Search results for: commercial real estate

Authors: B. Hamidu, A. Abdulhamid, S. Mohammed, S. Idi

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This study examined the household expenditure pattern on animal products in Bauchi metropolis. A cross-sectional data were collected from 157 households using systematic sampling technique. The data were analyzed using descriptive statistics, correlation and regression models. The results reveal that the mean age, mean household size, mean monthly income and mean total expenditure on animal products were found to be 39 years, 7 persons, N28,749 and N1,740 respectively. It was also found that household monthly income, number of children and educational level of the household heads (P<0.01) significantly influence the level of household expenditure on animal products. Similarly, income was found to be the most important factor determining the proportion of total expenditure on animal products (20.91%). Income elasticity was found to be 0.66 indicating that for every 1% increase in income, expenditure on animal products would increase by 0.66%. Furthermore, beef was found to be the most preferred (54.83%) and most regularly consumed (61.84%) animal products. However, it was discovered that the major constraints affecting the consumption of animal products were low-income level of the households (29.85%), high cost of animal products (15.82%) and increase in prices of necessities (15.82%). Therefore to improve household expenditure on animal products per capita real income of the households should be improved through creation of employment opportunities. Also stabilization of market prices of animal products and other foods items of necessities through increased production are recommended.

Keywords: animal products, economics, expenditure, households

Procedia PDF Downloads 246

Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

Procedia PDF Downloads 104

Authors: Khanita Limhan

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Due to the fact that the instructional media is a very crucial implement in English as Foreign Language (EFL) teaching and learning because it simply motivates or demotivates the learners to learn English. Furthermore, it could enormously involve the learners in the real language. The mixed-method research investigates undergraduate student teachers at the Faculty of Education in aspects of the preferences and attitudes towards the use of instructional media in a Thai EFL classroom. Therefore, there were 21 female and 4 male students, who are being educated to be secondary English teachers in Thai educational system, participated in this study. Moreover, the data was gathered from six open-ended questions; obviously, all were given at least 30 - 45 minutes to express their preferences and thoughts in their native tongue at the end of the English for English teacher course. The results of this study indicated that 64 % of student teachers preferred to study English grammar through songs and music; 54% of them desire to learn English grammar through English movies; and 40% of them want to acquire English grammar by watching short documentaries. Since, the participants illustrated that they feel neither anxious nor bored; however, they feel very excited and fun while studying. In addition, they pointed out that they could improve their listening proficiency; obtain new vocabulary; and comprehend the cultural content authentically from the instructional media. It can be concluded that the use of instructional media affects students and teachers’ motivations and attitudes on English teaching and learning.

Keywords: attitudes, preferences, student teachers, instructional media

Procedia PDF Downloads 282

Authors: Benlakhdar Mohamed Larbi, Yagoub Asma

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Purpose: This study aims at highlighting the significance and importance of utilizing marketing information system (MKIS) on decision-making, by clarifying the need for quick and efficient decision-making due to time saving and preventing of duplication of work. Design, methodology, approach: The study shows the roles of each part of MKIS for developing marketing strategy, which present a real challenge to individuals and institutions in an era characterized by uncertainty and clarifying the importance of each part separately, depending on decision type and the nature of the situation. The empirical research method was evaluated by specialized experts, conducted by means of questionnaires. Correlation analysis was employed to test the validity of the procedure. Results: The empirical study findings confirmed positive relationships between the level of utilizing and adopting ‘decision support system and marketing intelligence’ and the success of an organizational decision-making, and provide the organization with a competitive advantage as it allows the organization to solve problems. Originality/value: The study offer better understanding of performance- increasing market share as an organizational decision making based on marketing information system.

Keywords: database, marketing research, marketing intelligence, decision support system, decision-making

Procedia PDF Downloads 330

Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF

Procedia PDF Downloads 166

Authors: Ali Essam El Shazly

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The Haussmannization plan of Cairo in 1867 formed a regular network of roundabout spaces, though deteriorated at present. The method of identifying the spatial structure of roundabout Cairo for conservation matches the voronoi diagram with the space syntax through their geometrical property of spatial convexity. In this initiative, the primary convex hull of first-order voronoi adopts the integral and control measurements of space syntax on Cairo’s roundabout generators. The functional essence of royal palaces optimizes the roundabout structure in terms of spatial measurements and the symbolic voronoi projection of 'Tahrir Roundabout' over the Giza Nile and Pyramids. Some roundabouts of major public and commercial landmarks surround the pole of 'Ezbekia Garden' with a higher control than integral measurements, which filter the new spatial structure from the adjacent traditional town. Nevertheless, the least integral and control measures correspond to the voronoi contents of pollutant workshops and the plateau of old Cairo Citadel with the visual compensation of new royal landmarks on top. Meanwhile, the extended suburbs of infinite voronoi polygons arrange high control generators of chateaux housing in 'garden city' environs. The point pattern of roundabouts determines the geometrical characteristics of voronoi polygons. The measured lengths of voronoi edges alternate between the zoned short range at the new poles of Cairo and the distributed structure of longer range. Nevertheless, the shortest range of generator-vertex geometry concentrates at 'Ezbekia Garden' where the crossways of vast Cairo intersect, which maximizes the variety of choice at different spatial resolutions. However, the symbolic 'Hippodrome' which is the largest public landmark forms exclusive geometrical measurements, while structuring a most integrative roundabout to parallel the royal syntax. Overview of the symbolic convex hull of voronoi with space syntax interconnects Parisian Cairo with the spatial chronology of scattered monuments to conceive one universal Cairo structure. Accordingly, the approached methodology of 'voronoi-syntax' prospects the future conservation of roundabout Cairo at the inferred city-level concept.

Keywords: roundabout Cairo, first-order Voronoi, space syntax, spatial structure

Procedia PDF Downloads 501

Authors: Yueh Hsiu Giffen Cheng, Teng Jung Wang

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According to the study of British national advisory council on creative and cultural education（NACCCE, what the present and the future need awesome innovative and creative people from the perspective of commercial human resources. Therefore, we can know from above, creativity plays an important role in today’s enterprise indeed. Besides, many companies are aimed at developing team work as their main goal, so “creativity” and “teamwork” become more and more important factors to succeed and team creativity also turn into an important issue gradually. Then, the study takes in-depth interviews of design companies’ leaders and uses self-designed questionnaire regarding affecting team creativity to conduct cross-analysis. The results show that for those creative-oriented integrated design companies, their design strategies don’t begin until data collection and their scripts are usually the best way to inspire creativity. Besides, passing down a legacy of experiences are their common educational training. Most important of all, their organizational resources and leaders can assist all the team to learn and grow effectively and the good interaction between the leader and the member can also bring work flexibility and efficiency. In short, the leader’s expectation of members’ performance can cause them to encourage each other to progress. Moreover, the analysis of questionnaire indicates that members who are open-minded and leaders who have transformational leadership style can both help to establish a good team interaction. Furthermore, abundant resources and training system are also good approaches to establish a harmonious relationship. Finally, through integrating the outcomes of interviews and questionnaires, we can infer that those integrated design companies’ circumstances of design progress are mainly from their leaders’ guidance. In addition, the analysis of design problems are focused on their creative strategies and their scripts and sketches can also inspire their creativity. In sum, the feature of all team is influenced by 4 factors: leaders who have transformational leadership style, open-minded members, flexible working environment, resources and interactive relationship. Ultimately, the study hopes that the result above can apply to the design-related industries or help general companies elevate the team creativity.

Keywords: creativity, team creativity, integrated design companies, design process

Procedia PDF Downloads 356

Authors: Yi Yau, Chia-Huei Hsiao

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The elderly society is already a problem of globalization, and Taiwan will enter a super-aged society in 2025. Therefore, how to improve the health of the elderly and reduce the government's social burden is an important issue at present. Exercise is the best medical care, and it is also a healthy activity for people to live a healthy life. Facing the super-aged society in the future, it is necessary to attract them to participate in sports voluntarily through sports promotion so that they can live healthy and independent lives and continue to participate in society to enhance the well-being of the elderly. Experiential marketing and sports participation are closely related. In the past, it was mainly aimed at consumer behavior at the commercial level. At present, there are not many study objects focusing on participant behavior and middle-aged and elderly people. Therefore, this study takes the news emerged sport-Pickleball that has been loved by silver-haired people in recent years as the research sport. It uses questionnaire surveys and intentional sampling methods. The purpose of the group is to understand the middle-aged and elderly people’s experience and behavior patterns of Pickleball, explore the relationship between experiential marketing and participants' intentional behaviors, and predict which aspects of experiential marketing will affect their intentional behaviors. The findings showed that experience marketing is highly positively correlated with behavioral intentions, and experience marketing has a positive predictive power for behavioral intentions. Among them, "ACT" and "SENSE" are predictive variables that effectively predict behavioral intentions. This study proves the feasibility of pickleball for middle-aged and senior sports. It is recommended that in the future curriculum planning, try to simplify the exercise steps, increase the chances of contact with the sphere, and enhance the sensory experience to enhance the sense of success during exercise, and then generate exercise motivation, and ultimately change the exercise mode or habits and promote health.

Keywords: newly emerged sports, middle age and elderly, health promotion, ACT, SENSE

Procedia PDF Downloads 156

Authors: František Šebek, Petr Kubík, Jindřich Petruška, Jiří Hůlka

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Present study is aimed on the cutting process of circular cross-section rods where the fracture is used to separate one rod into two pieces. Incorporating the phenomenological ductile fracture model into the explicit formulation of finite element method, the process can be analyzed without the necessity of realizing too many real experiments which could be expensive in case of repetitive testing in different conditions. In the present paper, the steel AISI 1045 was examined and the tensile tests of smooth and notched cylindrical bars were conducted together with biaxial testing of the notched tube specimens to calibrate material constants of selected phenomenological ductile fracture models. These were implemented into the Abaqus/Explicit through user subroutine VUMAT and used for cutting process simulation. As the calibration process is based on variables which cannot be obtained directly from experiments, numerical simulations of fracture tests are inevitable part of the calibration. Finally, experiments regarding the cutting process were carried out and predictive capability of selected fracture models is discussed. Concluding remarks then make the summary of gained experience both with the calibration and application of particular ductile fracture criteria.

Keywords: ductile fracture, phenomenological criteria, cutting process, explicit formulation, AISI 1045 steel

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Authors: Hironori Karachi, Haruka Yamashita

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

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

Procedia PDF Downloads 131

Authors: J. Ritonja

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Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification

Procedia PDF Downloads 248

Authors: PB Venkataraman

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Most of the real-life problems are ill-structured. They do not have a single solution but many competing solutions. The solution paths are non-linear and ambiguous, and the problem definition itself is many times a challenge. Students of professional education learn to solve such problems through internships. The current pandemic situation has constrained on-site internship opportunities; thus the students have no option but to pursue this learning online. This research assessed the learning gain of four undergraduate students in engineering as they undertook an online internship in an organisation over a period of eight weeks. A clinical interview at the end of the internship provided the primary data to assess the team’s problem-solving skills using a tested rubric. In addition to this, change in their learning attitudes were assessed through a pre-post study using a repurposed CLASS instrument for Electrical Engineering. Analysis of CLASS data indicated a shift in the sophistication of their learning attitude. A learning engagement survey adopting a 6-point Likert scale showed active participation and motivation in learning. We hope this new research will stimulate educators to exploit online internships even beyond the time of pandemic as more and more business operations are transforming into virtual.

Keywords: ill-structured problems, learning attitudes, internship, assessment, student engagement

Procedia PDF Downloads 201

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

Procedia PDF Downloads 112

Authors: Afifa Aslam, Muhammad Ibrahim, Abid Mahmood, Muhammad Usman Alvi, Fariha Jabeen, Umara Tabassum

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Many factors cause air pollution in Pakistan, which poses a significant threat to human health. Diesel fuel and gasoline motor vehicles, as well as industrial companies, pollute the air in Pakistan's cities. The study's goal is to determine the level of air pollution in a Pakistani industrial city and to establish risk levels for the health of the population. We measured the intensity of air pollution by chemical characterization and examination of air samples collected at stationary remark sites. The PM10 levels observed at all sampling sites, including residential, commercial, high-traffic, and industrial areas were well above the limits imposed by Pakistan EPA, the United States EPA, and WHO. We assessed the health risk via chemical factors using a methodology approved for risk assessment. All Igeo index values greater than one were considered moderately contaminated or moderately to severely contaminated. Heavy metals have a substantial risk of acute adverse effects. In Faisalabad, Pakistan, there was an enormously high risk of chronic effects produced by a heavy metal acquaintance. Concerning specified toxic metals, intolerable levels of carcinogenic risks have been determined for the entire population. As a result, in most of the investigated areas of Faisalabad, the indices and hazard quotients for chronic and acute exposure exceeded the permissible level of 1.0. In the current study, re-suspended roadside mineral dust, anthropogenic exhaust emissions from traffic and industry, and industrial dust were identified as major emission sources of elemental particulate contents. Because of the unacceptable levels of risk in the research area, it is strongly suggested that a comprehensive study of the population's health status as a result of air pollution should be conducted for policies to be developed against these risks.

Keywords: elemental composition, particulate pollution, Igeo index, health risk assessment, hazard quotient

Procedia PDF Downloads 91

Authors: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

Procedia PDF Downloads 165

Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

Procedia PDF Downloads 112

Authors: Kaushal Jha

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India is one of the major producers of pineapple contributing a significant part in terms of total world production of pineapple. It has spread throughout tropical and subtropical regions as a commercial fruit crop. In India, the cultivation of pineapple is confined to high rainfall and humid coastal region in the peninsular India and hilly areas of Northeastern region of India. Nagaland, one of the potential states of North-East India is basically an agrarian state having been endowed with favourable agro climatic conditions and a rich bio-diversity of flora and fauna. Agriculture contributes significantly to the state’s economy. Pineapple is an important fruit crop grown in Nagaland and has a very high potential for doubling the income of farmers in comparison to the traditional practices of rice cultivation. This requires improved farm management practices as well as a genre of entrepreneurial intentions and capabilities. The present study aimed at analysing the dimensions of entrepreneurial skill development among the pineapple growers of Nagaland. Medziphema block under Dimapur district is considered as the pineapple valley of Nagaland. Pineapple grown in this area is considered as one of the best in Nagaland in terms of its sweetness as well as quality. A multistage sampling was undertaken for conducting the present study. Medziphema rural development block was selected purposively for this purpose. The sample was drawn from three leading pineapple producing villages under Medziphema block. The respondents were selected based on random sampling procedure. Data were collected from the respondents using a pre-tested structured schedule. Major findings revealed that entrepreneurial skill development was one of the important factors to augment the increase in the sustained flow of income among the target farmers. Development of farm leadership, improving self esteem, innovativeness, economic motivation, orientation towards management of farm resources and value addition were identified as important dimensions for promoting entrepreneurial skill development and bringing prosperity to the farmers.

Keywords: skill development, entrepreneurial attributes, pineapple growers, Nagaland

Procedia PDF Downloads 162

Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

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In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: M. Aladwani, Y. Alarfaj

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The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: BIM, digital construction, construction technologies, digital transformation

Procedia PDF Downloads 86

Authors: Fernando Augusto Ullmann Tobe, Moacyr Amaral Domingues, Figueiredo, Stephany Rie Yamamoto Gushiken

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The purpose of this paper is to present the process of elaborating the layout of an assembly line of a welding industry using the principles of lean manufacturing as the main driver. The objective of this paper is relevant since the current layout of the assembly line causes non-productive times for operators, being related to the lean waste of unnecessary movements. The methodology used for the project development was Project-based Learning (PBL), which is an active way of learning focused on real problems. The process of selecting the methodology for layout planning was developed considering three criteria to evaluate the most relevant one for this paper's goal. As a result of this evaluation, Systematic Layout Planning was selected, and three steps were added to it – Value Stream Mapping for the current situation and after layout changed and the definition of lean tools and layout type. This inclusion was to consider lean manufacturing in the layout redesign of the industry. The layout change resulted in an increase in the value-adding time of operations carried out in the sector, reduction in movement times between previous and final assemblies, and in cost savings regarding the man-hour value of the employees, which can be invested in productive hours instead of movement times.

Keywords: assembly line, layout, lean manufacturing, systematic layout planning

Procedia PDF Downloads 227

Authors: Ozcan B., Koca B., Tuzcuoglu E., Cavusoglu S., Efe A., Bayraktar S.

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A washing machine is mainly used for removing any types of dirt and stains and also eliminating malodorous substances from textile surfaces. Stains originate from various sources from the human body to environmental contamination. Therefore, there are various methods for removing them. They are roughly classified into four different groups: oily (greasy) stains, particulate stains, enzymatic stains and bleachable (oxidizable) stains. Oily stains on clothes surfaces are a common result of being in contact with organic substances of the human body (e.g. perspiration, skin shedding and sebum) or by being exposed to an oily environmental pollutant (e.g. oily foods). Studies showed that human sebum is major component of oily soil found on the garments, and if it is aged under the several environmental conditions, it can generate obstacle yellow stains on the textile surface. In this study, a parametric study was carried out to investigate the key factors affecting the cleaning performance (specifically sebum removal performance) of a washing machine. These parameters are mechanical agitation percentage of tumble, consumed water and total washing period. A full factorial design of the experiment is used to capture all the possible parametric interactions using Minitab 2021 statistical program. Tests are carried out with commercial liquid detergent and 2 different types of sebum-soiled cotton and cotton + polyester fabrics. Parametric results revealed that for both test samples, increasing the washing time and the mechanical agitation could lead to a much better removal result of sebum. However, for each sample, the water amount had different outcomes. Increasing the water amount decreases the performance of cotton + polyester fabrics, while it is favorable for cotton fabric. Besides this, it was also discovered that the type of textile can greatly affect the sebum removal performance. Results showed that cotton + polyester fabrics are much easier to clean compared to cotton fabric

Keywords: laundry, washing machine, low-temperature washing, cold wash, washing efficiency index, sustainability, cleaning performance, stain removal, oily soil, sebum, yellowing

Procedia PDF Downloads 143

Authors: Sara Rankohi, Lloyd Waugh

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Construction sites are information saturated. Digitalization is hitting construction sites to meet the incredible demand of knowledge sharing and information documentations. From flying drones, 3D Lasers scanners, pocket mobile applications, to augmented reality glasses and smart helmet, visualization technologies help real-time information imposed straight onto construction professional’s field of vision. Although these technologies are very applicable and can have the direct impact on project cost and productivity, experience shows that only a minority of construction professionals quickly adapt themselves to benefit from them in practice. The majority of construction managers still tend to apply traditional construction management methods. This paper investigates a) current applications of visualization technologies in construction projects management, b) the direct effect of these technologies on productivity improvement and cost saving of a multi-residential building project via a case study on Mac Taggart Senior Care project located in Edmonton, Alberta. The research shows the imaged based technologies have a direct impact on improving project productivity and cost savings.

Keywords: image-based technologies, project management, cost, productivity improvement

Procedia PDF Downloads 361

Authors: Ghada Badr, Arwa Alturki

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The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: alignment, RNA secondary structure, pairwise, component-based, data mining

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Authors: Claudia L. Bianchi, Giuseppina Cerrato, Federico Galli, Federica Minozzi, Valentino Capucci

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At the beginning of the industrial productions, porcelain gres tiles were considered as just a technical material, aesthetically not very beautiful. Today thanks to new industrial production methods, both properties, and beauty of these materials completely fit the market requests. In particular, the possibility to prepare slabs of large sizes is the new frontier of building materials. Beside these noteworthy architectural features, new surface properties have been introduced in the last generation of these materials. In particular, deposition of TiO₂ transforms the traditional ceramic into a photocatalytic eco-active material able to reduce polluting molecules present in air and water, to eliminate bacteria and to reduce the surface dirt thanks to the self-cleaning property. The problem of photocatalytic materials resides in the fact that it is necessary a UV light source to activate the oxidation processes on the surface of the material, processes that are turned off inexorably when the material is illuminated by LED lights and, even more so, when we are in darkness. First, it was necessary a thorough study change the existing plants to deposit the photocatalyst very evenly and this has been done thanks to the advent of digital printing and the development of an ink custom-made that stabilizes the powdered TiO₂ in its formulation. In addition, the commercial TiO₂, which is used for the traditional photocatalytic coating, has been doped with metals in order to activate it even in the visible region and thus in the presence of sunlight or LED. Thanks to this active coating, ceramic slabs are able to purify air eliminating odors and VOCs, and also can be cleaned with very soft detergents due to the self-cleaning properties given by the TiO₂ present at the ceramic surface. Moreover, the presence of dopant metals (patent WO2016157155) also allows the material to work as well as antibacterial in the dark, by eliminating one of the negative features of photocatalytic building materials that have so far limited its use on a large scale. Considering that we are constantly in contact with bacteria, some of which are dangerous for health. Active tiles are 99,99% efficient on all bacteria, from the most common such as Escherichia coli to the most dangerous such as Staphilococcus aureus Methicillin-resistant (MRSA). DIGITALIFE project LIFE13 ENV/IT/000140 – award for best project of October 2017.

Keywords: Ag-doped microsized TiO₂, eco-active ceramic, photocatalysis, digital coating

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Francisco Toledo-Castillo, Pilar Peiró-Torres, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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The communication presented is about tasks that are been developed in the research project “safeRoute”, “Information safety system for professional road driving” (IPT-2012-110-370000). This R&D project was proposed by the consortium formed by Fagor Electronica la SEU 3 and the University of Valencia to the Ministry of Economy and Competitiveness, which approved it inside the INNPACTO subprogramme grants. Through this type of calls, the Ministry promote the innovative capacity of the Spanish companies and turn on the mechanism for competing internationally. With this kind of calls, private investments for technological and industrial development join their R & D resources with public entities to implement innovative project that could have an international exposure. Thus INNPACTO subprogramme promotes the creation of research projects with public-private partnerships that create exploitable final products. The “safeRoute” Project pretends develop a tool to help to make more safety the travels of commercial transport vehicles of goods and passengers. To achieve its objectives, the project is focused in three main lines of research: vehicle safety, the safety of the roads that they are using, and the safety which drivers do their job, their behaviour while they are driving. To improve safety, the project gives information about these three factors to all people that are involved in the safety of the professional transport. These three factors have influence to the occurrence of traffic accidents, thanks to the information provided and treated about these factors, we can achieve a significant reduction in occupational accidents in the transport sector. SafeRoute provide information about routes, vehicles, and driver behaviours, and in this manner pretends provide to transport companies a tool which could result in a safer driving results and could reduce their costs related to traffic accidents of their vehicles, in that way, this tool could help them to be more competitive, and give a more reliable service. This paper will focus mainly on the information about routes that drivers use to travel in their professional work, and how the researchers of this project have catalogued and evaluated these routes, and finally how that information will be provided to users.

Keywords: driver support systems, professional drivers, road safety, safeRoute

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Authors: Mekonen Hailu, Liu Liping

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Cage aquaculture is highly preferred due to higher production per unit volume of water, lower costs of investment, and simpler routine farm management procedures compared to pond systems. In the 1980s, cage culture was first used on a trial basis in sub-Saharan Africa. Over the past 20 years, a small number of prosperous freshwater cage culture operations have started to emerge in Egypt, Rwanda, Kenya, Uganda, Tanzania, Ghana, Malawi, Zambia and Zimbabwe. Brackish and marine cage culture also offers a lot of potential, although this subsector hasn't seen any significant commercial growth to date. In 2019, 263 cage aquaculture installations on the African inland waters on 18 water bodies within eight countries with an estimated 20,114 cages were reported. The lakes Victoria, Kariba, Volta, and River Volta, which together account for 82.9% of all cage aquaculture installations regarded as sub-Saharan Africa's principal cage aquaculture regions (Fig 1). Except few small-scale trials with North African catfish (Clarias gariepinus), almost all farms in Sub-Saharan Africa and Egypt grow Nile tilapia (Oreochromis niloticus). More than 247,398 tonnes of fish are produced yearly from ten African countries through cage aquaculture. The expansion of cage culture in Africa provides job opportunities for both skilled and unskilled workers, nutritious food and foreign currency. The escaping non-native strains of tilapia in Lake Volta and the occurrence of a risky Tilapia lake virus (syncytial hepatitis), which has the potential to wipe out entire populations in both wild and farmed Nile tilapia on Lake Victoria, are threats coming with the expansion of cage aquaculture in Africa. In addition, the installations of 138 cage aquacultures were found in contrary to best cage culture practices. To sustain cage aquaculture development and maintain harmony with other water uses, developers must strictly abide by best practices. Hence, the exclusion of protected areas and small lakes (average depth 5 m or less) should be done, as well an Environmental Impact Assessment should be conducted before establishing the cage farms.

Keywords: Africa, cage aquaculture, production, threats

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: N. Khiati

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The present paper attempts to report on some findings that emerged out of a larger scale doctorate research into English language needs of a renowned Algerian company of Hydrocarbon industry. From a multifaceted English for specific purposes (ESP) research perspective, the paper considers the English needs of the finance/legal department staff in the midst of the conflicting needs perspectives involving both objective needs indicators (i.e., the pressure of globalised business) and the general negative attitudes among the administrative -mainly jurists- staff towards English (favouring a non-adaptation strategy). The researcher’s unearthing of the latter’s needs is an endeavour to concretise the concepts of unmet, or unconscious needs, among others. This is why, these initially uncovered hidden needs will be detailed questioning educational background, namely previous language of instruction; training experiences and expectations; as well as the actual communicative practices derived from the retrospective interviews and preliminary quantitative data of the questionnaire. Based on these rough clues suggesting real needs, the researcher will tentatively propose some implications for both pre-service and in-service training organisers as well as for educational policy makers in favour of an English course in legal English for the jurists mainly from pre-graduate phases to in-service training.

Keywords: English for specific purposes (ESP), legal and finance staff, needs analysis, unmet/unconscious needs, training implications

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Authors: M. Orefice, V. Di Vito

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This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: ADS-B Based Application, Collision Avoidance, RPAS, Spiral Geometry.

Procedia PDF Downloads 242