Search results for: computer generated music

Authors: Bâlc Denisa-Maria

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This paper aims to present some ways of preserving a language heritage in the global era. Teaching a second language to foreign students does not imply only teaching the grammar and the vocabulary in order to reach the 4 skills, but it means constant work on developing strategies to make the students aware of the heritage that the language they learn has. Teachers and professors need to be aware of the fact that language is in constant change, they need to adjust their techniques to the digital era, but they also have to be aware of the changes, the good and the bad parts of globalizations. How is it possible to preserve the patrimony of a certain language in a globalized era? What transformations does a language face in time? What does it mean to preserve the heritage of a language through L2 teaching? What makes a language special? What impact does it have on the foreign students? How can we, as teachers, preserve the heritage of our language? Would it be everything about books, films, music, cultural events or what else? How is it possible to include digital programs in your teaching and preserving the patrimony of a language at the same time? How does computational linguistics help us in teaching a certain language? All these questions will be tackled during the essay, with special accent on the definition of a language heritage, the new perspectives for teachers/ professors, everything in a multimodal and complex way of presenting the context. The objectives of this research are: - to present some ways of preserving the heritage of a certain language against globalization - to illustrate what preservation means for L2 teaching - to encourage teachers to be aware of their language patrimony The main contributions of my research are on moving the discussion of preserving a certain language patrimony in the context of L2 teaching.

Keywords: preservation, globalization, language heritage, L2 teaching

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Authors: Minhyuk Heo, Jihwan Yun, Seonghun Park

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It has been reported that intervertebral fusion surgery, which removes most of the ligaments and muscles of the spine, increases the degenerative disease in adjacent spinal segments. Therefore, it is required to develop a lumbar interspinous process fixation device that minimizes the risks and side effects from the surgery. The objective of the current study is to design an interspinous process fixation device with simple structures in order to minimize soft tissue removal and operation time during intervertebral fusion surgery. For the design concepts of a lumbar fixation device, the principle of the ratchet was first applied on the joining parts of the device in order to shorten the operation time. The coil spring structure was selected for connecting parts between the spinous processes so that a normal range of motion in spinal segments is preserved and degenerative spinal diseases are not developed in the adjacent spinal segments. The stiffness of the spring was determined not to interrupt the motion of a lumbar spine. The designed value of the spring stiffness allows the upper part of the spring to move ~10° which is higher than the range of flexion and extension for normal lumbar spine (6°-8°), when a moment of 10Nm is applied on the upper face of L1. A finite element (FE) model composed of L1 to L5 lumbar spines was generated to verify the mechanical integrity and the dynamic stability of the designed lumbar fixation device and to further optimize the lumbar fixation device. The FE model generated above produced the same pressure value on intervertebral disc and dynamic behavior as the normal intact model reported in the literature. The consistent results from this comparison validates the accuracy in the modeling of the current FE model. Currently, we are trying to generate an abnormal model with defects in one or more components of the normal FE model above. Then, the mechanical integrity and the dynamic stability of the designed lumbar fixation device will be analyzed after being installed in the abnormal model and then the lumbar fixation device will be further optimized.

Keywords: lumbar interspinous process fixation device, finite element method, lumbar spine, kinematics

Procedia PDF Downloads 228

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithm

Keywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm

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Authors: Frank Hespeler, Giuseppe Loiacono

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We propose measures for systemic risk generated through intra-sectorial interdependencies in the hedge fund sector. These measures are based on variations in the average cross-effects of funds showing significant interdependency between their individual returns and the moments of the sector’s return distribution. The proposed measures display a high ability to identify periods of financial distress, are robust to modifications in the underlying econometric model and are consistent with intuitive interpretation of the results.

Keywords: hedge funds, systemic risk, vector autoregressive model, risk monitoring

Procedia PDF Downloads 325

Authors: Saif K. Al-Qaisi, Jad R. Mansour, Aseel W. Sakka, Yousef Al-Abdallat

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Handwheels are common to numerous industries, such as power generation plants, oil refineries, and chemical processing plants. The forces required to manually turn handwheels have been shown to exceed operators’ physical strengths, posing risks for injuries. Therefore, the objectives of this research were twofold: (1) to determine humans’ physical strengths on handwheels of different sizes and angles and (2) to subsequently propose recommended torque limits (RTLs) that accommodate the strengths of even the weaker segment of the population. Thirty male and thirty female participants were recruited from a university student population. Participants were asked to exert their maximum possible forces in a counter-clockwise direction on handwheels of different sizes (35 cm, 45 cm, 60 cm, and 70 cm) and angles (0°-horizontal, 45°-slanted, and 90°-vertical). The participant’s posture was controlled by adjusting the handwheel to be at the elbow level of each participant, requiring the participant to stand erect, and restricting the hand placements to be in the 10-11 o’clock position for the left hand and the 4-5 o’clock position for the right hand. A torque transducer (Futek TDF600) was used to measure the maximum torques generated by the human. Three repetitions were performed for each handwheel condition, and the average was computed. Results showed that, at all handwheel angles, as the handwheel diameter increased, the maximum torques generated also increased, while the underlying forces decreased. In controlling the handwheel diameter, the 0° handwheel was associated with the largest torques and forces, and the 45° handwheel was associated with the lowest torques and forces. Hence, a larger handwheel diameter –as large as 70 cm– in a 0° angle is favored for increasing the torque production capacities of users. Also, it was recognized that, regardless of the handwheel diameter size and angle, the torque demands in the field are much greater than humans’ torque production capabilities. As such, this research proposed RTLs for the different handwheel conditions by using the 25th percentile values of the females’ torque strengths. The proposed recommendations may serve future standard developers in defining torque limits that accommodate humans’ strengths.

Keywords: handwheel angle, handwheel diameter, humans’ torque production strengths, recommended torque limits

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Authors: Sandra T. Matarneh, Mark Danso-Amoako, Salam Al-Bizri, Mark Gaterell

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Today’s facilities are ever more sophisticated and the need for available and reliable information for operation and maintenance activities is vital. The key challenge for facilities managers is to have real-time accurate and complete information to perform their day-to-day activities and to provide their senior management with accurate information for decision-making process. Currently, there are various technology platforms, data repositories, or database systems such as Computer-Aided Facility Management (CAFM) that are used for these purposes in different facilities. In most current practices, the data is extracted from paper construction documents and is re-entered manually in one of these computerized information systems. Construction Operations Building information exchange (COBie), is a non-proprietary data format that contains the asset non-geometric data which was captured and collected during the design and construction phases for owners and facility managers use. Recently software vendors developed add-in applications to generate COBie spreadsheet automatically. However, most of these add-in applications are capable of generating a limited amount of COBie data, in which considerable time is still required to enter the remaining data manually to complete the COBie spreadsheet. Some of the data which cannot be generated by these COBie add-ins is essential for facilities manager’s day-to-day activities such as job sheet which includes preventive maintenance schedules. To facilitate a seamless data transfer between BIM models and facilities management systems, we developed a framework that enables automated data generation using the data extracted directly from BIM models to external web database, and then enabling different stakeholders to access to the external web database to enter the required asset data directly to generate a rich COBie spreadsheet that contains most of the required asset data for efficient facilities management operations. The proposed framework is a part of ongoing research and will be demonstrated and validated on a typical university building. Moreover, the proposed framework supplements the existing body of knowledge in facilities management domain by providing a novel framework that facilitates seamless data transfer between BIM models and facilities management systems.

Keywords: building information modeling, BIM, facilities management systems, interoperability, information management

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Authors: Morteza Ghorbani, Reza Ghorbani

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Cavitation phenomenon has attracted much attention in the mechanical and biomedical technologies. Despite the simplicity and mostly low cost of the devices generating cavitation bubbles, the physics behind the generation and collapse of these bubbles particularly in micro/nano scale has still not well understood. In the chemical industry, micro/nano bubble generation is expected to be applicable to the development of porous materials such as microcellular plastic foams. Moreover, it was demonstrated that the presence of micro/nano bubbles on a surface reduced the adsorption of proteins. Thus, the micro/nano bubbles could act as antifouling agents. Micro and nano bubbles were also employed in water purification, froth floatation, even in sonofusion, which was not completely validated. Small bubbles could also be generated using micro scale hydrodynamic cavitation. In this study, compared to the studies available in the literature, we are proposing a novel approach in micro scale utilizing the energy produced during the interaction of the spray affected by the hydrodynamic cavitating flow and a thin aluminum plate. With a decrease in the size, cavitation effects become significant. It is clearly shown that with the aid of hydrodynamic cavitation generated inside the micro/mini-channels in addition to the optimization of the distance between the tip of the microchannel configuration and the solid surface, surface temperatures can be increased up to 50C under the conditions of this study. The temperature rise on the surfaces near the collapsing small bubbles was exploited for energy harvesting in small scale, in such a way that miniature, cost-effective, and environmentally friendly energy-harvesting devices can be developed. Such devices will not require any external power and moving parts in contrast to common energy-harvesting devices, such as those involving piezoelectric materials and micro engine. Energy harvesting from thermal energy has been widely exploited to achieve energy savings and clean technologies. We are proposing a cost effective and environmentally friendly solution for the growing individual energy needs thanks to the energy application of cavitating flows. The necessary power for consumer devices, such as cell phones and laptops, can be provided using this approach. Thus, this approach has the potential for solving personal energy needs in an inexpensive and environmentally friendly manner and can trigger a shift of paradigm in energy harvesting.

Keywords: cavitation, energy, harvesting, micro scale

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Authors: Yana Gorina, Olga Lopatina, Elina Tsigeman, Larisa Mararitsa

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The ability to act in concert with others, the so-called sensorimotor synchronisation, is a fundamental human ability that underlies successful interpersonal coordination. The manifestation of accuracy and plasticity in synchronisation is an adaptive aspect of interaction with the environment, as well as the ability to predict upcoming actions and behaviour of others. The ability to temporarily coordinate one’s actions with a predictable external event is manifested in such types of social behaviour as a synchronised group dance to music played live by an orchestra, group sports (rowing, swimming, etc.), synchronised actions of surgeons during an operation, applause from an admiring audience, walking rhythms, etc. Both our body and mind are involved in achieving the synchronisation during social interactions. However, it has not yet been well described how the brain determine the external rhythm and what neuropeptides coordinate and synchronise actions. Over the past few decades, there has been an increased interest among neuroscientists and neurophysiologists regarding the neuropeptide oxytocin in the context of its complex, diverse and sometimes polar effects manifested in the emotional and social aspects of behaviour (attachment, trust, empathy, emotion recognition, stress response, anxiety and depression, etc.). Presumable, oxytocin might also be involved in social synchronisation processes. The aim of our study is to test the hypothesis that oxytocin is linked to interpersonal synchronisation in a pair of strangers.

Keywords: behavior, movement, oxytocin, synchronization

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Authors: Ju-Hong Lee, Ching-Wei Liao

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Adaptive beamforming using antenna array of sensors is useful in the process of adaptively detecting and preserving the presence of the desired signal while suppressing the interference and the background noise. For conventional adaptive array beamforming, we require a prior information of either the impinging direction or the waveform of the desired signal to adapt the weights. The adaptive weights of an antenna array beamformer under a steered-beam constraint are calculated by minimizing the output power of the beamformer subject to the constraint that forces the beamformer to make a constant response in the steering direction. Hence, the performance of the beamformer is very sensitive to the accuracy of the steering operation. In the literature, it is well known that the performance of an adaptive beamformer will be deteriorated by any steering angle error encountered in many practical applications, e.g., the wireless communication systems with massive antennas deployed at the base station and user equipment. Hence, developing effective signal processing techniques to deal with the problem due to steering angle error for array beamforming systems has become an important research work. In this paper, we present an effective signal processing technique for constructing an adaptive beamformer against the steering angle error. The proposed array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. Based on the presumed steering vector and a preset angle range for steering mismatch tolerance, we first create a matrix related to the direction vector of signal sources. Two projection matrices are generated from the matrix. The projection matrix associated with the desired signal information and the received array data are utilized to iteratively estimate the actual direction vector of the desired signal. The estimated direction vector of the desired signal is then used for appropriately finding the quiescent weight vector. The other projection matrix is set to be the signal blocking matrix required for performing adaptive beamforming. Accordingly, the proposed beamformer consists of adaptive quiescent weights and partially adaptive weights. Several computer simulation examples are provided for evaluating and comparing the proposed technique with the existing robust techniques.

Keywords: adaptive beamforming, robustness, signal blocking, steering angle error

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Emmanuel Bole Akinpelu

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Festival is a social event that takes place every year which showcase culture and other social activities that usually take place in an environment or town. However, Oranyan Festival is an annual event organized and celebrated in Oyo town in honor of Oranyan the great who is reputed to be the overall head of the Kings of the Yoruba. This event is attended by people from all works of life. The Oyos are used to celebrating various cultural festivals; like Ogun, Oya, Sango, Egungun, Obatala and others. However, Oranyan festival in Oyo is a recent development in honour of Oranyan. He was said to be powerful and an embodiment of a unique cultural tradition. The study examined the significance of the festival to the Oyo Yoruba group. Oyo Yoruba cultural heritage include; Ewi, Ijala, Traditional food ‘Amala and Gbegiri’, Ekun Iyawo, (Bridal Chants), Traditional Music, Traditional Dance, Traditional Game ‘Ayo Olopon’ Eke (Traditional wrestling) and others. Data for this work was gathered through archival sources as journals and relevant publications on the various Oyo Yoruba Traditional Art and Culture. The study is of the opinion that the festival has influence over the religion, Political, economic and other aspects of the modern day traditions. The study also revealed that Oranyan Festival made people to have a better understanding of their rich Cultural Heritage and promoted unity among all and sundry. It also promotes peace among the people. Conclusively, it promotes the rich Cultural Heritage of Oyo Yoruba’s both within and outside NIGERIA and the world at large.

Keywords: Yoruba Oyo, arts and culture, Oranyan, festival

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Authors: Cheng Chieh Hsu, Alfred Chen, Yu-Pin Ma, Meng-Jie Lin, Fu Pai Chiu, Yi-Yan Sie

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In this study, it is attempted to construct an augmented reality display platform (ARDP), and its objectives are two facets, i.e. 1) providing a creative display mode for museums/historical heritages and 2) providing a benchmark for human-computer interaction professionals to build an augmented reality display platform. A general augmented reality theory has been explored in the very beginning and afterwards a systematic process model is proposed. There are three major core tasks to be done for the platform, i.e. 1) constructing the physical interactive table, 2) designing the media, and 3) designing the media carrier. In order to describe how the platform manipulates, the authors have introduced Tainan Confucius Temple, a cultural heritage in Taiwan, as a case study. As a result, a systematic process with thirteen steps has been developed and it aims at providing a rational method for constructing the platform.

Keywords: human-computer interaction, media, media carrier, augmented reality display platform

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Authors: M. Jalali Azizpour, H. Mohammadi Majd, A.R. Aboudi Asl, D. Sajedipour, V. Tawaf

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Sandblasting is a generally used surface treatment technique to improve the residual stress and adhesion of coatings to substrate. The goal of this work is to study the effect of temperature on the residual stress in sandblasting AISI1045 substrate. For this purpose a two dimensional axisymmetric model of shot impacting on an AISI 1045 disc was generated using ABAQUS version 6.10. The result shows for sandblasting temperature there is an optimum condition. In addition there are other effective factors that influence the fatigue life of parts.

Keywords: modeling, shot peen, residual stress, temperature

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Authors: S. Jagadeesh Kumar

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Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

Procedia PDF Downloads 158

Authors: Yeo Kyeong Lee, Ji Yeon Kang, Eun Mi Ryu, Hee Sun Kim, Yeong Soo Shin

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The objective of this paper is an investigation of the effects of the thickness and axial loading during a fire test on the load-bearing capacity of a fire-damaged normal-strength concrete wall. Two factors are attributed to the temperature distributions in the concrete members and are mainly obtained through numerous experiments. Toward this goal, three wall specimens of different thicknesses are heated for 2 h according to the ISO-standard heating curve, and the temperature distributions through the thicknesses are measured using thermocouples. In addition, two wall specimens are heated for 2 h while simultaneously being subjected to a constant axial loading at their top sections. The test results show that the temperature distribution during the fire test depends on wall thickness and axial load during the fire test. After the fire tests, the specimens are cured for one month, followed by the loading testing. The heated specimens are compared with three unheated specimens to investigate the residual load-bearing capacities. The fire-damaged walls show a minor difference of the load-bearing capacity regarding the axial loading, whereas a significant difference became evident regarding the wall thickness. To validate the experiment results, finite element models are generated for which the material properties that are obtained for the experiment are subject to elevated temperatures, and the analytical results show sound agreements with the experiment results. The analytical method based on validated thought experimental results is applied to generate the fire-damaged walls with 2,800 mm high considering the buckling effect: typical story height of residual buildings in Korea. The models for structural analyses generated to deformation shape after thermal analysis. The load-bearing capacity of the fire-damaged walls with pin supports at both ends does not significantly depend on the wall thickness, the reason for it is restraint of pinned ends. The difference of the load-bearing capacity of fire-damaged walls as axial load during the fire is within approximately 5 %.

Keywords: normal-strength concrete wall, wall thickness, axial-load ratio, slenderness ratio, fire test, residual strength, finite element analysis

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Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour

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Nowadays, huge amount of multimedia repositories make the browsing, retrieval and delivery of video contents very slow and even difficult tasks. Video summarization has been proposed to improve faster browsing of large video collections and more efficient content indexing and access. In this paper, we focus on approaches to video summarization. The video summaries can be generated in many different forms. However, two fundamentals ways to generate summaries are static and dynamic. We present different techniques for each mode in the literature and describe some features used for generating video summaries. We conclude with perspective for further research.

Keywords: video summarization, static summarization, video skimming, semantic features

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Authors: Romy Martinez

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This paper focuses on the use of the indigenous language Guarani in Paraguayan popular song and on some key interpreters born between the 1930s and 1980s. It analyses two representative musical genres of Paraguay, the Polka Paraguaya and Guarania. The lyrics of these genres follow one of four poetic-linguistic forms: to be entirely in Guarani, entirely in Spanish, bilingual (alternating verses in Guarani and Spanish), or in Jopará; the last being a form where words of both languages may be mixed in a single verse. Through these forms, the lyrics alternate and combine the indigenous voice with the one introduced with colonisation, in turn reflecting how Guarani seems to constantly transit, to and from, between a position of disdain and of value within Paraguayan society. Through analysing recordings of Polkas, Paraguayas, and Guaranias, it identifies three styles of singing adopted by female singers who include these genres in their repertoires, namely Paraguayan classical folk, Paraguayan folk, and Paraguayan pop-folk. This analysis is informed by a pilot study which consisted of online interviews with several Paraguayan artists, revealing significant aspects of their backgrounds and musical influences. In addition, it draws on autoethnographic approaches, building on the experience of the music researcher and singer. From a decolonising perspective, the paper brings together the distinctive voices and sounds expressed in popular songs from a marginalised country, language, and gender.

Keywords: female singers, Guarani, Paraguayan song, performance

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Authors: Gokul G. Kshirsagar

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Native folk theatre and folk songs have a significant influence on the origin and development of Indian cinema. Therefore, the presence of songs and music has been an integral part and special characteristics of Indian cinema which is popularly known as Bollywood. An Indian cinema without songs, either in Hindi or other regional languages, is simply unimaginable. The present paper, in the first part, attempts to explain the use and need of musical songs and also the psychology of Indian audience in this respect with reference to some of the films which give primary importance to songs. In the second part, the paper tries to situate the present study in the context by referring to the Hindi language drama film Teesari Kasam directed by Basu Bhattacharys. The film is based on the Hindi novelist Phanishwarnath Renu’s short story Teesari Kasam (Mare Gaye Gulfam) in this adapted film, the director has made use of eight songs, but these songs are the extensive versions of the songs as used in the original story. Thus, the main aim of the paper is to underscore the fact that through artistic use of the musical, the director has succeeded in transforming the central feelings conveyed in the original story. Eventually, through the present study of the film adaptation, the relevance of songs in films will be illustrated and understood.

Keywords: Bollywood, folk theatre, folk songs, film adaptation

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Authors: Essam Al Daoud

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Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

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Authors: Daniela Stephanie Kuenstle

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Complex industries such as banking or insurance experience slow growth in mobile sales. While today’s mobile applications are sophisticated and enable location based and personalized services, consumers prefer online or even face-to-face services to complete complex transactions. A possible reason for this reluctance is that the provided service within transactional mobile applications (apps) does not adequately correspond to users’ needs. Therefore, this paper examines the impact of the user context on mobile service (m-service) in m-commerce. Motivated by the potential which context-sensitive m-services hold for the future, the impact of temporal variations as a dimension of user context, on m-service design is examined. In particular, the research question asks: Does consumer urgency function as a determinant of m-service composition in transactional apps by moderating the relation between m-service type and m-service success? Thus, the aim is to explore the moderating influence of urgency on m-service types, which includes Technology Mediated Service and Technology Generated Service. While mobile applications generally comprise features of both service types, this thesis discusses whether unexpected urgency changes customer preferences for m-service types and how this consequently impacts the overall m-service success, represented by purchase intention, loyalty intention and service quality. An online experiment with a random sample of N=1311 participants was conducted. Participants were divided into four treatment groups varying in m-service types and urgency level. They were exposed to two different urgency scenarios (high/ low) and two different app versions conveying either technology mediated or technology generated service. Subsequently, participants completed a questionnaire to measure the effectiveness of the manipulation as well as the dependent variables. The research model was tested for direct and moderating effects of m-service type and urgency on m-service success. Three two-way analyses of variance confirmed the significance of main effects, but demonstrated no significant moderation of urgency on m-service types. The analysis of the gathered data did not confirm a moderating effect of urgency between m-service type and service success. Yet, the findings propose an additive effects model with the highest purchase and loyalty intention for Technology Generated Service and high urgency, while Technology Mediated Service and low urgency demonstrate the strongest effect for service quality. The results also indicate an antagonistic relation between service quality and purchase intention depending on the level of urgency. Although a confirmation of the significance of this finding is required, it suggests that only service convenience, as one dimension of mobile service quality, delivers conditional value under high urgency. This suggests a curvilinear pattern of service quality in e-commerce. Overall, the paper illustrates the complex interplay of technology, user variables, and service design. With this, it contributes to a finer-grained understanding of the relation between m-service design and situation dependency. Moreover, the importance of delivering situational value with apps depending on user context is emphasized. Finally, the present study raises the demand to continue researching the impact of situational variables on m-service design in order to develop more sophisticated m-services.

Keywords: mobile consumer behavior, mobile service design, mobile service success, self-service technology, situation dependency, user-context sensitivity

Procedia PDF Downloads 268

Authors: S. Blanchard, D. Beladjine, K. Beddiar

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Since 2015, the arrival of BIM in the building sector in France has turned the corporation world upside down. Not only constructive practices have been impacted, but also the uses and the men who have undergone important changes. Thus, the new collaborative mode generated by the BIM and the digital model has challenged the supremacy of some construction actors because the process involves working together taking into account the needs of other contributors. New BIM tools have emerged and actors in the act of building must take ownership of them. It is in this context that under the impetus of a European directive and the French government's encouragement of new missions and job profiles have. Moreover, concurrent engineering requires that each actor can advance at the same time as the others, at the whim of the information that reaches him, and the information he has to transmit. However, in the French legal system around public procurement, things are not planned in this direction. Also, a consequent evolution must take place to adapt to the methodology. The new missions generated by the BIM in France require a good mastery of the tools and the process. Also, to meet the objectives of the BIM approach, it is possible to define a typical job profile around the BIM, adapted to the various sectors concerned. The multitude of job offers using the same terms with very different objectives and the complexity of the proposed missions motivated by our approach. In order to reinforce exchanges with professionals or specialists, we carried out a statistical study to answer this problem. Five topics are discussed around the business area: the BIM in the company, the function (business), software used and BIM missions practiced (39 items). About 1400 professionals were interviewed. These people work in companies (micro businesses, SMEs, and Groups) of construction, engineering offices or, architectural agencies. 77% of respondents have the status of employees. All participants are graduated in their trade, the majority having level 1. Most people have less than a year of experience in BIM, but some have 10 years. The results of our survey help to understand why it is not possible to define a single type of BIM Manager. Indeed, the specificities of the companies are so numerous and complex and the missions so varied, that there is not a single model for a function. On the other hand, it was possible to define 3 main professions around the BIM (Manager, Coordinator and Modeler) and 3 main missions for the BIM Manager (deployment of the method, assistance to project management and management of a project).

Keywords: BIM manager, BIM modeler, BIM coordinator, project management

Procedia PDF Downloads 163

Authors: Burçin Saltık, Levent Genç

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In this study, it was aimed to determine a route for identification of rice cultivation areas within Thrace and Marmara regions of Turkey using remote sensing and GIS. Landsat 8 (OLI-TIRS) imageries acquired in production season of 2013 with 181/32 Path/Row number were used. Four different seasonal images were generated utilizing original bands and different transformation techniques. All images were classified individually using supervised classification techniques and Land Use Land Cover Maps (LULC) were generated with 8 classes. Areas (ha, %) of each classes were calculated. In addition, district-based rice distribution maps were developed and results of these maps were compared with Turkish Statistical Institute (TurkSTAT; TSI)’s actual rice cultivation area records. Accuracy assessments were conducted, and most accurate map was selected depending on accuracy assessment and coherency with TSI results. Additionally, rice areas on over 4° slope values were considered as mis-classified pixels and they eliminated using slope map and GIS tools. Finally, randomized rice zones were selected to obtain maximum-minimum value ranges of each date (May, June, July, August, September images separately) NDVI, LSWI, and LST images to test whether they may be used for rice area determination via raster calculator tool of ArcGIS. The most accurate classification for rice determination was obtained from seasonal LSWI LULC map, and considering TSI data and accuracy assessment results and mis-classified pixels were eliminated from this map. According to results, 83151.5 ha of rice areas exist within study area. However, this result is higher than TSI records with an area of 12702.3 ha. Use of maximum-minimum range of rice area NDVI, LSWI, and LST was tested in Meric district. It was seen that using the value ranges obtained from July imagery, gave the closest results to TSI records, and the difference was only 206.4 ha. This difference is normal due to relatively low resolution of images. Thus, employment of images with higher spectral, spatial, temporal and radiometric resolutions may provide more reliable results.

Keywords: landsat 8 (OLI-TIRS), LST, LSWI, LULC, NDVI, rice

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Authors: C. E. Nugraheni, L. Abednego

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This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: hyper-heuristics, evolutionary algorithms, production scheduling, meta-heuristic

Procedia PDF Downloads 381

Authors: Mohd Faridz Ahmad, Muhammad Amir Asyraf Rosli

Abstract:

Aerobic dance has becoming a popular mode of exercise especially among women due to its fun nature. With a catchy music background and joyful dance steps, aerobic dancers would be able to have fun while sweating out. Depending on its level of aggressiveness, aerobic may also improve and maintain cardiorespiratory fitness other than being a great tool for weight loss. This study intends to prove that aerobic dance activity can bring the same, if not better impacts on health than other types of cardiovascular exercise such as jogging and cycling. The objective of this study was to evaluate and identify the effect of six weeks aerobic dance on cardiovascular fitness and weight loss among women. This study, which was held in Seremban Fit Challenge, used a quasi-experimental design. The subjects selected include a total of 14 women (n = 14) with age (32.4 years old ± 9.1), weight (65.93 kg ± 11.24) and height (165.36 ± 3.46) who joined the Seremban Fit Challenge Season 13. The subjects were asked to join an aerobic dance class with duration of one hour for six weeks in a row. As for the outcome, cardiovascular fitness was measured with a 1-mile run test while any changes on weight was measured using the weighing scale. The result showed that there was a significant difference between pre and post-test for cardiovascular fitness when p = 0.02 < 0.05 and weight loss when p = 0.00 < 0.05. In conclusion, a six-week long aerobic dance program would have a positive effect on cardiovascular fitness and weight. Therefore, aerobic dance may be used as an alternative tool for people who wish to lead a healthy lifestyle in a fun way.

Keywords: aerobic dance, cardiovascular fitness, weight loss, 1-mile run test

Procedia PDF Downloads 547

Authors: Armin Ardekani, Mohammad Akbari

Abstract:

We present a method of generating series solutions to large classes of nonlinear differential equations. The method is well suited to be adapted in mathematical software and unlike the available commercial solvers, we are capable of generating solutions to boundary value ODEs and PDEs. Many of the generated solutions converge to closed form solutions. Our method can also be applied to systems of ODEs or PDEs, providing all the solutions efficiently. As examples, we present results to many difficult differential equations in engineering fields.

Keywords: computational mathematics, differential equations, engineering, series

Procedia PDF Downloads 336

Authors: Chhaya Sharma, Dushyant Kumar

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The present work deals with the treatment of wastewater generated by paper industry by using aluminium as anode material. The quantitative and qualitative analyses of chloropenolics have been carried out by using primary clarifier effluent with the help of gas chromatography mass spectrometry. Sixteen chlorophenolics compounds have been identified and estimated. Results indicated that among 16 identified compounds, 7 are 100% removed and overall 66% reduction in chorophenolics compounds have been detected. Moreover, during the treatment, the biodegradability index of wastewater significantly increases, along with 70 % reduction in chemical oxygen demand and 99 % in color.

Keywords: aluminium anode, chlorophenolics, electrocoagulation, pollution load, wastewater

Procedia PDF Downloads 347

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

Procedia PDF Downloads 137