Search results for: data center

Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda

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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.

Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming

Procedia PDF Downloads 81

Authors: Mehmet Savsar

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Complex Life Support Systems (LSS) are used in all large commercial and public aquariums in order to keep the fish alive. Reliabilities of individual equipment, as well as the complete system, are extremely important and critical since the life and safety of important fish depend on these life support systems. Failure of some critical device or equipment, which do not have redundancy, results in negative consequences and affects life support as a whole. In this paper, we have considered a life support system in a large public aquarium in Kuwait Scientific Center and presented a procedure and analysis to show how the reliability of such systems can be estimated by using appropriate tools and collected data. We have also proposed possible improvements for systems reliability. In particular, addition of parallel components and spare parts are considered and the numbers of spare parts needed for each component to achieve a required reliability during specified lead time are calculated. The results show that significant improvements in system reliability can be achieved by operating some LSS components in parallel and having certain numbers of spares available in the spare parts inventories. The procedures and the results presented in this paper are expected to be useful for aquarium engineers and maintenance managers dealing with LSS.

Keywords: life support systems, aquariums, reliability, failures, availability, spare parts

Procedia PDF Downloads 278

Authors: A. Keshavarz

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A physical model for guiding the wave in photorefractive media is studied. Propagation of cos-Gaussian beam as the special cases of sinusoidal-Gaussian beams in photorefractive crystal is simulated numerically by the Crank-Nicolson method in one dimension. Results show that the beam profile deforms as the energy transfers from the center to the tails under propagation. This simulation approach is of significant interest for application in optical telecommunication. The results are presented graphically and discussed.

Keywords: beam propagation, cos-Gaussian beam, numerical simulation, photorefractive crystal

Procedia PDF Downloads 497

Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

Procedia PDF Downloads 367

Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

Procedia PDF Downloads 95

Authors: Adelson G. Guillarte, M. D., Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Patients with malignant middle cerebral infarction (MCA) (with massive brain swelling and herniation) were reported to have a mortality rate of 80% even with the appropriate conservative medical therapy. European Trials (DECIMAL, DESTINY I, and II, HAMLET) showed significant improvement in mortality and functional outcome with hemicraniectomy. No known published local studies in the region, thus a local study is vital. This is a single center, retrospective, descriptive, cross-sectional, chart review study which includes ≥18 year-old patients with malignant MCA infarction, who underwent hemicraniectomy, and those who were given conservative medical therapy alone, from January 2008 to December 2012 at Perpetual Succour Hospital. Excluded were patients whose charts are with insufficient data, prior MCA stroke, with concomitant intracerebral hemorrhage and with other serious medical conditions or terminal illnesses. Minimum of 32 populations were needed. Data were presented in mean, standard deviation, frequency and percentage distribution. Man n Whitney U test and Chi Square test were used. P-values lesser than 0.05 alpha were considered statistically significant. A total of 672 stroke patients were admitted. 34 patients pass the inclusion criteria. 9 underwent hemicraniectomy and 25 were treated by conservative medical therapy alone. Although not statistically significant (64% vs 33%, p=0.112) there were more patients noted improved in the conservative treatment group. Meanwhile, the Hemicraniectomy group have increased percentage of mortality (67%) (p=0.112). There was a decreasing trend in the average NIHSS score in both groups from admission to post-op 7 days (p=0.198, p=0.78). A bigger multicenter prospective study is recommended to control inherent biases and limitations of a retrospective and smaller study.

Keywords: cerebral infarct, hemicraniectomy, ischemic stroke, malignant middle cerebral artery (MCA) infarct

Procedia PDF Downloads 313

Authors: Ana M. G. Sperandio, Adriana A. C. Rosa, Jussara C. Guarnieri

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This study consists of a research of the Post Occupancy Assessment (POA) of Medicinal Gardens' project of Urban Social Center’s square, in the city of 'Santa Barbara d'Oeste', located in the interior of Sao Paulo, Brazil. In view of the fact that community gardens, as well as medicinal gardens, are based on innumerable functions. The addition to the pedagogical function rescues people from their origins through (re)contact with the land, as a vehicle for social integration. Bearing in mind the project has the potential to fight hunger among the low-income population, to treat some diseases, also works as a strategy of environmental recovery especially of idle land. Such as very often only accumulate weeds and garbage, and therefore, must be considered in the Municipal Master Plan for the activity to be regulated. Objective: Identify on implantation the medicinal plants' value and principles for the promotion of a healthy city. Methodology: Application of the walkthrough, where it is possible to affirm that this instrument has three routes: one officer applied within the urban social center and two complementary ones, one being about 3 miles and the other being almost 5,5 miles. Results: Through a dialogical course, one can observe the benefits that the community medicinal gardens bring to the local population. In addition, it is consistent with the proposal for the community to be enabled to access collective care with home orientations that rescue the local and regional culture making the physical environment. This project aims at promoting more pleasant and inclusive through the actions of the caregiver, local leadership and the co-participation of local government. Although with the aim of increasing the supply value and improving the living conditions of social groups and interrelationship. Conclusion: This type of urban intervention, which articulates social participation, rescue of medicinal cultures and local knowledge, intersectoriality, social inclusion, among other premises connected with health promotion, and the city presents a potential for reverberation of practices in social networks with the objective of meeting the healthy city strategies.

Keywords: healthy city, healthy urban planning, medicinal gardens, social participation

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Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: Inkyu Kim, SangMan Moon

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This IEEE 802.11b protocol provides up to 11Mbps data rate, whereas aerospace industry wants to seek higher data rate COTS data link system in the UAV. The Total Maximum Throughput (TMT) and delay time are studied on many researchers in the past years This paper provides theoretical data throughput performance of UAV formation flight data link using the existing 802.11b performance theory. We operate the UAV formation flight with more than 30 quad copters with 802.11b protocol. We may be predicting that UAV formation flight numbers have to bound data link protocol performance limitations.

Keywords: UAV datalink, UAV formation flight datalink, UAV WLAN datalink application, UAV IEEE 802.11b datalink application

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Authors: Jemima C. A. Sumboh

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Given the urgency and consensus for countries to move towards Universal Health Coverage (UHC), health financing systems need to be accurately and consistently monitored to provide valuable data to inform policy and practice. Most of the indicators for monitoring UHC, particularly catastrophe and impoverishment, are established based on the impact of out-of-pocket health payments (OOPHP) on households’ living standards, collected through varied household surveys. These surveys, however, vary substantially in survey methods such as the length of the recall period or the number of items included in the survey questionnaire or the farming of questions, potentially influencing the level of OOPHP. Using different survey instruments can provide inaccurate, inconsistent, erroneous and misleading estimates of UHC, subsequently influencing wrong policy decisions. Using data from a household budget survey conducted by the Navrongo Health Research Center in Ghana from May 2017 to December 2018, this study intends to explore the potential implications of using surveys with varied levels of disaggregation of OOPHP data on estimates of financial risk protection. The household budget survey, structured around food and non-food expenditure, compared three OOPHP measuring instruments: Version I (existing questions used to measure OOPHP in household budget surveys), Version II (new questions developed through benchmarking the existing Classification of the Individual Consumption by Purpose (COICOP) OOPHP questions in household surveys) and Version III (existing questions used to measure OOPHP in health surveys integrated into household budget surveys- for this, the demographic and health surveillance (DHS) health survey was used). Version I, II and III contained 11, 44, and 56 health items, respectively. However, the choice of recall periods was held constant across versions. The sample size for Version I, II and III were 930, 1032 and 1068 households, respectively. Financial risk protection will be measured based on the catastrophic and impoverishment methodologies using STATA 15 and Adept Software for each version. It is expected that findings from this study will present valuable contributions to the repository of knowledge on standardizing survey instruments to obtain estimates of financial risk protection that are valid and consistent.

Keywords: Ghana, household budget surveys, measuring financial risk protection, out-of-pocket health payments, survey instruments, universal health coverage

Procedia PDF Downloads 133

Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 544

Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

Procedia PDF Downloads 806

Authors: Divya Pathak, James Sloane

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Surgical treatment of midface fractures should ideally occur within two weeks of injury, after which bony healing and consolidation make the repair more difficult for the operating surgeon. The oral and maxillofacial unit at the Royal Surrey Hospital is the tertiary referral center for maxillofacial trauma from five regional hospitals. This is a complete audit cycle of midface trauma referrals managed over a one year period. The standard set was that clinical assessment of the midface fracture would take place in a consultant led outpatient clinic within 7 days, and when indicated, surgical fixation would occur within 10 days of referral. Retrospective data was collected over one year (01/11/2018 - 31/12/2019). Three key changes were implemented: an IT referral mailbox, standardization of an on-call trauma table, and creation of a trauma theatre list. Re-audit was carried out over six months completing the cycle. 283 midface fracture referrals were received, of which 22 patients needed surgical fixation. The average time from referral to outpatient follow-up improved from 14.5 days to 8.3 days, and time from referral to surgery improved from 21.5 days to 11.6 days. Changes implemented in this audit significantly improved patient prioritization to appropriate outpatient clinics and shortened time to surgical intervention.

Keywords: maxillofacial trauma, midface trauma, oral and maxillofacial surgery, surgery fixation

Procedia PDF Downloads 139

Authors: Fahad Al Beyahi, Justin Thomas, Md Mamunur Rashid

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Various definitions of digital well-being have emerged in recent years, most of which center on the impacts -beneficial and detrimental- of digital technology on health and well-being (psychological, social, and financial). Other definitions go further, emphasizing the attainment of balance, viewing digital well-being as wholly subjective, the individual’s perception of optimal balance between the benefits and ills associated with online connectivity. Based on this broad conceptualization of digital well-being, we undertook a global survey measuring various dimensions of this emerging construct. The survey was administered across 35 nations and 7 world regions, with 1000 participants within each territory (N= 35000). Along with attitudinal, behavioral, and sociodemographic variables, the survey included measures of depression, anxiety, problematic social media use, gaming disorder, and other relevant metrics. Coupled with nation-level policy audits, these data were used to create a multinational (global) digital well-being index. Nations are ranked based on various dimensions of digital well-being, and predictive models are used to identify resilience and risk factors for problem technology use. In this paper, we will discuss key findings from the survey and the index. This work can inform public policy and shape our responses to the emerging implications of lives increasingly lived online and interconnected with digital technology.

Keywords: technology, health, behavioral addiction, digital wellbeing

Procedia PDF Downloads 75

Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

Procedia PDF Downloads 262

Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

Procedia PDF Downloads 534

Authors: Gheorghe Braniste

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Gender gap has always been in dispute when comparing records and has been a major factor influencing best performances in various sports. Consequently, our study registers the evolution of the difference between men's and women’s best performances within either cyclic or acyclic sports, considering the fact that the training sessions of high performance athletes prove both similarities and differences in long-term adaptation of their body to stress and effort in breaking limits and records. Firstly, for a correct interpretation of the data and tables included in this paper, we must point out that the intense muscular activity has a considerable impact on the structural organization of the organs and systems of the performer's body through the mechanism of motor-visceral reflexes, forming a high working capacity suitable for intense muscular activity. The opportunity to obtaine high sports results during the official competitions is due, on the one hand, to the genetic characteristics of the athlete's body, and on the other hand, to the fact that playing professional sports leaves its mark on the vital morphological and functional parameters. The aim of our research is to study the landmarking differences between male and female athletes and their physical development, together with their growing capacity to stand up to the functional training during the competitive period of their annual training cycle. In order to evaluate the physical development of the athletes, the data of the anthropometric screenings obtained at the Olympic Training Center of the selected teams of the Republic of Moldova were interpreted and rated. During the study of physical development in terms of body height and weight, vital capacity, thoracic excursion, maximum force (Fmax), dynamometry of the hand and back, a further evaluation of the physical development indices that allow an evaluation of complex physical development were registered. The interdependence of the results obtained in performance sports with the morphological and functional particularities of the athletes' body is firmly determined and cannot be disputed. Nevertheless, registered data proved that with the increase of the training capacity, the morphological and functional abilities of the female body increase and, in some respects, approach and even slightly surpass the men in certain sports.

Keywords: physical development, indices, parameters, active body weight, morphological maturity, physical performance

Procedia PDF Downloads 115

Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Serdar Delice, Mehmet Isik, Nizami Hasanli, Kadir Goksen

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Researchers have donated great interest to ternary and quaternary semiconductor compounds especially with the improvement of the optoelectronic technology. The quaternary compound Tl2Ga2Se3S which was grown by Bridgman method carries the properties of ternary thallium chalcogenides group of semiconductors with layered structure. This compound can be formed from TlGaSe2 crystals replacing the one quarter of selenium atom by sulfur atom. Although Tl2Ga2Se3S crystals are not intentionally doped, some unintended defect types such as point defects, dislocations and stacking faults can occur during growth processes of crystals. These defects can cause undesirable problems in semiconductor materials especially produced for optoelectronic technology. Defects of various types in the semiconductor devices like LEDs and field effect transistor may act as a non-radiative or scattering center in electron transport. Also, quick recombination of holes with electrons without any energy transfer between charge carriers can occur due to the existence of defects. Therefore, the characterization of defects may help the researchers working in this field to produce high quality devices. Thermoluminescence (TL) is an effective experimental method to determine the kinetic parameters of trap centers due to defects in crystals. In this method, the sample is illuminated at low temperature by a light whose energy is bigger than the band gap of studied sample. Thus, charge carriers in the valence band are excited to delocalized band. Then, the charge carriers excited into conduction band are trapped. The trapped charge carriers are released by heating the sample gradually and these carriers then recombine with the opposite carriers at the recombination center. By this way, some luminescence is emitted from the samples. The emitted luminescence is converted to pulses by using an experimental setup controlled by computer program and TL spectrum is obtained. Defect characterization of Tl2Ga2Se3S single crystals has been performed by TL measurements at low temperatures between 10 and 300 K with various heating rate ranging from 0.6 to 1.0 K/s. The TL signal due to the luminescence from trap centers revealed one glow peak having maximum temperature of 36 K. Curve fitting and various heating rate methods were used for the analysis of the glow curve. The activation energy of 13 meV was found by the application of curve fitting method. This practical method established also that the trap center exhibits the characteristics of mixed (general) kinetic order. In addition, various heating rate analysis gave a compatible result (13 meV) with curve fitting as the temperature lag effect was taken into consideration. Since the studied crystals were not intentionally doped, these centers are thought to originate from stacking faults, which are quite possible in Tl2Ga2Se3S due to the weakness of the van der Waals forces between the layers. Distribution of traps was also investigated using an experimental method. A quasi-continuous distribution was attributed to the determined trap centers.

Keywords: chalcogenides, defects, thermoluminescence, trap centers

Procedia PDF Downloads 276

Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: Dragan Zivotic, Mirjana Ilic, Aleksandra Perovic, Predrag Gavrilovic

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As with the provision of other services, the service quality perception is one of the key factors that the modern manager must pay attention to. Countries in which the state regulation is in transition also have specific features in providing fitness services. Identification of the dimensions in which the most significant different service quality perception between different types of fitness centers, enables managers to profile the offer according to the wishes and expectations of users. The aim of the paper was the comparison of the quality of services perception in the field of fitness in Serbia between three categories of fitness centers: the privately owned centers, the publicly owned centers, and the Public-private partnership centers. For this research 350 respondents of both genders (174 men and 176 women) were interviewed, aged between 18 and 68 years, being beneficiaries of fitness services for at least 1 year. Administered questionnaire with 100 items provided information about the 15 basic areas in which they expressed the service quality perception in the gym. The core sample was composed of 212 service users in private fitness centers, 69 service users in public fitness centers and 69 service users in the public-private partnership. Sub-samples were equal in representation of women and men, as well as by age and length of use of fitness services. The obtained results were subject of univariate analysis with the Kruskal-Wallis non-parametric analysis of variance. Significant differences between the analyzed sub-samples were not found solely in the areas of rapid response and quality outcomes. In the multivariate model, the results were processed by backward stepwise discriminant analysis that extracted 3 areas that maximize the differences between sub-samples: material and technical basis, secondary facilities and coaches. By applying the classification function 93.87% of private centers services users, 62.32% of public centers services users and 85.51% of the public-private partnership centers users of services were correctly classified (total 86.00%). These results allow optimizing the allocation of the necessary resources in profiling offers of a fitness center in order to optimally adjust it to the user’s needs and expectations.

Keywords: fitness, quality perception, management, public ownership, private ownership, public-private partnership, discriminative analysis

Procedia PDF Downloads 291

Authors: Narae Yang, Hyun Kyung Sung, Seon Mi Shin, Hee Jung, Yong Ji Kim, Tae-Yong Park, Ho Yeon Go

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The aim of this study was to build base-line data for the Korean Medicine Doctors` Visiting School Program (KMDVSP) by analyzing a student health survey filled out by the students. Korean medicine doctors assigned to 20 middle and high schools in Seong-nam visited these schools eight times in five months. During each visit, the assigned doctors performed health consultations and Korean medicine treatment, and taught health education classes. 12115 students answered self-reported questionnaires about their own physical condition at the beginning of the program. In a question about pain, 7080(58%) reported having a headache, while 4048(33%) said they had a backache, nuchal pain/shoulder pain was reported by 5993(49%), dyspepsia was present in 2736(23%), rhinitis/sinusitis was reported by 4176(34%), coughing/dyspnea by 7102(59%), itching/skin rash by 2840(23%), and constipation was reported by 1091(9%), while 2264(18%) said they had diarrhea. Increased urinary frequency/feeling of residual urine was reported by 569 students (5%), and 3324(27%) said they had insomnia/fitful sleep/morning fatigue. When asked about menstruation, 4450(83%) of the female students reported irregular menstruation or said they experienced menstrual pain. Understanding the health condition of adolescent students is the starting point to determining national health policy to prevent various diseases in the future. We have developed the pilot project of KMDVSP and collected research about students’ health. Based on this data, further studies should be performed in order to develop a cooperative program between schools and the Korean medical center.

Keywords: korean medicine doctors` visiting school program(kmdvsp), student`s health condition, questionnaires, cohort study

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Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

Abstract:

The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

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Authors: Shawna Staud, Mary Kaye Scaramucci

Abstract:

Objective: Rubber cup polishing has been a traditional method of preventative therapy in dental hygiene treatment. Newer methods such as air polishing have changed the way dental hygiene care is provided, yet this technique has not been embraced by students in the program nor by practitioners in the workforce. Students entering the workforce tend to follow office protocol and are limited in confidence to introduce technologies learned in the curriculum. This project was designed to help students gain confidence in newer skills and encourage private practice settings to adopt newer technologies for patient care. Our program recently introduced air polishing earlier in the program before the rubber cup technique to determine if students would embrace the technology to become leading-edge professionals when they enter the marketplace. Methods: The class of 2022 was taught the traditional method of polishing in the first-year curriculum and air polishing in the second-year curriculum. The class of 2023 will be taught the air polishing method in the first-year curriculum and the traditional method of polishing in the second-year curriculum. Pre- and post-graduation survey data will be collected from both cohorts. Descriptive statistics and pre and post-paired t-tests with alpha set at .05 to compare pre and post-survey results will be used to assess data. Results: This study is currently in progress, with a completion date of October 2023. The class of 2022 completed the pre-graduation survey in the spring of 2022. The post-gradation survey will be sent out in October 2022. The class of 2023 cohort will be surveyed in the spring of 2023 and October 2023. Conclusion: Our hypothesis is students who are taught air polishing first will be more inclined to adopt that skill in private practice, thereby embracing newer technology and improving oral health care.

Keywords: luggage handling system at world’s largest pilgrimage center

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Authors: M. Sumana, K. S. Hareesha

Abstract:

Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data

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Authors: Vahid Bairami Rad

Abstract:

The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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Authors: Keunhong Chae, Seokho Yoon

Abstract:

Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

Procedia PDF Downloads 277