Search results for: time prediction algorithms

Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

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This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

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Authors: Rima Al-Awadhi, Abdul Jaleel Tharayil

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On a regular basis, KOC engages into various types of Projects. However, due to very nature and complexity involved, each project experience generates a lot of ‘learnings’ that need to be factored into while drafting a new contract and thus avoid repeating the same mistakes. But, many a time these learnings are localized and remain as tacit leading to scope re-work, larger cycle time, schedule overrun, adjustment orders and claims. Also, these experiences are not readily available to new employees leading to steep learning curve and longer time to competency. This is to share our experience in designing and implementing a process driven architecture for the ‘lessons learnt’ knowledge sharing framework in KOC. It high-lights the ‘lessons learnt’ sharing process adopted, integration with the organizational processes, governance framework, the challenges faced and learning from our experience in implementing a ‘lessons learnt’ framework.

Keywords: lessons learnt, knowledge transfer, knowledge sharing, successful practices, Lessons Learnt Workshop, governance framework

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Authors: Himayatullah Khan, Alena Fedorova

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The present paper analyses the income-consumption relationships in Pakistan using annual time series data from 1980-81 to 2010-1. The paper uses the Augmented Dickey-Fuller test to check the unit root and stationarity in these two time series. The paper finds that the two time series are nonstationary but stationary at their first difference levels. The Augmented Engle-Granger test and the Cointegrating Regression Durbin-Watson test imply that the two time series of consumption and income are cointegrated and that long-run marginal propensity to consume is 0.88 which is given by the estimated (static) equilibrium relation. The paper also used the error correction mechanism to find out to model dynamic relationship. The purpose of the ECM is to indicate the speed of adjustment from the short-run equilibrium to the long-run equilibrium state. The results show that MPC is equal to 0.93 and is highly significant. The coefficient of Engle-Granger residuals is negative but insignificant. Statistically, the equilibrium error term is zero, which suggests that consumption adjusts to changes in GDP in the same period. The short-run changes in GDP have a positive impact on short-run changes in consumption. The paper concludes that we may interpret 0.93 as the short-run MPC. The pair-wise Granger Causality test shows that both GDP and consumption Granger cause each other.

Keywords: cointegrating regression, Augmented Dickey Fuller test, Augmented Engle-Granger test, Granger causality, error correction mechanism

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Authors: Harold P. Villota, Alejandro Osorio B.

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The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

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Authors: H. Hajimolahoseini, J. Hashemi, D. Redfearn

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Background: Catheter ablation is an effective therapy for symptomatic atrial fibrillation (AF). The intracardiac electrocardiogram (IEGM) collected during this procedure contains precious information that has not been explored to its full capacity. Novel processing techniques allow looking at these recordings from different perspectives which can lead to improved therapeutic approaches. In our previous study, we showed that variation in amplitude measured through Shannon Entropy could be used as an AF recurrence risk stratification factor in patients who received Ibutilide before the electrograms were recorded. The aim of this study is to further investigate the effect of Ibutilide on characteristics of the recorded signals from the left atrium (LA) of a patient with persistent AF before and after administration of the drug. Methods: The IEGMs collected from different intra-atrial sites of 12 patients were studied and compared before and after Ibutilide administration. First, the before and after Ibutilide IEGMs that were recorded within a Euclidian distance of 3 mm in LA were selected as pairs for comparison. For every selected pair of IEGMs, the Probability Distribution Function (PDF) of the amplitude in time domain and magnitude in frequency domain was estimated using the regression analysis. The PDF represents the relative likelihood of a variable falling within a specific range of values. Results: Our observations showed that in time domain, the PDF of amplitudes was fitted to a Gaussian distribution while in frequency domain, it was fitted to a Rayleigh distribution. Our observations also revealed that after Ibutilide administration, the IEGMs would have significantly narrower short-tailed PDFs both in time and frequency domains. Conclusion: This study shows that the PDFs of the IEGMs before and after administration of Ibutilide represents significantly different properties, both in time and frequency domains. Hence, by fitting the PDF of IEGMs in time domain to a Gaussian distribution or in frequency domain to a Rayleigh distribution, the effect of Ibutilide can easily be tracked using the statistics of their PDF (e.g., standard deviation) while this is difficult through the waveform of IEGMs itself.

Keywords: atrial fibrillation, catheter ablation, probability distribution function, time-frequency characteristics

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Shan Zhang, Peter Suechting

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Predicting trade patterns is critical to decision-making in public and private domains, especially in the current context of trade disputes among major economies. In the past, U.S. recycling has relied heavily on strong demand for recyclable materials overseas. However, starting in 2017, a series of new recycling policies (bans and higher inspection standards) was enacted by multiple countries that were the primary importers of recyclables from the U.S. prior to that point. As the global trade flow of recycling shifts, some new importers, mostly developing countries in South and Southeast Asia, have been overwhelmed by the sheer quantities of scrap materials they have received. As the leading exporter of recyclable materials, the U.S. now has a pressing need to build its recycling industry domestically. With respect to the global trade in scrap materials used for recycling, the interest in this paper is (1) predicting how the export of recyclable materials from the U.S. might vary over time, and (2) predicting how international trade flows for recyclables might change in the future. Focusing on three major recyclable materials with a history of trade, this study uses data-driven and machine learning (ML) algorithms---supervised (shrinkage and tree methods) and unsupervised (neural network method)---to decipher the international trade pattern of recycling. Forecasting the potential trade values of recyclables in the future could help importing countries, to which those materials will shift next, to prepare related trade policies. Such policies can assist policymakers in minimizing negative environmental externalities and in finding the optimal amount of recyclables needed by each country. Such forecasts can also help exporting countries, like the U.S understand the importance of healthy domestic recycling industry. The preliminary result suggests that gravity models---in addition to particular selection macroeconomic predictor variables--are appropriate predictors of the total export value of recyclables. With the inclusion of variables measuring aspects of the political conditions (trade tariffs and bans), predictions show that recyclable materials are shifting from more policy-restricted countries to less policy-restricted countries in international recycling trade. Those countries also tend to have high manufacturing activities as a percentage of their GDP.

Keywords: environmental economics, machine learning, recycling, international trade

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Authors: Tien-Li Chang, Huang-Chi Huang, Zhao-Chi Chen, Wun-Yi Chen

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The droplet-based microfluidic are used as micro-reactors for chemical and biological assays. Hence, the precise addition of reagents into the droplets is essential for this function in the scope of lab-on-a-chip applications. To obtain the characteristics (size, velocity, pressure, and frequency of production) of droplets, this study describes an integrated on-chip method of real-time signal detection. By controlling and manipulating the fluids, the flow behavior can be obtained in the droplet-based microfluidics. The detection method is used a type of infrared sensor. Through the varieties of droplets in the microfluidic devices, the real-time conditions of velocity and pressure are gained from the sensors. Here the microfluidic devices are fabricated by polydimethylsiloxane (PDMS). To measure the droplets, the signal acquisition of sensor and LabVIEW program control must be established in the microchannel devices. The devices can generate the different size droplets where the flow rate of oil phase is fixed 30 μl/hr and the flow rates of water phase range are from 20 μl/hr to 80 μl/hr. The experimental results demonstrate that the sensors are able to measure the time difference of droplets under the different velocity at the voltage from 0 V to 2 V. Consequently, the droplets are measured the fastest speed of 1.6 mm/s and related flow behaviors that can be helpful to develop and integrate the practical microfluidic applications.

Keywords: microfluidic, droplets, sensors, single detection

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Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

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Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

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Authors: Raman Sharma, S. K. Jain

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Aims and Objectives: Fixation of the mesh during laparoscopic total extraperitoneal (TEP) repair of inguinal hernia is thought to be necessary to prevent recurrence. However, mesh fixation may increase surgical complications and postoperative pain. Our objective was to compare the outcomes of nonfixation with fixation of polypropylene mesh by metal tacks during TEP repair of inguinal hernia. Methods: Forty patients aged 18 to72 years with inguinal hernia were included who underwent laparoscopic TEP repair of inguinal hernia with (n=20) or without (n=20) fixation of the mesh. The outcomes were operative duration, postoperative pain score, cost, in-hospital stay, time to return to normal activity, and complications. Results: Patients in whom the mesh was not fixed had shorter mean operating time (p < 0.05). We found no difference between groups in the postoperative pain score, incidence of recurrence, in-hospital stay, time to return to normal activity and complications (P > 0.05). Moreover, a net cost savings was realized for each hernia repair performed without stapled mesh. Conclusions: TEP repair without mesh fixation resulted in the shorter operating time and lower operative cost with no difference between groups in the postoperative pain score, incidence of recurrence, in-hospital stay, time to return to normal activity and complications. All this contribute to make TEP repair without mesh fixation a better choice for repair of uncomplicated inguinal hernia, especially in developing nations with scarce resources.

Keywords: postoperative pain score, inguinal hernia, nonfixation of mesh, total extra peritoneal (TEP)

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Authors: Yasuyuki Takahashi, Akemi Yoshida, Hirotaka Shimada

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99mTc-2-methoxy-isobutyl-isonitrile (MIBI) and 99mTcmercaptoacetylgylcylglycyl-glycine (MAG3 ) are heat to 368-372K and are labeled with 99mTc-pertechnetate. Quality control (QC) of 99mTc-labeled radiopharmaceuticals is performed at hospitals, using liquid chromatography, which is difficult to perform in general hospitals. We used chromatography strips to simplify QC and investigated the effects of the test procedures on quality control. In this study is 99mTc- MAG3. Solvent using chloroform + acetone + tetrahydrofuran, and the gamma counter was ARC-380CL. The changed conditions are as follows; heating temperature, resting time after labeled, and expiration year for use: which were 293, 313, 333, 353 and 372K; 15 min (293K and 372K) and 1 hour (293K); and 2011, 2012, 2013, 2014 and 2015 respectively were tested. Measurement time using the gamma counter was one minute. A nuclear medical clinician decided the quality of the preparation in judging the usability of the retest agent. Two people conducted the test procedure twice, in order to compare reproducibility. The percentage of radiochemical purity (% RCP) was approximately 50% under insufficient heat treatment, which improved as the temperature and heating time increased. Moreover, the % RCP improved with time even under low temperatures. Furthermore, there was no deterioration with time after the expiration date. The objective of these tests was to determine soluble 99mTc impurities, including 99mTc-pertechnetate and the hydrolyzed-reduced 99mTc. Therefore, we assumed that insufficient heating and heating to operational errors in the labeling. It is concluded that quality control is a necessary procedure in nuclear medicine to ensure safe scanning. It is suggested that labeling is necessary to identify specifications.

Keywords: quality control, tc-99m labeled radio-pharmaceutical, chromatography strip, nuclear medicine

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Authors: Dao Phuong Nam, Tran Van Tuyen, Do Trong Tan, Bui Minh Dinh, Nguyen Van Huong

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In this paper, we investigate the adaptive optimal control law for continuous-time systems with input disturbances and unknown parameters. This paper extends previous works to obtain the robust control law of uncertain systems. Through theoretical analysis, an adaptive dynamic programming (ADP) based optimal control is proposed to stabilize the closed-loop system and ensure the convergence properties of proposed iterative algorithm. Moreover, the global asymptotic stability (GAS) for closed system is also analyzed. The theoretical analysis for continuous-time systems and simulation results demonstrate the performance of the proposed algorithm for an inverted pendulum system.

Keywords: approximate/adaptive dynamic programming, ADP, adaptive optimal control law, input state stability, ISS, inverted pendulum

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Authors: Chaiyakrit Raoupatham, Ram Hari Dhakal, Chalermchai Wanichlamlert

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Fresh concrete that is on bound to be rejected due to belated use either from delay construction process or unflavored traffic cause delay on concrete delivering can recover the slump and use once again by introduce second dose of superplasticizer(naphthalene based type F) into system. By adding superplasticizer as solution for recover unusable slump loss concrete may affects other concrete properties. Therefore, this paper was observed setting time and compressive strength of concrete after being re-dose with chemical admixture type F (superplasticizer, naphthalene based) for slump recovery. The concrete used in this study was fly ash concrete with fly ash replacement of 0%, 30% and 50% respectively. Concrete mix designed for test specimen was prepared with paste content (ratio of volume of cement to volume of void in the aggregate) of 1.2 and 1.3, water-to-binder ratio (w/b) range of 0.3 to 0.58, initial dose of superplasticizer (SP) range from 0.5 to 1.6%. The setting time of concrete were tested both before and after re-dosed with different amount of second dose and time of dosing. The research was concluded that addition of second dose of superplasticizer would increase both initial and final setting times accordingly to dosage of addition. As for fly ash concrete, the prolongation effect was higher as the replacement of fly ash is increase. The prolongation effect can reach up to maximum about 4 hours. In case of compressive strength, the re-dosed concrete has strength fluctuation within acceptable range of ±10%.

Keywords: compressive strength, fly ash concrete, second dose of superplasticizer, setting times

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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Authors: Nadhir Al-Ansari, Ammar A. Ali, Sven Knutsson

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Iraq is located in the Middle East. It covers an area of 433,970 square kilometres populated by about 32 million inhabitants. Iraq greatly relies in its water resources on the Tigris and Euphrates Rivers. Recently, Iraq is suffering from water shortage problems. This is due to external and internal factors. The former includes global warming and water resources policies of neighbouring countries while the latter includes mismanagement of its water resources. The supply and demand are predicted to be 43 and 66.8 Billion Cubic Meters (BCM) respectively in 2015, while in 2025 it will be 17.61 and 77 BCM respectively. In addition, future prediction suggests that Tigris and Euphrates Rivers will be completely dry in 2040. To overcome this problem, prudent water management policies are to be adopted. This includes Strategic Water Management Vision, development of irrigation techniques, reduction of water losses, use of non-conventional water resources and research and development planning.

Keywords: Iraq, Tigris River, Euphrates River, water scarcity, water resources management

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Authors: K. S. Sreejith, C. Shaji

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Though both Arabian Sea and its counterpart Bay of Bengal is forced primarily by the semi-annually reversing monsoons, the spatio-temporal variations of surface waters is very strong in the Arabian Sea as compared to the Bay of Bengal. This study focuses on the inter-annual variability of Sea Surface Temperature (SST) in the Arabian Sea by analysing ERSST dataset which covers 152 years of SST (January 1854 to December 2002) based on the ICOADS in situ observations. To capture the dominant SST oscillations and to understand the inter-annual SST variations at various local regions of the Arabian Sea, wavelet analysis was performed on this long time-series SST dataset. This tool is advantageous over other signal analysing tools like Fourier analysis, based on the fact that it unfolds a time-series data (signal) both in frequency and time domain. This technique makes it easier to determine dominant modes of variability and explain how those modes vary in time. The analysis revealed that pentadal SST oscillations predominate at most of the analysed local regions in the Arabian Sea. From the time information of wavelet analysis, it was interpreted that these cold and warm events of large amplitude occurred during the periods 1870-1890, 1890-1910, 1930-1950, 1980-1990 and 1990-2005. SST oscillations with peaks having period of ~ 2-4 years was found to be significant in the central and eastern regions of Arabian Sea. This indicates that the inter-annual SST variation in the Indian Ocean is affected by the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events.

Keywords: Arabian Sea, ICOADS, inter-annual variation, pentadal oscillation, SST, wavelet analysis

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Authors: Tamas Garamhegyi, Jozsef Kovacs, Rita Pongracz, Peter Tanos, Balazs Trasy, Norbert Magyar, Istvan G. Hatvani

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Like most environmental processes, shallow groundwater fluctuation under natural circumstances also behaves periodically. With the statistical tools at hand, it can easily be determined if a period exists in the data or not. Thus, the question may be raised: Does the estimated average period time characterize the whole time period, or not? This is especially important in the case of such complex phenomena as shallow groundwater fluctuation, driven by numerous factors. Because of the continuous changes in the oscillating components of shallow groundwater time series, the most appropriate method should be used to investigate its periodicity, this is wavelet spectrum analysis. The aims of the research were to investigate the periodic behavior of the shallow groundwater time series of an agriculturally important and drought sensitive region in Central-Eastern Europe and its relationship to the European pressure action centers. During the research ~216 shallow groundwater observation wells located in the eastern part of the Great Hungarian Plain with a temporal coverage of 50 years were scanned for periodicity. By taking the full-time interval as 100%, the presence of any period could be determined in percentages. With the complex hydrogeological/meteorological model developed in this study, non-periodic time intervals were found in the shallow groundwater levels. On the local scale, this phenomenon linked to drought conditions, and on a regional scale linked to the maxima of the regional air pressures in the Gulf of Genoa. The study documented an important link between shallow groundwater levels and climate variables/indices facilitating the necessary adaptation strategies on national and/or regional scales, which have to take into account the predictions of drought-related climatic conditions.

Keywords: climate change, drought, groundwater periodicity, wavelet spectrum and coherence analyses

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

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Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Debamitra Chakravorty, Pratap K. Parida

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Cold-adapted proteases enhance wash performance in low-temperature laundry resulting in a reduction in energy consumption and wear of textiles and are also used in the dehairing process in leather industries. Unfortunately, the possible drawbacks of using cold-adapted proteases are their instability at higher temperatures. Therefore, proteases with broad temperature stability are required. Unfortunately, wild-type cold-adapted proteases exhibit instability at higher temperatures and thus have low shelf lives. Therefore, attempts to engineer cold-adapted proteases by protein engineering were made previously by directed evolution and random mutagenesis. The lacuna is the time, capital, and labour involved to obtain these variants are very demanding and challenging. Therefore, rational engineering for cold stability without compromising an enzyme's optimum pH and temperature for activity is the current requirement. In this work, mutations were rationally designed with the aid of high throughput computational methodology of network analysis, evolutionary conservation scores, and molecular dynamics simulations for Savinase from Bacillus lentus with the intention of rendering the mutants cold stable without affecting their temperature and pH optimum for activity. Further, an attempt was made to incorporate a mutation in the most stable mutant rationally obtained by this method to introduce oxidative stability in the mutant. Such enzymes are desired in detergents with bleaching agents. In silico analysis by performing 300 ns molecular dynamics simulations at 5 different temperatures revealed that these three mutants were found to be better in cold stability compared to the wild type Savinase from Bacillus lentus. Conclusively, this work shows that cold adaptation without losing optimum temperature and pH stability and additionally stability from oxidative damage can be rationally designed by in silico enzyme engineering. The key findings of this work were first, the in silico data of H5 (cold stable savinase) used as a control in this work, corroborated with its reported wet lab temperature stability data. Secondly, three cold stable mutants of Savinase from Bacillus lentus were rationally identified. Lastly, a mutation which will stabilize savinase against oxidative damage was additionally identified.

Keywords: cold stability, molecular dynamics simulations, protein engineering, rational design

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Authors: Diwan Singh

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The ability of non-living Spirogyra sp. biomass for biosorption of copper(II) ions from aqueous solutions was explored. The effect of contact time, pH, initial copper ion concentration, biosorbent dosage and temperature were investigated in batch experiments. Both the Freundlich and Langmuir Isotherms were found applicable on the experimental data (R2>0.98). Qmax obtained from the Langmuir Isotherms was found to be 28.7 mg/g of biomass. The values of Gibbs free energy (ΔGº) and enthalpy change (ΔHº) suggest that the sorption is spontaneous and endothermic at 20ºC-40ºC.

Keywords: biosorption, Spirogyra sp., contact time, pH, dose

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Authors: Kailash C. Madan

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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: a three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state

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Authors: Hyun-Kyu Cho, Jun-Su Kim, Choon-Geun Huh, Geon Lee Young-Chul Park

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In this study, the relationship between flow properties and fluid projection distance look into connection for shape variations of foam monitor. A numerical analysis technique for fluid analysis of a foam monitor was developed for the prediction. Shape of foam monitor the flow path of fluid flow according to the shape, The fluid losses were calculated from flow analysis result.. The modified model used the length increase model of the flow path, and straight line of the model. Inlet pressure was 7 [bar] and external was atmosphere codition. am. The results showed that the length increase model of the flow path and straight line of the model was improved in the nozzle projection distance.

Keywords: injection performance, finite element method, foam monitor, Projection distance

Procedia PDF Downloads 328

Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

Abstract:

A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

Procedia PDF Downloads 140

Authors: G. Olamiti; TK. Takalani; D. Beswa, AIO Jideani

Abstract:

The study investigated the effects of malting and fermentation times on some chemical, functional properties and microstructural behaviour of Agrigreen, Babala pearl millet cultivars and sorghum flours using response surface methodology (RSM). Central Composite Rotatable Design (CCRD) was performed on two independent variables: malting and fermentation times (h), at intervals of 24, 48, and 72, respectively. The results of dependent parameters such as pH, titratable acidity (TTA), Water absorption capacity (WAC), Oil absorption capacity (OAC), bulk density (BD), dispersibility and microstructural behaviour of the flours studied showed a significant difference in p < 0.05 upon malting and fermentation time. Babala flour exhibited a higher pH value at 4.78 at 48 h malted and 81.9 fermentation times. Agrigreen flour showed a higher TTA value at 0.159% at 81.94 h malted and 48 h fermentation times. WAC content was also higher in malted and fermented Babala flour at 2.37 ml g-1 for 81.94 h malted and 48 h fermentation time. Sorghum flour exhibited the least OAC content at 1.67 ml g-1 at 14 h malted and 48 h fermentation times. Agrigreen flour recorded the least bulk density, at 0.53 g ml-1 for 72 h malted and 24 h fermentation time. Sorghum flour exhibited a higher content of dispersibility, at 56.34%, after 24 h malted and 72 h fermented time. The response surface plots showed that increased malting and fermentation time influenced the dependent parameters. The microstructure behaviour of malting and fermentation times of pearl millet varieties and sorghum flours showed isolated, oval, spherical, or polygonal to smooth surfaces. The optimal processing conditions, such as malting and fermentation time for Agrigreen, were 32.24 h and 63.32 h; 35.18 h and 34.58 h for Babala; and 36.75 h and 47.88 h for sorghum with high desirability of 1.00. The validation of the optimum processing malting and fermentation times (h) on the dependent improved the experimented values. Food processing companies can use the study's findings to improve food processing and quality.

Keywords: Pearl millet, malting, fermentation, microstructural behaviour

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Authors: Hsien Hao Teng

Abstract:

This study uses numerical simulation to analyze the aerodynamic characteristics of the 53-degree Lambda wing with a sweep angle and mainly discusses the numerical simulation results and physical characteristics of the wall y+. Use the commercial software Fluent to execute Mach number 0.15; when the angle of attack attitude is between 0 degrees and 27 degrees, the physical characteristics of the overall aerodynamic force are analyzed, especially when the fluid separation and vortex structure changes are discussed under the condition of high angle of attack, it will affect The instability of pitching moment. In the numerical calculation, the use of wall y+ and turbulence model will affect the prediction of vortex generation and the difference in structure. The analysis results are compared with experimental data to discuss the trend of the aerodynamic characteristics of the Lambda wing.

Keywords: lambda wing, wall function, turbulence model, computational fluid dynamics

Procedia PDF Downloads 233

Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

Abstract:

The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models. These results are part of the CMST COST Action No. CM1306 "Understanding Movement and Mechanism in Molecular Machines".

Keywords: Antibacterial, benzimidazoles, chemometric, QSAR.

Procedia PDF Downloads 302

Authors: Pranav Gulati, Isha Sharma

Abstract:

Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

Procedia PDF Downloads 258