Search results for: scientific data mining

Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

Abstract:

Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

Procedia PDF Downloads 99

Authors: Rishi Agarwal

Abstract:

Digital twins are emerging as a strong technology used to imitate and monitor physical objects digitally in real time across sectors. It is not only dealing with the digital space, but it is also actuating responses in the physical space in response to the digital space processing like storage, modeling, learning, simulation, and prediction. This paper explores the application of digital twins for enhancing physical security in retail stores. The retail sector still relies on outdated physical security practices like manual monitoring and metal detectors, which are insufficient for modern needs. There is a lack of real-time data and system integration, leading to ineffective emergency response and preventative measures. As retail automation increases, new digital frameworks must control safety without human intervention. To address this, the paper proposes implementing an intelligent digital twin framework. This collects diverse data streams from in-store sensors, surveillance, external sources, and customer devices and then Advanced analytics and simulations enable real-time monitoring, incident prediction, automated emergency procedures, and stakeholder coordination. Overall, the digital twin improves physical security through automation, adaptability, and comprehensive data sharing. The paper also analyzes the pros and cons of implementation of this technology through an Emerging Technology Analysis Canvas that analyzes different aspects of this technology through both narrow and wide lenses to help decision makers in their decision of implementing this technology. On a broader scale, this showcases the value of digital twins in transforming legacy systems across sectors and how data sharing can create a safer world for both retail store customers and owners.

Keywords: digital twin, retail store safety, digital twin in retail, digital twin for physical safety

Procedia PDF Downloads 75

Authors: Eleonora Sofilda, Ria Amalia, Muhammad Zilal Hamzah

Abstract:

Foreign direct investment is one of the sources of financing or capital that important for a country, especially for developing countries. This investment also provides a great contribution to development through the transfer of assets, management improving, and transfer of technology in enhancing the economy of a country. In the other side currently in ASEAN countries emerge the interesting phenomenon where some big producers are re-locate their basic production among those countries. This research is aimed to analyze the factors that affect capital inflows of foreign direct investment into the 6 ASEAN countries (Indonesia, Malaysia, Singapore, Thailand, Philippines, and Vietnam) in period 2004-2012. This study uses panel data analysis to determine the factors that affect of foreign direct investment in 6 ASEAN. The factors that affect of foreign direct investment (FDI) are the gross domestic product (GDP), global competitiveness (GCI), interest rate, exchange rate and trade openness (TO). Result of panel data analysis show that three independent variables (GCI, GDP, and TO) have a significant effect to the FDI in 6 ASEAN Countries.

Keywords: foreign direct investment, the gross domestic product, global competitiveness, interest rate, exchange rate, trade openness, panel data analysis

Procedia PDF Downloads 477

Authors: Amit Kaushik

Abstract:

Equus kiang kiang is an indigenous large-bodied herbivore species, and in India, it is restricted to limited geographies of Ladakh. One of such areas is the Tsokar Basin. With the rise in global pashmina demand, the livestock numbers have grown significantly. Previous studies have reported conflict between a nomadic pastoral community, the Changpas, and kiang. Absentee pastoralism (in lieu of pure pastoralism) and tourism are two major economic activities among the local people. However, the social, economic, political, and ecological changes are inevitable in such a contemporary system. The study examines several factors influencing the local pastoral economy and focuses on the presence of two non-human cohabitants, kiang, and the wolf. This study used semi-structured interviews and vehicle count method in four different seasons. The results show that people perceived kiang as a threat but also reveal a level of tolerance towards them. The locals predicted high kiang numbers ranging from 200-3000 in the basin and contrastingly ranked them behind wolves, which are very few in numbers. Due to a lack of scientific pieces of evidence, the kiang population status remains obscure, and local peoples’ concerns remain unaddressed. But how this competitive dysfunctionality does take place? On one side, the rural development or the animal husbandry department aims at developing the area by providing stall-feed and tourism, whereas, on another side, the wildlife department emphasizes wildlife conservation. Therefore, the managers and planners may need to be cautious about the local socio-ecological complexities and may require inter-departmental communications. The study concludes that an interdisciplinary inquiry may be an important tool in understanding such a precarious situation and may be used in the policy-making processes.

Keywords: coexistence, human-livestock-wildlife interactions, interdisciplinary approach, kiang, policymaking, tsokar.

Procedia PDF Downloads 143

Authors: Alonge Isaac Olusola

Abstract:

Taking a cue from countries such as China and Japan, there is no doubt that the teaching and learning of Mother Tongue ( MT) or Language of Immediate Environment (LIE) is a potential source of development in every country. The engine of economic, scientific, technological and political advancement would be more functional when the language of instruction for teaching and learning in schools is in the child’s mother tongue. The purpose of this paper therefore, is to delve into the genesis of the official recognition given to the teaching and learning of Nigerian languages at national level with special focus on Yoruba language. Yoruba language and other Nigerian languages were placed on a national pedestal by a Nigerian Educational Minister, Late Professor Babatunde Fafunwa, who served under the government of General Ibrahim Babangida (1985 – 1993). Through his laudable effort, the teaching and learning of Nigerian languages in schools all over the nation was incorporated officially in the national policy of education. Among all the Nigerian languages, Hausa, Igbo and Yoruba were given foremost priorities because of the large population of their speakers. Since the Fafunwa era, Yoruba language has become a national subject taught in primary, secondary and tertiary institutions in Nigeria. However, like every new policy, its implementation has suffered several forms of criticisms and impediments from governments, policy makers, curriculum developers, school administrators, teachers and learners. This paper has been able to arrive at certain findings through oral interviews, questionnaires and evaluation of pupils/students enrolment and performances in Yoruba language with special focus on the South-west and North central regions of Nigeria. From the research carried out, some factors have been found to be responsible for the successful implementation or otherwise of Yoruba language instruction policy in some schools, colleges and higher institutions in Nigeria. In conclusion, the paper made recommendations on how the National Policy of Education would be implemented to enhance the teaching and learning of Yoruba language in all Nigerian schools.

Keywords: language of immediate environment, mother tongue, national policy of education, yoruba language

Procedia PDF Downloads 538

Authors: Jakkireddy Sravani

Abstract:

Introduction: The maintenance of hemodynamic stability is of pivotal importance in supratentorial surgeries. Anesthesia for supratentorial tumors requires an understanding of localized or generalized rising ICP, regulation, and maintenance of intracerebral perfusion, and avoidance of secondary systemic ischemic insults. We aimed to compare the effects of the combination of ketamine and propofol with propofol alone when used as an induction and maintenance anesthetic agent during supratentorial tumors. Methodology: This prospective, randomized, double-blinded controlled study was conducted at AIIMS Raipur after obtaining the institute Ethics Committee approval (1212/IEC-AIIMSRPR/2022 dated 15/10/2022), CTRI/2023/01/049298 registration and written informed consent. Fifty-two supratentorial tumor patients posted for craniotomy and excision were included in the study. The patients were randomized into two groups. One group received a combination of ketamine and propofol, and the other group received propofol for induction and maintenance of anesthesia. Intraoperative hemodynamic stability and quality of brain relaxation were studied in both groups. Statistical analysis and technique: An MS Excel spreadsheet program was used to code and record the data. Data analysis was done using IBM Corp SPSS v23. The independent sample "t" test was applied for continuously dispersed data when two groups were compared, the chi-square test for categorical data, and the Wilcoxon test for not normally distributed data. Results: The patients were comparable in terms of demographic profile, duration of the surgery, and intraoperative input-output status. The trends in BIS over time were similar between the two groups (p-value = 1.00). Intraoperative hemodynamics (SBP, DBP, MAP) were better maintained in the ketamine and propofol combination group during induction and maintenance (p-value < 0.01). The quality of brain relaxation was comparable between the two groups (p-value = 0.364). Conclusion: Ketamine and propofol combination for the induction and maintenance of anesthesia was associated with superior hemodynamic stability, required fewer vasopressors during excision of supratentorial tumors, provided adequate brain relaxation, and some degree of neuroprotection compared to propofol alone.

Keywords: supratentorial tumors, hemodynamic stability, brain relaxation, ketamine, propofol

Procedia PDF Downloads 33

Authors: Mariana Roberta Ribeiro, Isabela de Cássia Caramello, Roberto Saverio Souza Costa

Abstract:

Currently, one of the most important environmental problems is soil degradation. This wear is the result of inadequate agricultural practices, with water erosion as the main agent. As the runoff water is concentrated in certain points, it can reach a more advanced stage, which are the gullies. In view of this, the objective of this work was to evaluate which methodology is most suitable for the purpose of elaborating a project for the recovery of a gully, relating work time, data reliability, and the final cost. The work was carried out on a rural road in Monte Alto - SP, where there is 0.30 hectares of area under the influence of a gully. For the evaluation, an aerophotogrammetric survey was used with RPA, with georeferenced points, and with a GNSS L1/L2 receiver. To assess the importance of georeferenced points, there was a comparison of altimetric data using the support points with altimetric data using only the aircraft's internal GPS. Another method used was the survey by conventional topography, where coordinates were collected by total station and L1/L2 Geodetic GPS receiver. Statistical analysis was performed using analysis of variance (ANOVA) using the F test (p<0.05), and the means between treatments were compared using the Tukey test (p<0.05). The results showed that the surveys carried out by aerial photogrammetry and by conventional topography showed no significant difference for the analyzed parameters. Considering the data presented, it is possible to conclude that, when comparing the parameters of accuracy, the final volume of the gully, and cost, for the purpose of elaborating a project for the recovery of a gully, the methodologies of aerial photogrammetric survey and conventional topography do not differ significantly. However, when working time, use of labor, and project detail are compared, the aerial photogrammetric survey proves to be more viable.

Keywords: drones, erosion, soil conservation, technology in agriculture

Procedia PDF Downloads 119

Authors: A. J. Regan, F. J. Lidgey, M. Betteridge, P. Georgiou, C. Toumazou, K. Hayatleh, J. R. Dibble

Abstract:

Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-of-sample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.

Keywords: financial algorithm, GPU, S&P 500, stock market prediction

Procedia PDF Downloads 352

Authors: Salwa Aftab, Sehrish Riaz

Abstract:

The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression

Procedia PDF Downloads 406

Authors: Yue Huang, Yiheng Feng

Abstract:

Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

Procedia PDF Downloads 97

Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

Abstract:

For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

Procedia PDF Downloads 265

Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

Abstract:

The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1^st, 2008 and December 31^st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2^nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: mortality map, spatial patterns, statistical area, variation

Procedia PDF Downloads 262

Authors: Bruk Gebregziabher

Abstract:

The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

Procedia PDF Downloads 87

Authors: Yehya Elsayed, Sarah Dalibalta, Fareedah Alqtaishat, Ioline Gomes, Nagelle Fernandes

Abstract:

Bakhour or Arabian incense is traditionally used to perfume houses, shops and clothing as part of cultural or religious practices in several Middle Eastern countries. Conventionally, Bakhour consists of a mixture of natural ingredients such as chips of agarwood (oud), musk and sandalwoods that are soaked in scented oil. Bakhour is usually burned by charcoal or by using gas or electric burners to produce the scented smoke. It is necessary to evaluate the impact of such practice on human health and environment especially that the burning of Bakhour is usually done on a regular basis and in closed areas without proper ventilation. Although significant amount of research has been reported in scientific literature on the chemical analysis of various types of incense smoke, unfortunately only very few of them focused specifically on the health impacts of Bakhour. Raw Bakhour samples, their smoke emissions and the ash residue were analyzed to assess the existence of toxic ingredients and their possible influence on health and the environment. Three brands of Bakhour samples were analyzed for the presence of harmful heavy metals and organic compounds. Thermal Desorption Gas Chromatography-Mass Spectrometry (TD-GC-MS) was used to identify organic compounds while Inductively Coupled Plasma (ICP) and Scanning Electron Microscope-Energy Dispersive X-Ray Spectrometer (SEM-EDS) were used to analyze the presence of toxic and heavy metals. Organic compounds from the smoke were collected on specific tenax and activated carbon adsorption tubes. More than 850 chemical compounds were identified. The presence of 19 carcinogens, 23 toxins and 173 irritants were confirmed. Additionally, heavy metals were detected in amounts similar to those present in cigarettes. However, it was noticed that many of the detected compounds in the smoke lacked clinical studies on their health effects which shows the need for further clinical studies to be devoted to this area of study.

Keywords: Bakhour, incense smoke, pollution, indoor environment, health risk, chemical analysis

Procedia PDF Downloads 432

Authors: Yehya Elsayed, Sarah Dalibalta, Fareedah Alqtaishat, Ioline Gomes, Nagelle Fernandes

Abstract:

Bakhour, or Arabian incense, is traditionally used to perfume houses, shops and clothing as part of cultural or religious practices in several Middle Eastern countries. Conventionally, Bakhour consists of a mixture of natural ingredients such as chips of agarwood (oud), musk and sandalwoods that are soaked in scented oil. Bakhour is usually burned by charcoal or by using gas or electric burners to produce the scented smoke. It is necessary to evaluate the impact of such practice on human health and environment especially that the burning of Bakhour is usually done on a regular basis and in closed areas without proper ventilation. Although significant amount of research has been reported in scientific literature on the chemical analysis of various types of incense smoke, unfortunately, only very few of them focused specifically on the health impacts of Bakhour. Raw Bakhour samples, their smoke emissions and the ash residue were analyzed to assess the existence of toxic ingredients and their possible influence on health and the environment. Three brands of Bakhour samples were analyzed for the presence of harmful heavy metals and organic compounds. Thermal Desorption Gas Chromatography-Mass Spectrometry (TD-GC-MS) was used to identify organic compounds while Inductively Coupled Plasma (ICP) and Scanning Electron Microscope-Energy Dispersive X-Ray Spectrometer (SEM-EDS) were used to analyze the presence of toxic and heavy metals.. Organic compounds from the smoke were collected on specific tenax and activated carbon adsorption tubes. More than 850 chemical compounds were identified. The presence of 19 carcinogens, 23 toxins, and 173 irritants were confirmed. Additionally, heavy metals were detected in amounts similar to those present in cigarettes. However, it was noticed that many of the detected compounds in the smoke lacked clinical studies on their health effects which shows the need for further clinical studies to be devoted to this area of study.

Keywords: bakhour, incense smoke, pollution, indoor environment, health risk, chemical analysis

Procedia PDF Downloads 298

Authors: Sogand Barghi

Abstract:

The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

Procedia PDF Downloads 77

Authors: H. Yousefnia, S. Zolghadri

Abstract:

The measurement of organ radiation exposure dose is one of the most important steps to be taken initially, for developing a new radiopharmaceutical. In this study, the dosimetric studies of a novel agent for SPECT-imaging of the bone metastasis, 111In-1,4,7,10-tetraazacyclododecane-1,4,7,10 tetraethylene phosphonic acid (111In-DOTMP) complex, have been carried out to estimate the dose in human organs based on the data derived from rats. The radiolabeled complex was prepared with high radiochemical purity in the optimal conditions. Biodistribution studies of the complex was investigated in the male Syrian rats at selected times after injection (2, 4, 24 and 48 h). The human absorbed dose estimation of the complex was made based on data derived from the rats by the radiation absorbed dose assessment resource (RADAR) method. 111In-DOTMP complex was prepared with high radiochemical purity of >99% (ITLC). Total body effective absorbed dose for 111In-DOTMP was 0.061 mSv/MBq. This value is comparable to the other 111In clinically used complexes. The results show that the dose with respect to the critical organs is satisfactory within the acceptable range for diagnostic nuclear medicine procedures. Generally, 111In-DOTMP has interesting characteristics and can be considered as a viable agent for SPECT-imaging of the bone metastasis in the near future.

Keywords: In-111, DOTMP, Internal Dosimetry, RADAR

Procedia PDF Downloads 409

Authors: Ana Lucia Molina

Abstract:

Introduction: Fine motor skills refer to the use of the hands and coordination of the small muscles that control the fingers. A deficiency in fine motor skills is as important as a change in global movements, as fine motor skills directly affect activities of daily living. Fine movements are involved in some functions, such as motor control of the extremities, sensitivity, strength and tonus of the hands. A growing interest in the effects of non-invasive neuromodulation, such as transcranial stimulation technologies, through transcranial magnetic stimulation (TMS), has been observed in the scientific literature, with promising results in fine motor rehabilitation, as it provides modulation of the corresponding cortical activity in the area primary motor skills of the hands in both hemispheres (according to the International System 10-20, corresponding to C3 and C4). Objectives: to carry out a literature review about the effects of TMS on the cortical motor area corresponding to hand motricity. Methodology: This is a bibliographic survey carried out between October 2022 and March 2023 at Pubmed, Google Scholar, Lillacs and Virtual Health Library (BVS), with a national and international database. Some books on neuromodulation were included. Results: 28 articles and 5 books were initially found, and after reading the abstracts, only 14 articles and 3 books were selected, with publication dates between 2008 and 2022, to compose the literature review since it suited the purpose of this study. Conclusion: TMS has shown promising results in the treatment of fine motor rehabilitation, such as improving coordination, muscle strength and range of motion of the hands, being a complementary technique to existing treatments and thus providing more potent results for manual skills in activities of daily living. It is important to emphasize the need for more specific studies on the application of TMS for the treatment of manual disorders, which describe the uniqueness of each movement.

Keywords: transcranial magnetic stimulation, fine motor skills, motor rehabilitation, non-invasive neuromodulation

Procedia PDF Downloads 76

Authors: Slavica P. Petrovic

Abstract:

One of the key dimensions of management problems in organizations refers to the relations between stakeholders. The management problems that are characterized by conflict and coercion, in which participants do not agree on the ends and means, in which different groups, i.e., individuals, strive to – using the power they have – impose on others their favoured strategy and decisions represent the relevant research subject. Creatively managing the coercive problems in organizations, in which the sources of power can be identified, implies the emancipatory paradigm and the use of corresponding systems methodology. The main research aim is to critically reassess the theoretical foundations and methodological and methodical development of Critical Systems Heuristics (CSH) – as a valid representative of the emancipatory paradigm – in order to determine the conditions, ways, and achievements of its application in managing the coercive problems in organizations. The basic hypothesis is that CSH, as the emancipatory methodology, given its own theoretical foundations and methodological-methodical development, can be employed in a scientifically based and practically useful manner in creative addressing the coercive problems. The scientific instrumentarium corresponding to this research aim is critical systems thinking with its three key commitments to: a) Critical awareness of the strengths and weaknesses of each research instrument (theory, methodology, method, technique, model) for structuring the problem situations in organizations, b) Improvement of managing the coercive problems in organizations, and c) Pluralism – respect the different perceptions and interpretations of problem situations, and enable the combined use of research instruments. The relevant research result is that CSH – considering its theoretical foundations, methodological and methodical development – enables to reveal the normative content of the proposed or existing designs of organizational systems. Accordingly, it can be concluded that through the use of critically heuristic categories and dialectical debate between those involved and those affected by the designs, but who are not included in designing organizational systems, CSH endeavours to – in the application – support the process of improving position of all stakeholders.

Keywords: coercion and conflict in organizations, creative management, critical systems heuristics, the emancipatory systems methodology

Procedia PDF Downloads 446

Authors: Mitra Saberi, Saeideh Fakhari, Amir Karam, Ali Ahmadabadi

Abstract:

Geomorphology is the scientific study of the characteristics of form and shape of the Earth's surface. The existence of types of landforms and their variation is mainly controlled by changes in the shape and position of land and topography. In fact, the interest and application of fractal issues in geomorphology is due to the fact that many geomorphic landforms have fractal structures and their formation and transformation can be explained by mathematical relations. The purpose of this study is to identify and analyze the fractal behavior of landforms of macro geomorphologic regions of Iran, as well as studying and analyzing topographic and landform characteristics based on fractal relationships. In this study, using the Iranian digital elevation model in the form of slopes, coefficients of deposition and alluvial fan, the fractal dimensions of the curves were calculated through the box counting method. The morphometric characteristics of the landforms and their fractal dimension were then calculated for 4criteria (height, slope, profile curvature and planimetric curvature) and indices (maximum, Average, standard deviation) using ArcMap software separately. After investigating their correlation with fractal dimension, two-way regression analysis was performed and the relationship between fractal dimension and morphometric characteristics of landforms was investigated. The results show that the fractal dimension in different pixels size of 30, 90 and 200m, topographic curves of different landform units of Iran including mountain, hill, plateau, plain of Iran, from1.06in alluvial fans to1.17in The mountains are different. Generally, for all pixels of different sizes, the fractal dimension is reduced from mountain to plain. The fractal dimension with the slope criterion and the standard deviation index has the highest correlation coefficient, with the curvature of the profile and the mean index has the lowest correlation coefficient, and as the pixels become larger, the correlation coefficient between the indices and the fractal dimension decreases.

Keywords: box counting method, fractal dimension, geomorphology, Iran, landform

Procedia PDF Downloads 90

Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen

Abstract:

The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate one-dimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.

Keywords: seismic data, Gokpinar Damp, urban planning, Denizli

Procedia PDF Downloads 292

Authors: Jingwei Du

Abstract:

The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

Procedia PDF Downloads 34

Authors: Arian Ebneyamini, Hoda Azimi, Jules Thibaults, F. Handan Tezel

Abstract:

In this study, a modification of Hennepe model for pervaporation separation of butanol from aqueous solutions using Polydimethylsiloxane (PDMS) mixed matrix membranes has been introduced and validated by experimental data. The model was compared to the original Hennepe model and few other models which are applicable for membrane gas separation processes such as Maxwell, Lewis Nielson and Pal. Theoretical modifications for non-ideal interface morphology have been offered to predict the permeability in case of interface void, interface rigidification and pore-blockage. The model was in a good agreement with experimental data.

Keywords: butanol, PDMS, modeling, pervaporation, mixed matrix membranes

Procedia PDF Downloads 224

Authors: Andreas Walmsley, Shobana Partington, Rebecca Armstrong, Harold Goodwin

Abstract:

In the UK, more than 1 in 5 workers earn less than a living wage. The hospitality sector is particularly affected where it has been claimed two thirds of workers earn less than the living wage. The UK Government is set to introduce (April 2016) a national living wage (NLW) which is therefore likely to have a significant impact on the hospitality sector. To date limited data exists that focus on how hotels are tackling the issue, what stakeholder perceptions are towards the change in legislation, and how the NLW may affect working patterns in the sector. This study draws on interviews with a range of key stakeholders such as hotel HR and general managers as well as industry representatives to explore these issues within the broader context of responsible tourism. Data collection is still ongoing and is scheduled to be completed by the end of June 2016.

Keywords: hospitality, living wage, responsible tourism, tourism employment

Procedia PDF Downloads 390

Authors: Aafaf El Jazouli, Ahmed Barakat, Rida Khellouk

Abstract:

Mapping of soil degradation is derived from field observations, laboratory measurements, and remote sensing data, integrated quantitative methods to map the spatial characteristics of soil properties at different spatial and temporal scales to provide up-to-date information on the field. Since soil salinity, texture and organic matter play a vital role in assessing topsoil characteristics and soil quality, remote sensing can be considered an effective method for studying these properties. The main objective of this research is to asses soil degradation by combining remote sensing data and laboratory analysis. In order to achieve this goal, the required study of soil samples was taken at 50 locations in the upper basin of Oum Er Rbia in the Middle Atlas in Morocco. These samples were dried, sieved to 2 mm and analyzed in the laboratory. Landsat 8 OLI imagery was analyzed using physical or empirical methods to derive soil properties. In addition, remote sensing can serve as a supporting data source. Deterministic potential (Spline and Inverse Distance weighting) and probabilistic interpolation methods (ordinary kriging and universal kriging) were used to produce maps of each grain size class and soil properties using GIS software. As a result, a correlation was found between soil texture and soil organic matter content. This approach developed in ongoing research will improve the prospects for the use of remote sensing data for mapping soil degradation in arid and semi-arid environments.

Keywords: Soil degradation, GIS, interpolation methods (spline, IDW, kriging), Landsat 8 OLI, Oum Er Rbia high basin

Procedia PDF Downloads 171

Authors: Arun Joshi

Abstract:

The present study deals with the report of Gangamopteriscyclopteroides from the Barakar Formation of Simlong Open Cast Mine, Rajmahal Area, Rajmahal Basin, Jharkhand, India. The genus Gangamopteriscomprises leaves which are simple, entire, symmetrical or asymmetrical, linear, lanceolate, elliptical, obovate in shape, apex broadly rounded, obtuse, acute, acuminate or mucronate, base petiolate or contracted, midrib absent. Median region occupied by subparallel veins with anastomoses of elongate or hexagonal outline. Secondary veins arise from median veins by repeated dichotomy, arched, bifurcating and anasotomosing network. The present work is significant as it represents the presence of Glossopteris flora (250- 290 ma) which is mainly responsible for the formation of coal. Coal is one of the major fuels for power production through thermal power plants. The Glossopteris flora is one of the major floras that occupied the southern continent during Carboniferous- Permian time. This southern continent is also known as Gondwana comprising Australia, South Africa, Antarctica, Madagascar and India. There is a vast geological reserve of coal with favorable stripping ratio available at the Simlong Block but the area comes under the most naxalite prone area and thus the mine has been running in an unplanned manner. It has got the potential of becoming a big project with higher capacity and is well suited for enhancing production which can be helpful in the economic growth of the country. Though, the present record is scanty, it shows the presence of Glossopteris flora responsible for the formation of coal in the Coalmine. However, there are fears of fossils disappearing from this area as the state government of Jharkhand has given out a mining lease in the area to private companies. Therefore, it is very necessary to study such coal forming vegetation and their systematic study from the area to generate a new palaeobotanical database, palaeoenvironmental interpretation, basinal correlation and for the understanding of evolutionary perspectives.

Keywords: Barakar formation, coal, Glossopteris flora, Gondwana, India, Naxalite, Rajmahal Basin

Procedia PDF Downloads 159

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 237

Authors: Oluwambe Akinmoye

Abstract:

The textile industry in Nigeria has grown rapidly, fueled by rising demand for fast fashion driven by celebrity culture, fashion TV, and the Internet. However, this growth has come at a cost, with the industry contributing to environmental degradation, waste management crises, economic imbalances, and social injustices. This paper examines the attitudes of consumers and designers toward sustainability in the Nigerian textile and fast fashion industry. The study adopts a mixed-methods research design. Both qualitative and quantitative data were drawn from fast fashion consumers and designers. The sample of consumers and designers was determined using random and purposive sampling techniques. Data were elicited from the consumers and designers using questionnaires and focus group discussions, respectively, coupled with comprehensive literature reviews. The collected data were analyzed using descriptive statistics, content, and thematic analyses. Findings indicate that the strata of Nigerian society pay little attention to fast fashion sustainability. Conversely, designers have started to innovate and adopt sustainable practices by sourcing eco-friendly materials, yet they face significant barriers. The study emphasizes the need for a shift in the industry's approach to sustainability, with a greater concern on circular economy principles, sustainable materials, and fair labour practices.

Keywords: Fast fashion, textiles, sustainability, Climate crises, consumers, designers

Procedia PDF Downloads 12

Authors: Frederic Henry-Couannier

Abstract:

Dark Gravity is a natural extension of general relativity in presence of a flat non dynamical background. Matter and radiation fields from its dark sector, as soon as their gravity dominates over our side fields gravity, produce a constant acceleration law of the scale factor. After a brief reminder of the Dark Gravity theory foundations, the confrontation with the main cosmological probes is carried out. We show that, amazingly, the sudden transition between the usual matter dominated decelerated expansion law a(t) ∝ t²/³ and this accelerated expansion law a(t) ∝ t² predicted by the theory should be able to fit the main cosmological probes (SN, BAO, CMB and age of the oldest stars data) but also direct H₀ measurements with two free parameters only: H₀ and the transition redshift.

Keywords: anti-gravity, negative energies, time reversal, field discontinuities, dark energy theory

Procedia PDF Downloads 63

Authors: D. Serero, L. Couton, J. D. Parisse, R. Leroy

Abstract:

In urban planning, an increasing number of cities require wind analysis to verify comfort of public spaces and around buildings. These studies are made using computer fluid dynamic simulation (CFD). However, this technique is often based on wind information taken from meteorological stations located at several kilometers of the spot of analysis. The approximated input data on project surroundings produces unprecise results for this type of analysis. They can only be used to get general behavior of wind in a zone but not to evaluate precise wind speed. This paper presents another approach to this problem, based on collecting wind data and generating an urban wind cartography using connected ultrasound anemometers. They are wireless devices that send immediate data on wind to a remote server. Assembled in array, these devices generate geo-localized data on wind such as speed, temperature, pressure and allow us to compare wind behavior on a specific site or building. These Netatmo-type anemometers communicate by wifi with central equipment, which shares data acquired by a wide variety of devices such as wind speed, indoor and outdoor temperature, rainfall, and sunshine. Beside its precision, this method extracts geo-localized data on any type of site that can be feedback looped in the architectural design of a building or a public place. Furthermore, this method allows a precise calibration of a virtual wind tunnel using numerical aeraulic simulations (like STAR CCM + software) and then to develop the complete volumetric model of wind behavior over a roof area or an entire city block. The paper showcases connected ultrasonic anemometers, which were implanted for an 18 months survey on four study sites in the Grand Paris region. This case study focuses on Paris as an urban environment with multiple historical layers whose diversity of typology and buildings allows considering different ways of capturing wind energy. The objective of this approach is to categorize the different types of wind in urban areas. This, particularly the identification of the minimum and maximum wind spectrum, helps define the choice and performance of wind energy capturing devices that could be implanted there. The localization on the roof of a building, the type of wind, the altimetry of the device in relation to the levels of the roofs, the potential nuisances generated. The method allows identifying the characteristics of wind turbines in order to maximize their performance in an urban site with turbulent wind.

Keywords: computer fluid dynamic simulation in urban environment, wind energy harvesting devices, net-zero energy building, urban wind behavior simulation, advanced building skin design methodology

Procedia PDF Downloads 107