Search results for: sensing time

Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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Authors: Roberta Ranielle M. de Freitas, Vagner R. Botaro

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The relationship between biodegradation and mechanical behavior is fundamental for studies of the application of cellulose acetate films as a possible material for biodegradable packaging. In this work, the biodegradation of cellulose acetate (CA) with DS 2.5 was analyzed in simulated soil. CA films were prepared by casting and buried in the simulated soil. Samples were taken monthly and analyzed, the total time of biodegradation was 6 months. To characterize the biodegradable CA, the DMA technique was employed. The main result showed that the time of exposure to the simulated soil affects the mechanical properties of the films and the values of crystallinity. By DMA analysis, it was possible to conclude that as the CA is biodegraded, its mechanical properties were altered, for example, storage modulus has increased with biodegradation and the modulus of loss has decreased. Analyzes of DSC, XRD, and FTIR were also carried out to characterize the biodegradation of CA, which corroborated with the results of DMA. The observation of the carbonyl band by FTIR and crystalline indices obtained by XRD were important to evaluate the degradation of CA during the exposure time.

Keywords: biodegradation, cellulose acetate, DMA, simulated soil

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Authors: Ayan Chakraborty, BV. Rathish Kumar

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Off-late many models in viscoelasticity, signal processing or anomalous diffusion equations are formulated in fractional calculus. Tempered fractional calculus is the generalization of fractional calculus and in the last few years several important partial differential equations occurring in the different field of science have been reconsidered in this term like diffusion wave equations, Schr$\ddot{o}$dinger equation and so on. In the present paper, a time-dependent tempered fractional diffusion equation of order $\gamma \in (0,1)$ with forcing function is considered. Existence, uniqueness, stability, and regularity of the solution has been proved. Crank-Nicolson discretization is used in the time direction. B spline finite element approximation is implemented. Generally, B-splines basis are useful for representing the geometry of a finite element model, interfacing a finite element analysis program. By utilizing this technique a priori space-time estimate in finite element analysis has been derived and we proved that the convergent order is $\mathcal{O}(h²+T²)$ where $h$ is the space step size and $T$ is the time. A couple of numerical examples have been presented to confirm the accuracy of theoretical results. Finally, we conclude that the studied method is useful for solving tempered fractional diffusion equations.

Keywords: B-spline finite element, error estimates, Gronwall's lemma, stability, tempered fractional

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Authors: Aniket Tiwari, Ameya London

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Web-based student attendance management system is required to assist the faculty and the lecturer for the time-consuming process. For this purpose, GSM/GPRS (Global System for Mobile Communication/General Packet Radio Service) based student’s attendance management system using RFID (Radio Frequency Identification) is a much convenient method to take the attendance. Student is provided with the RFID tags. When student comes near to the reader, it will sense the respective student and update attendance. The whole process is controlled using the microcontroller. The main advantage of this system is that it reduced the complexity comparison to student attendance system using RF technology. This system requires only one microcontroller for the operation, it is real time process. This paper reviews some of these monitoring systems and proposes a GPRS based student attendance system. The system can be easily accessed by the lecturers via the web and most importantly, the reports can be generated in real-time processing, thus, provides valuable information about the students’ commitments in attending the classes.

Keywords: RFID reader, RFID tags, student, attendance

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

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The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

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Authors: John Wangui, Charles Gachene, Stephen Mureithi, Boniface Kiteme

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Land use changes caused by demographic, natural variability, economic, technological and policy factors affect the goods and services derived from an ecosystem. In the past few decades, Lake Ol Bolossat catchment in Nyandarua County Kenya has been facing challenges of land cover changes threatening its capacity to perform ecosystems functions and adversely affecting communities and ecosystems downstream. This study assessed land cover changes in the catchment for a period of twenty eight years (from 1986 to 2014). Analysis of three Landsat images i.e. L5 TM 1986, L5 TM 1995 and L8 OLI/TIRS 2014 was done using ERDAS 9.2 software. The results show that dense forest, cropland and area under water increased by 27%, 29% and 3% respectively. On the other hand, open forest, dense grassland, open grassland, bushland and shrubland decreased by 3%, 3%, 11%, 26% and 1% respectively during the period under assessment. The lake was noted to have increased due to siltation caused by soil erosion causing a reduction in Lake’s depth and consequently causing temporary flooding of the wetland. The study concludes that the catchment is under high demographic pressure which would lead to resource use conflicts and therefore formulation of mitigation measures is highly recommended.

Keywords: land cover, land use change, land degradation, Nyandarua, Remote sensing

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Pallavi Thacker, H. P. Mathur

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This paper tries to find out from the available literature the status of Competitive Advantage. It has been stated a number of times that firms must strive to attain sustainable competitive advantage; but is the concept of sustainability of advantage still valid in this new diversified and too-rapidly changing world? The paper reaches a conclusion that the answer is “no”. Gone is the time when once attained position could easily be retained forever or at-least for a substantial amount of time. We live in a time which is very much globalised. We are used to a high level of competition from all directions. Technological advances, developed human capital, flexibility and end number of factors make the sustenance of competitive advantage difficult. This paper analyses competitive advantage from the view points of Michael Porter (who talks about sustainability) and Rita Gunther McGrath (who says competitive advantage can no more be sustained). It uses many examples and evidences from papers, journals and news. A research in this area is very much required (especially in a developing country like India) so that industries, firms and people can find out the suitable strategies that match with the changing times.

Keywords: competitive advantage, sustainable, transient, globalisation

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Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

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In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: non-minimum phase system, optimal linear quadratic tracker, proportional plus integral observer, state and disturbance estimator

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Zahra Ahmadi, Fazlollah Adibnia

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Scheduling of tasks and the optimal allocation of resources in the cloud are based on the dynamic nature of tasks and the heterogeneity of resources. Applications that are based on the scientific workflow are among the most widely used applications in this field, which are characterized by high processing power and storage capacity. In order to increase their efficiency, it is necessary to plan the tasks properly and select the best virtual machine in the cloud. The goals of the system are effective factors in scheduling tasks and resource selection, which depend on various criteria such as time, cost, current workload and processing power. Multi-criteria decision-making methods are a good choice in this field. In this research, a new method of work planning and resource allocation in a heterogeneous environment based on the modified AHP algorithm is proposed. In this method, the scheduling of input tasks is based on two criteria of execution time and size. Resource allocation is also a combination of the AHP algorithm and the first-input method of the first client. Resource prioritization is done with the criteria of main memory size, processor speed and bandwidth. What is considered in this system to modify the AHP algorithm Linear Max-Min and Linear Max normalization methods are the best choice for the mentioned algorithm, which have a great impact on the ranking. The simulation results show a decrease in the average response time, return time and execution time of input tasks in the proposed method compared to similar methods (basic methods).

Keywords: hierarchical analytical process, work prioritization, normalization, heterogeneous resource allocation, scientific workflow

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Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: automation, optimization, paradigm, RTC

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Authors: Ahmed Osama, Hassan A. Mahdy, Khalid A. Kandil, Mohamed Elhabiby

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Automatic Vehicle Location systems (AVL) have been used worldwide for more than twenty years and have showed great success in public transportation management and monitoring. Cairo public bus service suffers from several problems such as unscheduled stops, unscheduled route deviations, and inaccurate schedules, which have negative impacts on service reliability. This research aims to study those problems for a selected bus route in Cairo using a prototype AVL system. Experimental trips were run on the selected route; and the locations of unscheduled stops, regions of unscheduled deviations, along with other trip time and speed data were collected. Data was analyzed to demonstrate the reliability of passengers on the unscheduled stops compared to the scheduled ones. Trip time was also modeled to assess the unscheduled stops’ impact on trip time, and to check the accuracy of the applied scheduled trip time. Moreover, frequency and length of the unscheduled route deviations, as well as their impact on the bus stops, were illustrated. Solutions were proposed for the bus service deficiencies using the AVL system. Finally, recommendations were proposed for further research.

Keywords: automatic vehicle location, public transportation, unscheduled stops, unscheduled route deviations, inaccurate schedule

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Authors: Ghorbanali Mohammadi

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New approaches to sequencing mixed-model manufacturing systems are present. These approaches have attracted considerable attention due to their potential to deal with difficult optimization problems. This paper presents Multi-Objective Simulated Annealing Algorithms (MOSAA) approaches to the Just-In-Time (JIT) sequencing problem where workload-smoothing (WL) and the number of set-ups (St) are to be optimized simultaneously. Mixed-model assembly lines are types of production lines where varieties of product models similar in product characteristics are assembled. Moreover, this type of problem is NP-hard. Two annealing methods are proposed to solve the multi-objective problem and find an efficient frontier of all design configurations. The performances of the two methods are tested on several problems from the literature. Experimentation demonstrates the relative desirable performance of the presented methodology.

Keywords: scheduling, just-in-time, mixed-model assembly line, sequencing, simulated annealing

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Authors: Somayyeh Karimiyan

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To evaluate the seismic vulnerability of vital offshore structures with the highest possible precision, Nonlinear Time History Analyses (NLTHA), is the most reliable method. However, since it is very time-consuming, a quick procedure is greatly desired. This paper presents a quick method by combining the Push Over Analysis (POA) and the NLTHA. The POA is preformed first to recognize the more critical members, and then the NLTHA is performed to evaluate more precisely the critical members’ vulnerability. The proposed method has been applied to jacket type structure. Results show that combining POA and NLTHA is a reliable seismic evaluation method, and also that none of the earthquake characteristics alone, can be a dominant factor in vulnerability evaluation.

Keywords: jacket structure, seismic evaluation, push-over and nonlinear time history analyses, critical members

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Authors: Kamal Bahrin Jaafar

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The study area is located at Bukit Kukus, Penang where the construction of twin road project in ongoing. A landslide event has occurred on 19th October 2018, which causes fatal deaths. The purpose of this study is to figure out the causes of failure, the estimated volume of failure, and its balance. The study comprises of unmanned aerial vehicle (UAV) sensing and resistivity survey. The resistivity method includes spreading three lines of 200m length resistivity survey with the depth of penetration in the subsurface not exceeding 35m. The result of UAV shows the current view of the site condition. Based on resistivity result, the dominant layer in the study area consists of residual soil/filling material with a thickness of more than 35m. Three selected cross sections from construction drawing are overlain with the current cross sections to understand more on the condition of the subsurface profile. By comparison, there is a difference between past and present topography. The combination of result from the previous data and current condition shows the calculated volume of failure is 85,000 m³, and its balance is 50,000 m³. In conclusion, the failure occurs since the contractor has conducted the construction works without following the construction drawing supplied by the consultant. Besides, the cause of failure is triggered by the geology condition, such as a fault that should be considered prior to the commencement of work.

Keywords: UAV, landslide, resistivity survey, cause of failure

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Authors: S. A. Tabatabaei, S. Aarabi

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Predicting the hot mix asphalt (HMA) response and performance is a challenging task because of the subjectivity of HMA under the complex loading and environmental condition. The behavior of HMA is a function of temperature of loading and also shows the time and rate-dependent behavior directly affecting design criteria of mixture. Velocity of load passing make the time and rate. The viscoelasticity illustrates the reaction of HMA under loading and environmental conditions such as temperature and moisture effect. The behavior has direct effect on design criteria such as tensional strain and vertical deflection. In this paper, the computational framework for viscoelasticity and implementation in 3D dimensional HMA model is introduced to use in finite element method. The model was lied under various repeated loading conditions at constant temperature. The response of HMA viscoelastic behavior is investigated in loading condition under speed vehicle and sensitivity of behavior to the range of speed and compared to HMA which is supposed to have elastic behavior as in conventional design methods. The results show the importance of loading time pulse, unloading time and various speeds on design criteria. Also the importance of memory fading of material to storing the strain and stress due to repeated loading was shown. The model was simulated by ABAQUS finite element package

Keywords: viscoelasticity, finite element method, repeated loading, HMA

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Authors: Rashid Mahmood, Muhammad Sufyan, Nasir Ahmed

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The MANETs have lessened transportation and decentralized network. There are numerous basis of routing protocols. We derived the MANETs protocol into three major categories like Reactive, Proactive and hybrid. In these protocols, we discussed only some protocols like Distance Sequenced Distance Vector (DSDV), Ad hoc on Demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The AODV and DSR are both reactive type of protocols. On the other hand, DSDV is proactive type protocol here. We compare these routing protocols for network security estimated by network simulator (NS-2). In this dissertation some parameters discussed such as simulation time, packet size, number of node, packet delivery fraction, push time and speed etc. We will construct all these parameters on routing protocols under suitable conditions for network security measures.

Keywords: DSDV, AODV, DSR NS-2, PDF, push time

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Authors: Manit Pollar

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Identifying the dengue epidemic periods early would be helpful to take necessary actions to prevent the dengue outbreaks. Providing an accurate prediction on dengue epidemic seasons will allow sufficient time to take the necessary decisions and actions to safeguard the situation for local authorities. This study aimed to develop a forecasting model on number of dengue incidences in Nakhon Si Thammarat Province, Southern Thailand using time series analysis. We develop Seasonal Autoregressive Moving Average (SARIMA) models on the monthly data collected between 2003-2011 and validated the models using data collected between January-September 2012. The result of this study revealed that the SARIMA(1,1,0)(1,2,1)12 model closely described the trends and seasons of dengue incidence and confirmed the existence of dengue fever cases in Nakhon Si Thammarat for the years between 2003-2011. The study showed that the one-step approach for predicting dengue incidences provided significantly more accurate predictions than the twelve-step approach. The model, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

Keywords: SARIMA, time series model, dengue cases, Thailand

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Authors: Meryem Imane Babaghayou, Asma Abdelhafidi, Salem Fouad Chabira, Mohammed Sebaa

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A challenge of plastics industries is the realization of materials that resist the degradation in its application environment, and that to guarantee a longer life time therefore an optimal time of use. Blown extruded films of low-density polyethylene (LDPE) supplied by SABIC SAUDI ARABIA blown and extruded in SOFIPLAST company in Setif ALGERIA , have been subjected to climatic ageing in a sub-Saharan facility at Laghouat (Algeria) with direct exposure to sun. Samples were characterized by X-ray diffraction (XRD) and differential scanning calorimetry (DSC) techniques after prescribed amounts of time up to 8 months. It has been shown via these two techniques the impact of UV irradiation on the morphological development of a plastic material, especially the crystallinity degree which increases with exposure time. The reason of these morphological changes is related to photooxidative reactions leading to cross linking in the beginning and to chain scissions for an advanced stage of ageing this last ones are the first responsible. The crystallinity degree change is essentially controlled by the secondary crystallization of the amorphous chains whose mobility is enhanced by the chain scission processes. The diffusion of these short segments integrates the surface of the lamellae increasing in this way their thicknesses. The results presented highlight the complexity of the involved phenomena.

Keywords: Low Density poly (Ethylene), crystallinity, ageing, XRD, DSC

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Authors: N. P. Tien, S. Songsermpong, T. H. Quan

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Mung bean vermicelli is a popular food in Asian countries and is made from mung bean starch. The preparation process involves several steps, including drying, which affects the structure and quality of the vermicelli. This study aims to examine the effects of different drying technologies on the rehydration time and quality of mung bean vermicelli. Three drying technologies, namely hot air drying, microwave continuous drying, and microwave vacuum drying, were used for the drying process. The vermicelli strands were dried at 45°C for 12h in a hot air dryer, at 70 Hz of conveyor belt speed inverter in a microwave continuous dryer, and at 30 W.g⁻¹ of microwave power density in a microwave vacuum dryer. The results showed that mung bean vermicelli dried using hot air drying had the longest rehydration time of 12.69 minutes. On the other hand, vermicelli dried through microwave continuous drying and microwave vacuum drying had shorter rehydration times of 2.79 minutes and 2.14 minutes, respectively. Microwave vacuum drying also resulted in larger porosity, higher water absorption, and cooking loss. The tensile strength and elasticity of vermicelli dried using hot air drying were higher compared to microwave drying technologies. The sensory evaluation did not reveal significant differences in most attributes among the vermicelli treatments. Overall, microwave drying technology proved to be effective in reducing rehydration time and producing good-quality mung bean vermicelli.

Keywords: mung bean vermicelli, drying, hot air, microwave continuous, microwave vacuum

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Authors: Yoonjin Lee, Dongwook Hwang, Juhee Park, Woojin Park

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As undesirable sitting posture is known to be a major cause of musculoskeletal disorder of office workers, sitting has attracted attention on occupational health. However, there seems to be no consensus on what are safe and unsafe sitting behaviors. The purpose of this study was to characterize safe and unsafe behaviors based on scientific findings of sitting behavior. Three objectives were as follows; to identify different sitting behaviors measure used in ergonomics studies on safe sitting, for each measure identified, to find available findings or recommendations on safe and unsafe sitting behaviors along with relevant empirical grounds, and to synthesize the findings or recommendations to provide characterizations of safe and unsafe behaviors. A systematic review of electronic databases (Google Scholar, PubMed, Web of Science) was conducted for extensive search of sitting behavior. Key terms included awkward sitting position, sedentary sitting, dynamic sitting, sitting posture, sitting posture, and sitting biomechanics, etc. Each article was systemically abstracted to extract a list of studied sitting behaviors, measures used to study the sitting behavior, and presence of empirical evidence of safety of the sitting behaviors. Finally, characterization of safe and unsafe sitting behavior was conducted based on knowledge with empirical evidence. This characterization is expected to provide useful knowledge for evaluation of sitting behavior and about postures to be measured in development of sensing chair.

Keywords: sitting position, sitting biomechanics, sitting behavior, unsafe sitting

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Authors: Muhamad Azani Yahya, Vikneswaran Munikanan, Mohammed Alias Yusof

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There is the need to take the holistic approach in achieving sustainable construction for a contemporary practice. Sustainable construction is the practice that involved method of human preservation of the environment, whether economically or socially through responsibility, management of resources and maintenance utilizing support. This paper shows the correlation of achieving rapid construction with sustainable concepts using lean principles. Lean principles being used widely in the manufacturing industry, but this research will demonstrate the principles into building construction. Lean principle offers the benefits of stabilizing work flow and elimination of unnecessary work. Therefore, this principle contributes to time and waste reduction. The correlation shows that pulling factor provides the improvement of progress curve and stabilizing the time-quality relation. The finding shows the lean principles offer the elements of rapid construction synchronized with the elements of sustainability.

Keywords: sustainable construction, rapid construction, time reduction, lean construction

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Authors: Bello Gonzalez, Setten Van M., Brouwer M.

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The chicken small intestine represents a dynamic and complex organ in which the enzymatic digestion and absorption of nutrients take place. The development of an in vitro fermentation chicken small intestinal model could be used as an alternative to explore the interaction between the microbiota and nutrient metabolism and to enhance the efficacy of targeting interventions to improve animal health. In the present study we have developed an in vitro fermentation chicken ileum microbiota model for unrevealing the complex interaction of ileum microbial community under physiological conditions. A two-vessel continuous fermentation process simulating in real-time the physiological conditions of the ileum content (pH, temperature, microaerophilic/anoxic conditions, and peristaltic movements) has been standardized as a proof of concept. As inoculum, we use a pool of ileum microbial community obtained from chicken broilers at the age of day 14. The development and validation of the model provide insight into the initial characterization of the ileum microbial community and its dynamics over time-related to nutrient assimilation and fermentation. Samples can be collected at different time points and can be used to determine the microbial compositional structure, dynamics, and diversity over time. The results of studies using this in vitro model will serve as the foundation for the development of a whole small intestine in vitro fermentation chicken gastrointestinal model to complement our already established in vitro fermentation chicken caeca model. The insight gained from this model could provide us with some information about the nutritional strategies to restore and maintain chicken gut homeostasis. Moreover, the in vitro fermentation model will also allow us to study relationships between gut microbiota composition and its dynamics over time associated with nutrients, antimicrobial compounds, and disease modelling.

Keywords: broilers, in vitro model, ileum microbiota, fermentation

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Authors: Mohamed Elbehery

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Historical textiles in the burial environment or in museums are exposed to many types of stains and dirt that are associated with historical textiles by multiple chemical bonds that cause damage to historical textiles. The cleaning process must be carried out with great care, with no irreversible damage, and sediments removed without affecting the original material of the surface being cleaned. Science and technology continue to provide innovative systems in the bio-cleaning process (using pure enzymes) of historical textiles and artistic surfaces. Lipase and α-amylase were immobilized on nanoparticles of alginate/κ-carrageenan nanoparticle complex and used in historical textiles cleaning. Preparation of nanoparticles, activation, and enzymes immobilization were characterized. Optimization of loading time and units of the two enzymes were done. It was found that, the optimum time and units of amylase were 4 hrs and 25U, respectively. While, the optimum time and units of lipase were 3 hrs and 15U, respectively. The methods used to examine the fibers using a scanning electron microscope equipped with an X-ray energy dispersal unit: SEM with EDX unit.

Keywords: nanoparticles, enzymes, immobilization, textiles

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: They Shao Peng

Abstract:

Machine vision system for inspection is an automated technology that is normally utilized to analyze items on the production line for quality control purposes, it also can be known as an automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws, and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models, which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model, are trained, evaluated, and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage.

Keywords: automated visual inspection, deep learning, machine vision, mobile application

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Authors: Randa Alharbi, Vladislav Vyshemirsky

Abstract:

Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Sunita Singh, Rajani Srivastava

Abstract:

For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

Procedia PDF Downloads 362