Search results for: dispersed region growing algorithm (DRGA)

Authors: Raja V., Chokkalingam B.

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For rough cutting, in many industries and educational institutions using carbon steels or HSS single point cutting tools in center lathe machine. In power hacksaw blades, only the cutter teeth region used to parting off the given material. The portions other than the teeth can be used as a single point cutting tool for rough turning and facing on soft materials. The hardness and Tensile strength of this used Power hacksaw blade is almost same as conventional cutting tools. In this paper, the effect of power hacksaw blades over conventional tool has been compared. Thickness of the blade (1.6 mm) is very small compared to its length and width. Hence, a special tool holding device is designed to hold the tool.

Keywords: hardness, high speed steels, power hacksaw blade, tensile strength

Procedia PDF Downloads 457

Authors: Hossam Hassan Elborombaly, Nader Y. Azab

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The Middle East region is rich with its architecture and urban settings. This makes it viable for exploring and applying different strategies that deal with conservation. Current context characterized by pollution, socioeconomic issues, behavioral problems, etc. affects architectural and urban heritage –literally- in all Middle Eastern countries. Although there have been numerous strategies in place to preserve and/ or rehabilitate heritage, all has been designed and implemented following political more than technical or methodical processes. This only resulted in more deterioration of the targeted areas. This paper explores different approaches in some selected Arab countries and relies on comparative analysis with some successful European experiences. The aim is to establish some solid basis for dealing with heritage areas; an approach that respects heritage and traditions without compromising sustainability or socioeconomic opportunities.

Keywords: rehabilitation, socioeconomic, urban conservation, urban strategy

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Authors: Mohamed Haffar, Muhammad Abdul Aziz, Ahmad Ghoneim

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The importance of having a good organizational culture that supports employee job satisfaction has fascinated both the business and academic world because of a tantalizing promise: culture can be fundamental to the enhancement of financial performance. This promise has led to growing interest for both researchers and practitioners in attempting to understand the influence of organizational culture on employees’ satisfaction and organizational performance. Even though the relationship between organizational culture and employee job satisfaction have gained attention in the literature, the majority of studies have been conducted within manufacturing organizations and tend to oversee the impact of culture on employee job satisfaction in a service-based environment. Thus, the main driving force of this study was to explore the role of organizational culture types in facilitating employee job satisfaction at Emerald Publishing Group. Interviews qualitative data analysis indicated that Emerald’s culture dominated by adhocracy and clan culture values. In addition, the findings provided evidence, which demonstrated that group and adhocracy organizational culture types play key roles in facilitating employee job satisfaction in a service-based environment.

Keywords: employee satisfaction, organizational culture, performance, service based environment

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Authors: Ritu Chaturvedi, Mayank Varun, M. S. Paul

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Heavy metal contamination of soil is a growing area of concern since the soil is the matrix that supports flora and impacts humans directly. Phytoremediation of contaminated sites is gaining popularity due to its cost effectiveness and solar driven nature. Some hyperaccumulators have been identified for their potential. Metal-accumulating plants have various mechanisms to cope up with stress and one of them is increasing antioxidative capacity. The aim of this research is to assess the effect of Vesicular arbuscular mycorrhiza (VAM) application on the phytoremedial potential of Solanum melongena (Eggplant) and level of photosynthetic pigments along with antioxidative enzymes. Results showed that VAM application increased shoot length, root proliferation pattern of plants. The level of photosynthetic pigments, proline, SOD, CAT, APX altered significantly in response to heavy metal treatment. In conclusion, VAM increased the uptake of heavy metals which lead to the activation of the defense system in plants for scavenging free radicals.

Keywords: heavy metal, phytoextraction, phytostabilization, reactive oxygen species

Procedia PDF Downloads 275

Authors: Masahiro Takahashi, Kosuke Harada, Shihomi Nakao, Mitsuhiro Higashihata, Hiroshi Ikenoue, Daisuke Nakamura, Tatsuo Okada

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Zinc oxide (ZnO) is one of the light emitting materials in ultraviolet (UV) region. In addition, ZnO nanostructures are also attracting increasing research interest as building blocks for UV optoelectronic applications. We have succeeded in synthesizing vertically-aligned ZnO nanostructures by laser interference patterning, which is catalyst-free and non-contact technique. In this study, vertically-aligned ZnO nanowall arrays were synthesized using two-beam interference. The maximum height and average thickness of the ZnO nanowalls were about 4.5 µm and 200 nm, respectively. UV lasing from a piece of the ZnO nanowall was obtained under the third harmonic of a Q-switched Nd:YAG laser excitation, and the estimated threshold power density for lasing was about 150 kW/cm2. Furthermore, UV lasing from the vertically-aligned ZnO nanowall was also achieved. The results indicate that ZnO nanowalls can be applied to random laser.

Keywords: zinc oxide, nanowall, interference laser, UV lasing

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Authors: Amie Smith, Jodi-Lyn Benjamin

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In 2020, there are currently four generations in the nursing workforce: The Veterans, Boomers, Generation X and Generation Y (Gen Y). Understanding each generation and their growing needs will equip the workforce for when the Boomers prepare for retirement, with majority of nursing leadership positions to be potentially replaced with Gen Y nurses. In SA Medical Imaging(SAMI), at Flinders Medical Centre (FMC), it has been proven that despite challenges in succession planning, Gen Y nurse leaders are able to overcome these obstacles and provide the leadership necessary to meet the changing needs in healthcare and across organisations. Changing the culture in radiology nursing has been seen as an obstacle due to the historical nursing practices and resistance to adapt to current/future practice. As radiology advances so does the role of the nurse in imaging, this has required resilience and strong support through leadership as we change and develop the culture to keep up with the evolution of technology and standard of patient care. As a result of supporting Gen Y nurses in leadership roles, SAMI, FMC has seen a positive change in culture by creating a healthy work environment which has allowed Gen Y nurses to make long lasting contributions to the nursing profession.

Keywords: changing culture, Generation Y, radiology, nursing, leadership

Procedia PDF Downloads 138

Authors: Qian Wang

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In recent years, a growing number of Chinese women choose to pursue Ph.D. education. Except for the male and female, women with PhD degrees are stigmatized as the ‘third gender’ in Chinese society. People, especially most men, believe that female PhD students challenge the traditional image and gender role of Chinese women. This gender stereotype causes a range of difficulties in finding partners in marriage market for Chinese female PhD students. In this study, the author conducted in-depth interviews with 15 participants who are currently doing their PhD studies in Chinese universities to explore their perceptions of being leftover women on the basis of their experience. All the participants are single. Based on the analysis of qualitative data, this study found that the ‘leftover women’ phenomenon among Chinese female PhD students is the result of the contradictions generated between Chinese patriarchal society and them. Although Chinese female PhD students is an attention-attracting group, the studies about them are very limited in China. This study could not only contribute to the understanding of the ‘third gender’ phenomenon and the ‘leftover women’ studies in China, but also, in practical level, could give some guidance for governments to resolve the social problems of female PhD students.

Keywords: Chinese female Ph.D. students, the ‘leftover women’, the Chinese patriarchal society, gender role, Chinese culture

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Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

Procedia PDF Downloads 583

Authors: Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Michel Dhome

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In this paper, we handle the problem of real time localization and mapping in indoor environment assisted by a partial prior 3D model, using an RGBD sensor. The proposed solution relies on a feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D floor plan of the building) along with RGBD data from a Kinect camera. The proposed approach is evaluated on a public benchmark dataset as well as on real scene acquired by a Kinect sensor.

Keywords: SLAM, global localization, 3D sensor, bundle adjustment, 3D model

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Authors: Mohsen Khaledian, Razali Ismail, Mehdi Saeidmanesh, Mahdiar Hosseinghadiry

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A semi-analytical model for impact ionization coefficient of graphene nanoribbon (GNR) is presented. The model is derived by calculating probability of electrons reaching ionization threshold energy Et and the distance traveled by electron gaining Et. In addition, ionization threshold energy is semi-analytically modeled for GNR. We justify our assumptions using analytic modeling and comparison with simulation results. Gaussian simulator together with analytical modeling is used in order to calculate ionization threshold energy and Kinetic Monte Carlo is employed to calculate ionization coefficient and verify the analytical results. Finally, the profile of ionization is presented using the proposed models and simulation and the results are compared with that of silicon.

Keywords: nanostructures, electronic transport, semiconductor modeling, systems engineering

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Authors: K. Umbleja, M. Ichino, H. Yaguchi

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In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Khaled M. El-Naggar

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This paper presents a fast and efficient technique for monitoring and supervising power system disturbances generated due to dynamic performance of power systems or faults. Monitoring power system quantities involve monitoring fundamental voltage, current magnitudes, and their frequencies as well as their negative and zero sequence components under different operating conditions. The proposed technique is based on simulated annealing optimization technique (SA). The method uses digital set of measurements for the voltage or current waveforms at power system bus to perform the estimation process digitally. The algorithm is tested using different simulated data to monitor the symmetrical components of power system waveforms. Different study cases are considered in this work. Effects of number of samples, sampling frequency and the sample window size are studied. Results are reported and discussed.

Keywords: estimation, faults, measurement, symmetrical components

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Authors: Xin-Hua Zhao

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In recent years, the growth rate of social responsibility reports disclosed by Chinese corporations has grown rapidly. The economic effects of the growing corporate social responsibility reports have become a hot topic. The article takes the chemical listed engineering corporations that disclose social responsibility reports in China as a sample, and based on the information asymmetry theory, examines the economic effect generated by corporate social responsibility disclosure with the method of ordinary least squares. The research is conducted from the perspective of analysts’ earnings forecasts and studies the impact of corporate social responsibility information disclosure on improving the accuracy of analysts' earnings forecasts. The results show that there is a statistically significant negative correlation between corporate social responsibility disclosure index and analysts’ earnings forecast error. The conclusions confirm that enterprises can reduce the asymmetry of social and environmental information by disclosing social responsibility reports, and thus improve the accuracy of analysts’ earnings forecasts. It can promote the effective allocation of resources in the market.

Keywords: analysts' earnings forecasts, corporate social responsibility disclosure, economic effect, information asymmetry

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Authors: Ahmed Saheel

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Enhanced oil recovery using carbon dioxide (CO₂-EOR) is a method that can increase oil production beyond what is typically achievable using conventional recovery methods by injecting, and hence storing, carbon dioxide (CO₂) in the oil reservoir. In Libya, plans are under way to source a proportion of this CO₂ from subsurface geology that is known from previous drilling to contain high volumes of CO₂. But first these subsurface volumes need to be more clearly defined and understood. Focusing on the Al-Harouj region of central Libya, ground gravity and airborne magnetic data from the LPI database and the African Magnetic Mapping Project respectively have been prepared and processed by Libyan Petroleum Institute (LPI) and Reid Geophysics Limited (RGL) to produce a range of grids and related products suitable for interpreting geological structure and to make recommendations for subsequent work that will assist CO₂ exploration for purposes of enhanced oil recovery (EOR).

Keywords: gravity, magnetic, deduced lineaments, upward continuation

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

Procedia PDF Downloads 242

Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo, Linhang Zhu

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This study proposed a 3D human body reconstruction method, which integrates multi-view joint information into a set of joints and processes it with a parametric human body template. Firstly, we obtained human body image information captured from multiple perspectives. The multi-view information can avoid self-occlusion and occlusion problems during the reconstruction process. Then, we used the MvP algorithm to integrate multi-view joint information into a set of joints. Next, we used the parametric human body template SMPL-X to obtain more accurate three-dimensional human body reconstruction results. Compared with the traditional single-view parametric human body template reconstruction, this method significantly improved the accuracy and stability of the reconstruction.

Keywords: parametric human body templates, reconstruction of the human body, multi-view, joint

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Authors: Naime Boudemagh

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In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

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Authors: Shiuh-Jer Huang, Shin-Ham Lee, Sheam-Chyun Lin

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A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.

Keywords: balance control, synchronization control, two-wheel inverted pendulum, TWIP

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Authors: Mayuri Gandhi, Nayan Agrawal, Harshita Bhatia

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In the present work, cerium fluoride (CeF3) was selected as the host material because of its high density, fast response and high radiation resistance, efficient absorption and energy transfer by host (to activator). For the synthesis of CeF3 nanoparticles doped with Sm3+ ion, co-precipitation route was employed. Thus for optimum results, concentration dependent studies of the fluorescence of Sm3+ was carried out. The photoluminescence gave emissions in both visible as well as the NIR region and therefore it can have its application in solar cells, where it can absorb a large spectrum of energy. CeF3:Sm3+ nanoparticles were carefully incorporated in a suitable polymer matrix in order to demonstrate a variety of applications to improve the performance of the polymer materials and use it to develop high grade optoelectronic devices such as LEDs, security labelling, lasers, displays, biological imaging, etc.

Keywords: bioimaging, cerium fluoride, NIR emission, samarium

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Authors: Omar Alelweet

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Carbon emissions are quantified in terms of carbon dioxide equivalents, generated through a specific activity or accumulated throughout the life stages of a product or service. Given the growing concern about climate change and the role of carbon dioxide emissions in global warming, this initiative aims to create awareness and understanding of the impact of human activities and identify potential areas for improvement regarding the management of the carbon footprint on campus. Given that trees play a vital role in reducing carbon emissions by absorbing CO₂ during the photosynthesis process, this paper evaluated the contribution of each tree to reducing those emissions. Collecting data over an extended period of time is essential to monitoring carbon dioxide levels. This will help capture changes at different times and identify any patterns or trends in the data. By linking the data to specific activities, events, or environmental factors, it is possible to identify sources of emissions and areas where carbon dioxide levels are rising. Analyzing the collected data can provide valuable insights into ways to reduce emissions and mitigate the impact of climate change.

Keywords: sustainability, green building, environmental impact, CO₂

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Authors: Ravinder Reddy Butreddy, Sadhana Katlakunta

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The nanocomposites of CoFe2O4-xZrO2 with different loadings of ZrO2 (x = 0.025, 0.05, 0.075, 0.1 and 1.5) were prepared using ball mill method. All the samples were prepared at 980°C/1h using microwave sintering method. The x-ray diffraction patterns show the existence of tetragonal/monoclinic phase of ZrO2 and cubic phase of CoFe2O4. The effects of ZrO2 on structural and microstructural properties of CoFe2O4 composite ceramics were investigated. It is observed that the density of the composite decreases and porosity increases with x. The magnetic properties such as saturation magnetization (Ms), and Coercive field were calculated at room temperature. The Ms is decreased with x while coercive field is increased with x. The dielectric parameters exhibit the relaxation behavior in high-frequency region and showing increasing trend with ZrO2 concentration, showing suitable

Keywords: dielectric properties, magnetic properties, microwave sintering, nanocomposites

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Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

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The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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Authors: Chander Shekhar, Manoj Kumar

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The present research paper is based on the explorations and excavations of Buddhist sites of the Indian state Haryana. It is a small state in north India. Earlier it was part of greater Punjab. Haryana has a very rich ancient history right from the Stone Age. It is known as the cradle of civilization. During the Buddha period, Haryana was very prosperous. Buddha also visited this region during the travel of the northwest province of British India. In this research work, the authors describe the Buddhist trail in Haryana and the tangible heritage of Buddhism, which were built in the respect and memory of the Buddha's journey like Stupa, Monasteries, Pillar, sculptures, etc. Several stupas like Chaneti Stupa, Thanesar Stupa, Agroha stupa, Adibadri, Katrawali, Assandh Stupa, and many monasteries were come into light during the excavation and exploration in Haryana as well as a lot of Buddhist sculptures also found.

Keywords: archaeology, Buddhism, exploration, excavations, stupa

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Authors: Xochilt Ramirez-Garcia, Mario Garcia-Valdez

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Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error.

Keywords: algorithms, collaborative filtering, intelligent systems, fuzzy logic, recommender systems

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Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Tarnai Tena, Strinić Dean

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Chronic non-communicable diseases are today the leading cause of mortality, morbidity and mortality disability at the world level and in Croatia. Among them are the most represented precisely cardiovascular diseases (CVD), so today we are talking about their global card epidemic. From 2018 to 2021, cardiovascular diseases are the leading cause of death for both women and men in the Dubrovnik- Neretva County. With regard to the COVID-19 pandemic, which has taken over, without forgetting how much these patients are additionally affected, we are still talking about the primary cause of sickness and death in the population of this county and region. In this record, we present collected data processed according to gender and disease classification. We also bring a kind of overview because, for years, we have been following how the population of one of the origins of the Mediterranean diet has been struggling with cardiovascular diseases.

Keywords: cardiovascular disease, burden, COVID-19, epidemiology, ishemic heart disease, cardiovascular medicine

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Authors: Enas R. Shouman

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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

Procedia PDF Downloads 109