Search results for: Big Data Movement

Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

Procedia PDF Downloads 250

Authors: Shoukat Ali, Abdul Qadir Jandga, Amjad Hussain

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Objective: The main purpose of this study is to compare the Percent Depth dose (PDD) and In-plane and cross-plane profiles of Varian Golden beam data to the measured data of 6 and 18 MV photons for the commissioning of Eclipse treatment planning system. Introduction: Commissioning of treatment planning system requires an extensive acquisition of beam data for the clinical use of linear accelerators. Accurate dose delivery require to enter the PDDs, Profiles and dose rate tables for open and wedges fields into treatment planning system, enabling to calculate the MUs and dose distribution. Varian offers a generic set of beam data as a reference data, however not recommend for clinical use. In this study, we compared the generic beam data with the measured beam data to evaluate the reliability of generic beam data to be used for the clinical purpose. Methods and Material: PDDs and Profiles of Open and Wedge fields for different field sizes and at different depths measured as per Varian’s algorithm commissioning guideline. The measurement performed with PTW 3D-scanning water phantom with semi-flex ion chamber and MEPHYSTO software. The online available Varian Golden Beam Data compared with the measured data to evaluate the accuracy of the golden beam data to be used for the commissioning of Eclipse treatment planning system. Results: The deviation between measured vs. golden beam data was in the range of 2% max. In PDDs, the deviation increases more in the deeper depths than the shallower depths. Similarly, profiles have the same trend of increasing deviation at large field sizes and increasing depths. Conclusion: Study shows that the percentage deviation between measured and golden beam data is within the acceptable tolerance and therefore can be used for the commissioning process; however, verification of small subset of acquired data with the golden beam data should be mandatory before clinical use.

Keywords: percent depth dose, flatness, symmetry, golden beam data

Procedia PDF Downloads 483

Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

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Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

Procedia PDF Downloads 159

Authors: Rahul Malhotra, Anurag Sharma

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

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Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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Authors: Piotr Dukalski, Bartlomiej Bedkowski, Tomasz Jarek, Tomasz Wolnik

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The article is concerned with the design of an electric in wheel hub motor installed in an electric car with two-wheel drive. It presents the construction of the motor on the 3D cross-section model. Work simulation of the motor (applicated to Fiat Panda car) and selected driving parameters such as driving on the road with a slope of 20%, driving at maximum speed, maximum acceleration of the car from 0 to 100 km/h are considered by the authors in the article. The demand for the drive power taking into account the resistance to movement was determined for selected driving conditions. The parameters of the motor operation and the power losses in its individual elements, calculated using the FEM 2D method, are presented for the selected car driving parameters. The calculated power losses are used in 3D models for thermal calculations using the CFD method. Detailed construction of thermal models with materials data, boundary conditions and losses calculated using the FEM 2D method are presented in the article. The article presents and describes calculated temperature distributions in individual motor components such as winding, permanent magnets, magnetic core, body, cooling system components. Generated losses in individual motor components and their impact on the limitation of its operating parameters are described by authors. Attention is paid to the losses generated in permanent magnets, which are a source of heat as the removal of which from inside the motor is difficult. Presented results of calculations show how individual motor power losses, generated in different load conditions while driving, affect its thermal state.

Keywords: electric car, electric drive, electric motor, thermal calculations, wheel hub motor

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Authors: Margaret S. Wright

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Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

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Authors: S. Kealy, J. Louys, S. O’Connor

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The island archipelago that stretches between the continents of Sunda (Southeast Asia) and Sahul (Australia - New Guinea) and comprising much of modern-day Indonesia as well as Timor-Leste, represents the biogeographic region of Wallacea. The islands of Wallaea are significant archaeologically as they have never been connected to the mainlands of either Sunda or Sahul, and thus the colonization by early modern humans of these islands and subsequently Australia and New Guinea, would have necessitated some form of water crossings. Accurate palaeogeographic reconstructions of the Wallacean Archipelago for this time are important not only for modeling likely routes of colonization but also for reconstructing likely landscapes and hence resources available to the first colonists. Here we present five digital reconstructions of coastal outlines of Wallacea and Sahul (Australia and New Guinea) for the periods 65, 60, 55, 50, and 45,000 years ago using the latest bathometric chart and a sea-level model that is adjusted to account for the average uplift rate known from Wallacea. This data was also used to reconstructed island areal extent as well as topography for each time period. These reconstructions allowed us to determine the distance from the coast and relative elevation of the earliest archaeological sites for each island where such records exist. This enabled us to approximate how much effort exploitation of coastal resources would have taken for early colonists, and how important such resources were. These reconstructions also allowed us to estimate visibility for each island in the archipelago, and to model how intervisible each island was during the period of likely human colonisation. We demonstrate how these models provide archaeologists with an important basis for visualising this ancient landscape and interpreting how it was originally viewed, traversed and exploited by its earliest modern human inhabitants.

Keywords: Wallacea, palaeogeographic reconstructions, islands, intervisibility

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Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

Procedia PDF Downloads 252

Authors: Nour Aladdin

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This paper explores the interconnectedness of belonging, space, and identity in Anglo Arab literature, particularly Saleem Haddad’s Guapa and Hasan Namir’sGod in Pink. This paper suggest that Rasa and Ramy, the queer Arab characters respectively, do not belong in either the Middle East or the West. Using Amin Maalouf’s analysis of the Arab identity, specifically his argument that an individual identifies strongly with the aspect of their identity that is under attack, this paper argues that all of Rasa and Ramy’s spaces are politically charged - a term that denotes that all values and beliefs instilled in Arabs and their spaces are heavily influenced by Arab politics, culture, and, often times religion. Therefore, the politically charged environments Rasa and Ramy inhabit will always be against one part of their identity, which is why they cannot identify as queer and Arab simultaneously. For Rasa, the unnamed Middle Eastern country, his home environment, as well as the so-called safe space nightclub, condemn his queerness, leading him to connect more to his sexual orientation. However, Rasa associates himself with his Arab roots when he migrates to America, a different form of politically charged space that minoritizes his ethnicity. Similarly, Ramy’s spaces are naturally religiopolitical after Islam heightened in Iraq during the Iraq War; as a result, Ramy’s home environment, Sheikh Ammar’s house, the mosque, and the nightclub are influenced by the religiopolitics and bombard his ability to identify as not only a queer Arab but a queer Arab Muslim. Ultimately, because Rasa and Ramy are constantly in movement, their identity attributes are also in movement. This paper is divided into three sections. The first section focuses on Guapa and the Arab Spring’s politics, mainly its influence on queer Arabs in and around the Middle East. Drawing from a number of queer and Arab gender theories, I analyze all of Rasa’s spaces as politically charged that prevent him from the means to be queer and Arab. The second section examines God in Pink in close connection to the 2003 invasion of Iraq. Ramy’s spaces are religiopolitically charged, that prevent him to embrace all of his identity attributes – nationality, ethnicity, sexual orientation, and religious affiliation – concomitantly. The last section considers the rapid use of technology and social media in the Middle East as a means to provide deviant heterotopic spaces for queer Arabs. With the rise of subtle and covert queer heterotopias, there is a slow and steady shift of queer tolerance in the Arab world.

Keywords: belonging, identity, spaces, queer, arabness, middle east, orientalism

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Authors: Woon Lam Ng.

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This paper explores the basic structures of Chinese calligraphy brushwork, its textures, its characteristic forms, and how its strength can be incorporated into 3d animation. It investigates how these structures could create visual simplification and suggest movement. The conceptual difference between realistic rendering and the Chinese calligraphic concept of simplification is discussed. With the help of the Python programmable environment in Maya, the concept of Chinese calligraphy in 3d space and its idea of visual simplification and abstraction were explored. The work demonstrates how the Chinese calligraphic brushwork could suggest the dynamics of motion in 3d space. Some limitations of the Maya emitting process are also discussed. Possible further explorations through additional mathematical adjustments to the selected Maya shader are also suggested to enhance the presentation.

Keywords: calligraphy, brushwork, dynamics, movements

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

Procedia PDF Downloads 293

Authors: Yasmeen Jamal Alabdallat, Almutazballlah Bassam Qablan, Obada Ahmad Al Jayyousi, Ihdaa Mahmoud Bani Khalaf, Eman E. Alshial

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Background: Bipolar disorder, formerly known as manic depression, is a mental health status that leads to extreme mood swings that include emotional lows (depression) and highs (mania or hypomania). This systematic review and meta-analysis aimed to assess the safety and efficacy of lithium versus valproate among bipolar patients. Methods: A computer literature search of PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials was conducted from inception until June 2022. Studies comparing lithium versus valproate among bipolar patients were selected for the analysis, and all relevant outcomes were pooled in the meta-analysis using Review Manager Software. Results: 11 Randomized Clinical Trials were included in this meta-analysis with a total of 4159 patients. Our meta showed that lithium was superior to valproate in terms of Young Mania Rating Scale (YMRS) (MD = 0.00 with 95% CI, (-0.55 – 0.55; I2 = 0%), P = 1.00). The results of the Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored the valproate treated group (MD = 1.41 with 95% CI, (-0.15 – 2.67; I2 = 0%), P = 0.03). Concerning the results of the Montgomery-Asberg Depression Rating Scale (MADRS), the results showed that the lithium was superior to valproate (MD = 0.03 with 95% CI, (-0.80 to 0.87; I2 = 40%), P = 0.94). In terms of the sexual side effect, we found that the valproate was superior to lithium (RR 1.19 with 95% CI, (0.74 to 1.91; I2 = 0%), P = 0.47). The lithium-treated group was superior in comparison to valproate treated group in terms of Abnormal Involuntary Movement Scale (AIMS) (MD = -0.03 with 95% CI (-0.38 to 0.32; I2 = 0%), P = 0.87). The lithium was more favorable in terms of Simpson-Agnes scale (MD = -0.40 with 95% CI, (-0.86 to 0.06; I2 = 0%), P = 0.09). The results of the Barnes akathisia scale showed that the overall effect of the valproate was more favorable in comparison to lithium (MD = 0.05 with 95% CI, (-0.12 to 0.22; I2 = 0%), P = 0.57). Conclusion: Our study revealed that on the scales of efficacy Lithium treated group surpassed Valproate treated group in terms of Young Mania Rating Scale (YMRS), Abnormal Involuntary Movement Scale (AIMS) and Simpson-Agnes scale, but valproate surpassed it in Barnes Akathisia scale. Furthermore, on the scales of depression Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored Valproate treated group, but Lithium surpassed valproate in terms of Montgomery-Asberg Depression Rating Scale (MADRS). Valproate surpassed Lithium in terms of sexual side effects.

Keywords: bipolar, mania, bipolar-depression, sexual dysfunction, sexual side effects, treatment

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Authors: Walid Fantazi

Abstract:

The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

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Authors: Amin Akbari, Dongcai Wang, Huiru Li, Xiaoping Du, Jie Chen

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The effect of vibrational force (VF) on accelerating orthodontic tooth movement depends on the level of delivered stimulation to the tooth in terms of peak load (PL), which requires contacts between the tooth and the VF device. A personalized device ensures the contacts, but the resulting PL distribution on the teeth is unknown. Furthermore, it is unclear whether the PL on particular teeth can be adjusted to the prescribed values. The objective of this study was to investigate the efficacy of apersonalized VF device in controlling the level of stimulation on two teeth, the mandibular canines and 2nd molars. A 3-D finite element (FE) model of human dentition, including teeth, PDL, and alveolar bone, was created from the cone beam computed tomography images of an anonymous subject. The VF was applied to the teeth through a VFdevice consisting of a mouthpiece with engraved tooth profile of the subject and a VF source that applied 0.3 N force with the frequency of 30 Hz. The dentition and mouthpiece were meshed using 10-node tetrahedral elements. Interface elements were created at the interfaces between the teeth and the mouthpiece. The upper and lower teeth bite on the mouthpiece to receive the vibration. The depth of engraved individual tooth profile could be adjusted, which was accomplished by adding a layer of material as an interference or removing a layer of material as a clearance to change the PL on the tooth. The interference increases the PL while the clearance decreases it. Fivemouthpiece design cases were simulated, which included a mouthpiece without interference/clearance; the mouthpieces with bilateral interferences on both mandibular canines and 2nd molars with magnitudes of 0.1, 0.15, and 0.2-mm, respectively; and mouthpiece with bilateral 0.3-mm clearances on the four teeth. Then, the force distributions on the entire dentition were compared corresponding to these adjustments. The PL distribution on the teeth is uneven when there is no interference or clearance. Among all teeth, the anterior segment receives the highest level of PL. Adding 0.1, 0.15, and 0.2-mm interferences to the canines and 2nd molars bilaterally leads to increase of the PL on the canines by 10, 62, and 73 percent and on the 2nd molar by 14, 55, and 87 percent, respectively. Adding clearances to the canines and 2nd molars by removing the contactsbetween these teeth and the mouthpiece results in zero PL on them. Moreover, introducing interference to mandibular canines and 2nd molarsredistributes the PL on the entireteeth. The share of the PL on the anterior teeth are reduced. The use of the personalized mouthpiece ensures contactsof the teeth to the mouthpiece so that all teeth can be stimulated. However, the PL distribution is uneven. Adding interference between a tooth and the mouthpiece increases the PL while introducing clearance decreases the PL. As a result, the PL is redistributed. This study confirms that the level of VF stimulation on the individual tooth can be adjusted to a prescribed value.

Keywords: finite element method, orthodontic treatment, stress analysis, tooth movement, vibrational force

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Authors: Urbi Pal, Piyas Palit, Jitendra Mathur, Abhay Chaturvedi, Sandip Bhattacharya

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The hot rolled slab lifting crane cable reel drum (CRD) failed due to failure of cable reel flat spring which are inside the cassette of CRD. CRD is used for the movement of tong cable. Stereoscopic observation revealed beach marks and Scanning Electron Microscopy showed striations confirming fatigue mode of failure. Chemical composition should be spring steel (Cr-Mo-V) as per IS 3431:1982 instead of C-Mn steel. To find out the reason of fatigue failure, the theoretical fatigue life of flat spiral spring has been calculated. The calculation of number of fatigue cycles included bending moment, maximum stress on the spring, ultimate tensile strength and alternative stress. The bending moment determination has been taken account with various parameters like Young’s Modulus, width, thickness, outer diameter, arbor diameter, pay out the length and angular deflection in rotations. With all the required data, the calculated fatigue life turned to be 10000 cycles, but the spring served 15000 cycles which clearly indicated beyond fatigue life usage. Different UTS values have been plotted with respect to the number of fatigue cycles and clearly showed that the increase in UTS by 40% increases fatigue life by 50%. The significance of higher UTS lied here, and higher UTS depends on modified chemistry with proper tempered martensite microstructure. This kind of failure can be easily avoided by changing the crane spring maintenance schedule from 2 years to 1.5 years considering 600 cycles per month. The plant has changed changing the schedule of cable reel spring and procured new flat reel spring made of 50CrV2 steel.

Keywords: cable reel spring, fatigue life, stress, spring steel

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Arash Kosari, Ali Araghi

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A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: absorption, data throughput, depolarization, optical fiber

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Authors: Davinder Singh, Jaimal Singh Khamba, Tarun Nanda

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Growth of the Indian economy has accelerated to 8% and efforts are on to further propel it to 10%. Undoubtedly, all the segments of the economy, viz. agriculture, industry and services have to improve their contribution to the economy. Growth of Micro-small and medium enterprises (MSMEs) is a sine qua non for the growth of industry, exports and other segments of the economy. Furthermore, promotion of entrepreneurship is also vital for sustenance and upward movement of the current growth trajectory of the economy. The MSME sector acts as a catalyst in upholding and encouraging the creation of the innovative spirit and entrepreneurship in the economy, thereby helping in laying the foundation for rapid industrial development. In this competitive world, they need to be able to confront the increasing competition from developed and emerging economies and to plug into the new market opportunities.

Keywords: characteristics, management, MSMEs, technology infrastructure

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Michelle J. Miller

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In recent year, there has been a rise of two emerging issues that impact the global employment and business market that the legal community must review closer: offshore outsourcing and data privacy. These two issues intersect because employment opportunities are shifting due to offshore outsourcing and some States, like the United States, anti-outsourcing legislation has been passed or presented to retain jobs within the country. In addition, the legal requirements to retain the privacy of data as a global employer extends to employees and third party service provides, including services outsourced to offshore locations. For this reason, this paper will review the intersection of these two issues with a specific focus on data privacy.

Keywords: outsourcing, data privacy, international compliance, multinational corporations

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Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

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Authors: Kazım Kaba, Erdem Erdi, M. Akif Erdoğan, H. Mustafa Kandırmaz

Abstract:

Rainfall is crucial data source for very different discipline such as agriculture, hydrology and climate. Therefore rain rate should be known well both spatial and temporal for any area. Rainfall is measured by using rain-gauge at meteorological ground stations traditionally for many years. At the present time, rainfall products are acquired from radar and satellite images with a temporal and spatial continuity. In this study, we investigated the accuracy of these rainfall data according to rain-gauge data. For this purpose, we used Adana-Hatay radar hourly total precipitation product (RN1) and Meteosat convective rainfall rate (CRR) product over Seyhan plain. We calculated daily rainfall values from RN1 and CRR hourly precipitation products. We used the data of rainy days of four stations located within range of the radar from October 2013 to November 2015. In the study, we examined two rainfall data over Seyhan plain and the correlation between the rain-gauge data and two raster rainfall data was observed lowly.

Keywords: meteosat, radar, rainfall, rain-gauge, Turkey

Procedia PDF Downloads 321

Authors: Sihem Oujdi, Hafida Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

Procedia PDF Downloads 609

Authors: G. Sirbiladze, B. Ghvaberidze, B. Matsaberidze

Abstract:

A fuzzy vehicle routing problem is considered in the possibilistic environment. A new criterion, maximization of expectation of reliability for movement on closed routes is constructed. The objective of the research is to implement a two-stage scheme for solution of this problem. Based on the algorithm of preferences on the first stage, the sample of so-called “promising” routes will be selected. On the second stage, for the selected promising routes new bi-criteria problem will be solved - minimization of total traveled distance and maximization of reliability of routes. The problem will be stated as a fuzzy-partitioning problem. Two possible solutions of this scheme are considered.

Keywords: vehicle routing problem, fuzzy partitioning problem, multiple-criteria optimization, possibility theory

Procedia PDF Downloads 543

Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 128