness skills of the students who participate in the group counseling program increased meaningfully compared to the control group and pre-experiment. Besides, it was determined that the change observed in the experimental group occurred separately from the age and socio-economic level variables, and it was determined with the monitoring test applied after four months that this affect was continued. According to this result, it can be said that the applied group counseling program is an effective means to improve the assertiveness skills of secondary school students.

Keywords: high school, assertiveness, assertiveness inventory, assertiveness education

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Authors: Bachir Chemani, Rachid Halfaoui

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The aim of study was to evaluate pressure distribution characteristics of the elastic textile bandages using two instrumental techniques: a prototype Instrument and a load Transference. The prototype instrument which simulates shape of real leg has pressure sensors which measure bandage pressure. Using this instrument, the results show that elastic textile bandages presents different pressure distribution characteristics and none produces a uniform distribution around lower limb. The load transference test procedure is used to determine whether a relationship exists between elastic textile bandage structure and pressure distribution characteristics. The test procedure assesses degree of load, directly transferred through a textile when loads series are applied to bandaging surface. A range of weave fabrics was produced using needle weaving machine and a sewing technique. A textile bandage was developed with optimal characteristics far superior pressure distribution than other bandages. From results, we find that theoretical pressure is not consistent exactly with practical pressure. It is important in this study to make a practical application for specialized nurses in order to verify the results and draw useful conclusions for predicting the use of this type of elastic band.

Keywords: textile, cotton, pressure, venous ulcers, elastic

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

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Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: machine learning, wearable devices, user interface, user experience, internet of things

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Authors: Ashish Ankus Yerunkar, Ravi Terkar

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Study aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality as well as productivity with special emphasis on reduction of cutting tool flank wear, because reduction in flank wear ensures increase in tool life. The predicted optimal setting ensured minimization of surface roughness. Purpose of this paper is focused on the analysis of optimum cutting conditions to get lowest surface roughness in turning SCM 440 alloy steel by Taguchi method. Design for the experiment was done using Taguchi method and 18 experiments were designed by this process and experiments conducted. The results are analyzed using ANOVA method. Taguchi method has depicted that the depth of cut has significant role to play in producing lower surface roughness followed by feed. The Cutting speed has lesser role on surface roughness from the tests. The vibrations of the machine tool, tool chattering are the other factors which may contribute poor surface roughness to the results and such factors ignored for analyses. The inferences by this method will be useful to other researches for similar type of study and may be vital for further research on tool vibrations, cutting forces etc.

Keywords: surface roughness (ra), machining, dry turning, taguchi method, turning process, anova method, mahr perthometer

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Authors: Fekkak Bouazza, Menaa Mohamed, Loukriz Abdelhamid, Krim Mohamed L.

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This paper presents modeling and control strategy for the grid connected wind turbine system based on Permanent Magnet Synchronous Generator (PMSG). The considered system is based on back-to-back converter topology. The Grid Side Converter (GSC) achieves the DC bus voltage control and unity power factor. The Machine Side Converter (MSC) assures the PMSG speed control. The PMSG is used as a variable speed generator and connected directly to the turbine without gearbox. The pitch angle control is not either considered in this study. Further, Optimal Tip Speed Ratio (OTSR) based MPPT control strategy is used to ensure the most energy efficiency whatever the wind speed variations. A filter (L) is put between the GSC and the grid to reduce current ripple and to improve the injected power quality. The proposed grid connected wind system is built under MATLAB/Simulink environment. The simulation results show the feasibility of the proposed topology and performance of its control strategies.

Keywords: wind, grid, PMSG, MPPT, OTSR

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Authors: A. Lubis, L. Setiawati, A. R. Setyoningrum, A. Suryawan, Irwanto

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Asthma is a condition that causing chronic health problems in children. In addition to basic therapy against disease, we must try to reduce the impact of chronic health problems and also optimize their medical aspect of growth and development. A boy with mild asthma attack frequent episode did not showed any improvement with medical treatment and his asthma control test was 11. From radiologic examination he got hyperaerated lung and billateral sinusitis maxillaris; skin test results were house dust, food and pet allergy; an overweight body; bad school grades; psychological and environmental problem. We followed and evaluated this boy in 6 months, treated holistically. Even we could not do much on environmental but no more psychological and school problems, his on a good bodyweight and his asthma control test was 22. A case of a child with mild asthma attack frequent episode was reported. Asthma clinical course show no significant improvement when other predisposing factor is not well-controlled and a child’s growth and development may be affected. Improving condition of the patient can be created with the help of loving and caring way of nurturing from the parents and supportive peer group. Therefore, continuous and consistent monitoring is required because prognosis of asthma is generally good when regularly and properly controlled.

Keywords: asthma, chronic health problems, growth, development

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Authors: Rim Chang Hyon, Song Hak Jin, Song Kwang Hyok, Jong Ki Hun

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The calibration of the articulated arm coordinate measuring machine (AACMM) is key to improving calibration accuracy and saving calibration time. To reduce the time consumed for calibration, we should choose the proper calibration gauges and develop a reasonable calibration method. In addition, we should get the exact optimal solution by accurately removing the rough errors within the experimental data. In this paper, we present a calibration method of the portable coordinate measuring arm (PCMA) using the 1.2m long bar guage with cone-holes. First, we determine the locations of the bar gauge and establish an optimal objective function for identifying the structural parameter errors. Next, we make a mathematical model of the calibration algorithm and present a new mathematical method to remove the rough errors within calibration data. Finally, we find the optimal solution to identify the kinematic parameter errors by using Levenberg-Marquardt algorithm. The experimental results show that our calibration method is very effective in saving the calibration time and improving the calibration accuracy.

Keywords: AACMM, kinematic model, parameter identify, measurement accuracy, calibration

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Authors: Sophonie Sarielle Jean Jacques Bertrand

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Background: Acute flaccid paralysis (PFA) is the sudden weakness or paralysis of muscles seen in children under 15 years of age. According to the WHO, PFA remains a real public health problem. For Haiti, the PFA represents a national priority. This study aims to describe the epidemiological profile of cases of Acute Flaccid Paralysis (PFA) in Haiti from 2018-2020. Methods: A descriptive cross-sectional study covering the period of 2018-2021 was carried out. epidemiological surveillance data PFA exported to Integrated Monitoring Evaluation Surveillance (MESI) were used. Sociodemographic variables were studied. Prevalence and clinical mortality rate were calculated. Epi Info 7.2 and Excel 2016 were used for data analysis. Results: 76 AFP cases were recorded for the period, or 13 (17%) in 2018, 23 (30%) in 2019, 8 (11%) in 2020 32 (42%) in 2021. Children aged 5-14 years accounted for 36% of cases (n= 26). The M/F sex ratio was 0.52, with a predominance of the female sex. The clinical mortality rate was 2.6%. The prevalence was 1.77/100,000 people. Conclusion: From 2018-2021, 76 cases of PFA cases were recorded in the 10 departments of the country, of which the West department was the most affected. Maintaining high vaccination coverage and a standard acute flaccid paralysis surveillance system are essential for the eradication of this condition. Strengthen epidemiological surveillance of PFA.

Keywords: epidemiology, PFA, Haïti, MESI

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Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

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Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

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Authors: MohammadSadegh SaeediFakher, Jafar Rouzegar, Hassan Assaee

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In this research, mechanical behavior and energy absorption capacity of empty and rubber-filled brazen circular tubes under quasi-static axial loading are investigated, experimentally. The brazen tubes were cut out of commercially available brazen circular tubes with the same length and diameter. Some of the specimens were filled with rubbers with three different shores and also, an empty tube was prepared. The specimens were axially compressed between two rigid plates in a quasi-static process using a Zwick testing machine. Load-displacement diagrams and energy absorption of the tested tubes were extracted from experimental data. The results show that filling the brazen tubes with rubber causes those to absorb more energy and the energy absorption of specimens are increased by increasing the shore of rubbers. In comparison to the empty tube, the first fold for the rubber-filled tubes occurs at lower load and it can be concluded that the rubber-filled tubes are better energy absorbers than the empty tubes. Also, in contrast with the empty tubes, the tubes that were filled with lower rubber shore deform asymmetrically.

Keywords: axial compression, quasi-static loading, folding, energy absorbers, rubber-filled tubes

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Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

Abstract:

Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

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Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

Abstract:

Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: application, environment, insecurity, sensor, wireless sensor network

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Authors: Sufia Maroof

Abstract:

This empirical study investigated the web-translations of five Pakistani public offices (FPSC, FIA, HEC, USB, and Ministry of Finance) offering Urdu tab as an option to access information on their official websites. Triangulation of quantitative and qualitative research design informed the researcher of the semantic, lexical and syntactic caveats in these translations. The study hypothesized that majority of the Pakistani population is oblivious of the Supreme Court’s amendments in language policy concerning national and official language; hence, Urdu web-translations of the public departments have not been accessed effectively. Firstly, the researcher conducted an online survey, comprising of two sections, close ended and short answer based questions. Secondly, the researcher compiled corpus of the five selected websites in a tabular form to compare the data. Thirdly, the administrators of the departments had been contacted regarding the methods of translation and the expertise of the personnel involved. The corpus was assessed for TQA after examining the lexical, semantic, syntactical and technical alignment inaccuracies and imperfections. The study suggests the public offices to invest in their Urdu webs by either hiring expert translators or engaging expertise of a translation agency for this project to offer quality translation to public.

Keywords: machine translations, public offices, Urdu translations, websites

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Authors: Md Mizanur Rahman, M. Aslam Alam, Muhammad Abu Yusuf

Abstract:

The abundance of Jellyfish across the coasts of the Bay of Bengal is increasing sharply due to marine pollution, increased sea acidification and climate change. Jellyfish draws our attention to address the local and global stressors. This also indicates that something wrong is happening in this bay behind the scenes. This study aimed to investigate how the policy framework governing the sea can be reformed. To do so, this study evaluated the existing policy, regulatory and institutional framework. Empirical data were collected from the middle coastal zone of Bangladesh. The secondary literature on policy, legal documents, and institutional arrangements were reviewed. The causes of poor coordination among different public sectors and non-compliance of laws were identified. The key findings show that despite the existing of Department of Environment, poor coordination with other departments, and lack of logistics and technical staffs have resulted in severe marine pollution and degradation of coastal and marine living resources. The existing policies had no monitoring and evaluation mechanisms. Non-compliance of the existing laws has been fueling the problems. This study provides an integrated policy and a guideline for updating the legal and institutional mechanism to manage coastal and marine living resources sustainably in Bangladesh to achieve Sustainable Development Goal 14.

Keywords: legal, institutional, framework, jellyfish

Procedia PDF Downloads 107