Search results for: artificial oil bodies
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2875

Search results for: artificial oil bodies

925 Need for Shariah Screening of Companies in Nigeria: Lessons from Other Jurisdictions

Authors: Aishat Abdul-Qadir Zubair

Abstract:

Background: The absence of Shari’ah screening methodology for companies in Nigeria has further engineered the uncertainty surrounding the acceptability of investing in certain companies by people professing the religion of Islam due to the nature of the activities carried out by these companies. There are some existing shariah screening indices in other jurisdictions whose criteria can be used to check if a company or business is shariah-compliant or not. Examples such as FTSE, DJIM, Standard and Poor to mention just a few. What these indices have tried to do is to ensure that there are benchmarks to check with before investing in companies that carry out mixed activities in their business, wherein some are halal and others may be haram. Purpose: There have been numerous studies on the need to adopt certain screening methodologies as well as call for new methods in screening companies for shariah compliance in order to suit the investments needs of Muslims in other jurisdictions. It is, however, unclear how suitable these methodologies will be to Nigeria. This paper, therefore, seeks to address this gap to consider an appropriate screening methodology to be employed in Nigeria, drawing from the experience of other jurisdictions. Methods: This study employs a triangulation of both quantitative and qualitative methods to analyze the need for Shari’ah screening of companies in Nigeria. The qualitative method is used by way of ijtihad, and this study tries to apply some Islamic Principles of Maqasid al-shari’ah as well as Qawaid al-Fiqiyyah to analyze activities of companies in order to ensure that they are indeed Shari’ah compliant. In addition, using the quantitative data gathered from the interview survey, the perspective of the investors with regards to the need for Shari’ah screening of companies in Nigeria is further analyzed. Results: The result of the study shows that there is a lack of awareness from the teeming Muslim population in Nigeria on the need for Shari’ah screening of companies in Nigeria. The result further shows that there is the need to take into cognizance the peculiar nature of company activities in Nigeria before any particular Shari’ah screening methodology is adopted and setting the necessary benchmarks. Conclusion and Implications: The study concludes that there is the need to ensure that the conscious Muslims in Nigeria screen companies for Shari’ah compliance so that they can easily identify the companies to invest in. The paper, therefore, recommends that the Nigerian government need to come up with a screening methodology that will suit the peculiar nature of companies in Nigeria. The study thus has a direct implication on the Investment regulatory bodies in Nigeria such as the Securities and Exchange Commission (SEC), Central Bank of Nigeria (CBN) as well as the investor Muslims.

Keywords: Shari'ah screening, Muslims, investors, companies

Procedia PDF Downloads 152
924 Comparison of Yb and Tm-Fiber Laser Cutting Processes of Fiber Reinforced Plastics

Authors: Oktay Celenk, Ugur Karanfil, Iskender Demir, Samir Lamrini, Jorg Neumann, Arif Demir

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Due to its favourable material characteristics, fiber reinforced plastics are amongst the main topics of all actual lightweight construction megatrends. Especially in transportation trends ranging from aeronautics over the automotive industry to naval transportation (yachts, cruise liners) the expected economic and environmental impact is huge. In naval transportation components like yacht bodies, antenna masts, decorative structures like deck lamps, light houses and pool areas represent cheap and robust solutions. Commercially available laser tools like carbon dioxide gas lasers (CO₂), frequency tripled solid state UV lasers, and Neodymium-YAG (Nd:YAG) lasers can be used. These tools have emission wavelengths of 10 µm, 0.355 µm, and 1.064 µm, respectively. The scientific goal is first of all the generation of a parameter matrix for laser processing of each used material for a Tm-fiber laser system (wavelength 2 µm). These parameters are the heat affected zone, process gas pressure, work piece feed velocity, intensity, irradiation time etc. The results are compared with results obtained with well-known material processing lasers, such as a Yb-fiber lasers (wavelength 1 µm). Compared to the CO₂-laser, the Tm-laser offers essential advantages for future laser processes like cutting, welding, ablating for repair and drilling in composite part manufacturing (components of cruise liners, marine pipelines). Some of these are the possibility of beam delivery in a standard fused silica fiber which enables hand guided processing, eye safety which results from the wavelength, excellent beam quality and brilliance due to the fiber nature. There is one more feature that is economically absolutely important for boat, automotive and military projects manufacturing that the wavelength of 2 µm is highly absorbed by the plastic matrix and thus enables selective removal of it for repair procedures.

Keywords: Thulium (Tm) fiber laser, laser processing of fiber-reinforced plastics (FRP), composite, heat affected zone

Procedia PDF Downloads 181
923 The Trajectory of the Ball in Football Game

Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

Procedia PDF Downloads 445
922 Genetic Structure of Four Bovine Populations in the Philippines Using Microsatellites

Authors: Peter James C. Icalia, Agapita J. Salces, Loida Valenzuela, Kangseok Seo, Geronima Ludan

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This study evaluated polymorphism of 11 microsatellite markers in four local genetic groups of cattle. Batanes cattle which has never been studied using microsatellites is evaluated for its genetic distance from the Ilocos cattle while Brahman and Holstein-Sahiwal are also included as there were insemination programs by the government using these two breeds. PCR products that were genotyped for each marker were analyzed using POPGENEv32. Results showed that 55% (Fst=0.5501) of the genetic variation is due to the differences between populations while the remaining 45% is due to individual variation. The Fst value also indicates that there were very great differences from population to population using the range proposed by Sewall and Wright. The constructed phylogenetic tree based on Nei’s genetic distance using the modified neighboor joining procedure of PHYLIPv3.5 showed the admixture of Brahman and Holstein-Sahiwal having them grouped in the same clade. Batanes and Ilocos cattle were grouped in a different cluster showing that they have descended from a single parental population. This would presumably address the claim that Batanes and Ilocos cattle are genetically distant from other groups and still exist despite the artificial insemination program of the government using Brahman and other imported breeds. The knowledge about the genetic structure of this population supports the development of conservation programs for the smallholder farmers.

Keywords: microsatellites, cattle, Philippines, populations, genetic structure

Procedia PDF Downloads 495
921 An Entropy Stable Three Dimensional Ideal MHD Solver with Guaranteed Positive Pressure

Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

Procedia PDF Downloads 328
920 Heat Stress Adaptive Urban Design Intervention for Planned Residential Areas of Khulna City: Case Study of Sonadanga

Authors: Tanjil Sowgat, Shamim Kobir

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World is now experiencing the consequences of climate change such as increased heat stress due to high temperature rise. In the context of changing climate, this study intends to find out the planning interventions necessary to adapt to the current heat stress in the planned residential areas of Khulna city. To carry out the study Sonadanga residential area (phase I) of Khulna city has been taken as the study site. This residential neighbourhood covering an area of 30 acres has 206 residential plots. The study area comprises twelve access roads, one park, one playfield, one water body and two street furniture’s. This study conducts visual analysis covering green, open space, water body, footpath, drainage and street trees and furniture and questionnaire survey deals with socio-economic, housing tenancy, experience of heat stress and urban design interventions. It finds that the current state that accelerates the heat stress condition such as lack of street trees and inadequate shading, maximum uses are not within ten minutes walking distance, no footpath for the pedestrians and lack of well-maintained street furniture. It proposes that to adapt to the heat stress pedestrian facilities, buffer sidewalk with landscaping, street trees and open spaces, soft scape, natural and man-made water bodies, green roofing could be effective urban design interventions. There are evidences of limited number of heat stress adaptive planned residential area. Since current sub-division planning practice focuses on rigid land use allocation, it partly addresses the climatic concerns through creating open space and street trees. To better respond to adapt to the heat stress, urban design considerations in the context of sub-division practice would bring more benefits.

Keywords: climate change, urban design, adaptation, heat stress, water-logging

Procedia PDF Downloads 282
919 The Impact of Artificial Intelligence on Rural Life

Authors: Triza Edwar Fawzi Deif

Abstract:

In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

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918 The Post Thawing Quality of Boer Goat Semen after Freezing by Mr. Frosty System Using Commercial Diluter

Authors: Gatot Ciptadi, Mudawamah, R. P. Putra, S. Wahjuningsih, A. M. Munazaroh

Abstract:

The success rate of Artificial Insemination (AI) application, particularly in the field at the farmer level is highly dependent on the quality of the sperms one post thawing. The objective of this research was to determine the effect of freezing method (-1oC/ minute) using Mr. Frosty system with commercial diluents on the post-thawing quality of Boer goat semen. Method use is experimental design with the completely randomized design (CRD) with 4 treatments of commercial diluter percentage (v/v). Freezing semen was cryopreserved in 2 main final temperatures of –45 oC (Freezer) and –196 oC (liquid nitrogen). Result showed that different commercial diluter is influenced on viability motility and abnormalities of Boer semen. Pre-freezing qualities of viability, motilities and abnormalities was 88.67+4.16 %, 66.33 +1.53 % and 4.67+ 0.57 % respectively. Meanwhile, post-thawing qualities is considered as good as standard qualities at least more than 40 % (51.0+6.5%). The percentage of commercial diluents were influenced highly significant (P<0.01).The best diluents ration is 1:4 (v/v) for both final sperms stocked. However freezing sperm conserved in -196 oC is better than –45 oC (i.e. motility 39.3.94 % vs. 51.0 + 6.5 %). It was concluded that Mr. frosty system was considered as the feasible method for freezing semen in the reason for practical purposes.

Keywords: sperm quality, goat, viability, diluteR

Procedia PDF Downloads 241
917 Mineralogy and Fluid Inclusion Study of the Kebbouch South Pb-Zn Deposit, Northwest Tunisia

Authors: Imen Salhi, Salah Bouhlel, Bernrd Lehmann

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The Kebbouch South Pb-Zn deposit is located 20 km to the east of El Kef (NW) in the southeastern part of the Triassic diapir belt in the Tunisian Atlas. The deposit is composed of sulfide and non-sulfide zinc-lead ore bodies. The aim of this study is to provide petrographic results, mineralogy, as well as fluid inclusion data of the carbonate-hosted Pb-Zn Kebbouch South deposit. Mineralization forms two major ore types: (1) lenticular dolostones and clay breccias in the contact zone between Triassic and Upper Cretaceous strata;, it consists of small-scale lenticular, strata-or fault-controlled mineralization mainly composed of marcasite, galena, sphalerite, pyrite, and (2) stratiform mineralization in the Bahloul Formation (Upper Cenomanian-Lower Turonian) consisting of framboidal and cubic pyrite, disseminated sphalerite and galena. Non-metalliferous and/or gangue minerals are represented by dolomite, calcite, celestite and quartz. Fluid inclusion petrography study has been carried out on calcite and celestite. Fluid inclusions hosted in celestite are less than 20 µm large and show two types of aqueous inclusions: monophase liquid aqueous inclusions (L), abundant and very small, generally less than 15 µm and liquid-rich two phase inclusions (L+V). The gas phase forms a mobile vapor bubble. Microthermometric analyses of (L+V) fluid inclusions for celestite indicate that the homogenization temperature ranges from 121 to 156°C, and final ice melting temperatures are in the range of – 19 to -9°C corresponding to salinities of 12 to 21 wt% NaCl eq. (L+V) fluid inclusions from calcite are frequently localized along the growth zones; their homogenization temperature ranges from 96 to 164°C with final ice melting temperatures between -16 and -7°C corresponding to salinities of 9 to 19 wt% NaCl eq. According to mineralogical and fluid inclusion studies, mineralization in the Pb – Zn Kebbouch South deposit formed between 96 to 164°C with salinities ranging from 9 to 21 wt% NaCl eq. A contribution of basinal brines in the ore formation of the kebbouch South Pb–Zn deposit is likely. The deposit is part of the family of MVT deposits associated with the salt diapir environment.

Keywords: fluid inclusion, Kebbouch South, mineralogy, MVT deposits, Pb-Zn

Procedia PDF Downloads 237
916 Ownership and Shareholder Schemes Effects on Airport Corporate Strategy in Europe

Authors: Dimitrios Dimitriou, Maria Sartzetaki

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In the early days of the of civil aviation, airports are totally state-owned companies under the control of national authorities or regional governmental bodies. From that time the picture has totally changed and airports privatisation and airport business commercialisation are key success factors to stimulate air transport demand, generate revenues and attract investors, linked to reliable and resilience of air transport system. Nowadays, airport's corporate strategy deals with policies and actions, affecting essential the business plans, the financial targets and the economic footprint in a regional economy they serving. Therefore, exploring airport corporate strategy is essential to support the decision in business planning, management efficiency, sustainable development and investment attractiveness on one hand; and define policies towards traffic development, revenues generation, capacity expansion, cost efficiency and corporate social responsibility. This paper explores key outputs in airport corporate strategy for different ownership schemes. The airport corporations are grouped in three major schemes: (a) Public, in which the public airport operator acts as part of the government administration or as a corporised public operator; (b) Mixed scheme, in which the majority of the shares and the corporate strategy is driven by the private or the public sector; and (c) Private, in which the airport strategy is driven by the key aspects of globalisation and liberalisation of the aviation sector. By a systemic approach, the key drivers in corporate strategy for modern airport business structures are defined. Key objectives are to define the key strategic opportunities and challenges and assess the corporate goals and risks towards sustainable business development for each scheme. The analysis based on an extensive cross-sectional dataset for a sample of busy European airports providing results on corporate strategy key priorities, risks and business models. The conventional wisdom is to highlight key messages to authorities, institutes and professionals on airport corporate strategy trends and directions.

Keywords: airport corporate strategy, airport ownership, airports business models, corporate risks

Procedia PDF Downloads 290
915 Breast Cancer Diagnosing Based on Online Sequential Extreme Learning Machine Approach

Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

Procedia PDF Downloads 97
914 Artificial Intelligence Impact on the Australian Government Public Sector

Authors: Jessica Ho

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AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

Procedia PDF Downloads 53
913 Contactless Heart Rate Measurement System based on FMCW Radar and LSTM for Automotive Applications

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

Procedia PDF Downloads 54
912 Adhering to the Traditional Standard of Originality in the Era of Artificial Intelligence

Authors: Xiaochen Mu

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With the emergence and application of ChatGPT, the issue of copyright ownership for artificial intelligence-generated works has once again drawn attention in the academic community. Compared to previous AI technologies, the level of intelligence of ChatGPT can be described as disruptively enhanced. The recent amendment to copyright law not only clarifies the definition of work through Article 3 but also changes the catch-all clause from "other works stipulated by laws and administrative regulations" to "other intellectual achievements that meet the characteristics of a work", which seems to reflect the legislative attitude towards expanding the types and scope of works protected by copyright. In addition, the term "audiovisual works" replacing "cinematographic works and works created by methods similar to filmmaking", as well as the rise of short video platforms and the emergence of various new types of works (such as AI-generated works), have sparked discussions in academia about the level of copyright protection that should be provided for these new "works". However, the prerequisite for providing protection to these new "works" is an analysis of their copyrightability, that is, whether they are works in the sense of copyright law and can meet the standard of originality. Originality, as one of the essential components of a work in copyright law, has reached a consensus in both academia and the judicial domain. However, there is not yet a complete system for judging the meaning and degree of originality, leading to confusion in the criteria for assessing originality. Originality is supposed to be a scale in the hands of judges, but this scale lacks gradations. After analyzing different theories and cases related to originality, this article advocates for adherence to the standard of originality judgment, not arbitrarily applying the same originality standard to all types of works nor ignoring the changes in creative methods and dissemination modes brought about by technology. We allow for corresponding adjustments and interpretations based on the different forms of work. For example, to address the need to protect computer software and data compilations, the European Union issued the "EU Directive on the Legal Protection of Computer Programs" in 1991 and the "EU Directive on the Legal Protection of Databases" in 1996, proposing a standard of "author's own intellectual creation" for the issue of originality in works. For instance, Article 1(3) of the "EU Directive on the Legal Protection of Computer Programs" stipulates that computer software is protected only if it is original and is the author's own intellectual creation. No other standard should be applied to determine the legality of the protection of computer software. Similarly, Article 3 of the "EU Directive on the Legal Protection of Databases" provides that databases, by virtue of the selection and arrangement of their contents, are protected only if they constitute the author's own intellectual creation, and no other standard should be applied to determine the legality of this protection. Clearly, "author's own intellectual creation" is a standard that lies between the "spirit, emotion, personality" criteria of the author's rights system and the "skill, judgment, labor" criteria of the copyright system. For example, even in Germany, which emphasizes a high degree of creation, the "small coin" theory is applied to make special judgments on the originality of computer programs, product descriptions, tables, catalogs, etc. Appropriate adjustments and interpretations are our response to technological progress, but what we adhere to are the principles and bottom lines of these adjustments and interpretations, which are the legislative intent and purpose of copyright law. Technological development will never cease, and in the face of challenges brought by technological innovation, in addition to utilizing hermeneutical methods to make reasonable interpretations of existing theories based on the inclusiveness of language and text, we can make adjustments through judicial interpretations. Furthermore, the systematic nature of law can be employed to examine whether related legal systems can resolve such conflicts. Taking originality as an example, for works with different degrees of originality, both the fair use system and the neighboring rights system can offer reasonable interpretations.

Keywords: copyright, data protection, property right, intellectual property

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911 Modeling Pan Evaporation Using Intelligent Methods of ANN, LSSVM and Tree Model M5 (Case Study: Shahroud and Mayamey Stations)

Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

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The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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910 Profitability Assessment of Granite Aggregate Production and the Development of a Profit Assessment Model

Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an artificial neural network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R²), Root mean square error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: national development, granite, profitability assessment, ANN models

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909 The Impact of Civil Disobedience on Tourist and Local Residents in Cameroon: Case Study the North West Region

Authors: Zita Fomukong Andam

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Civil disobedience according to John Rawls (1971) is a public nonviolent and conscientious breach of laws undertaken with the aim of bringing about a change in government laws and policies. Thus individuals who engage themselves in such an act are aware and ready to accept the consequences of their actions. Cameroon more precisely the Northwest and the Southwest region which are the English part are considered as one of the societies facing this act of civil disobedience. It has been a tormenting issue in the country affecting its economy and the tourism sector. This is because these regions known as one of the best touristic sites of the country is not more considered as a destination to be visited by tourist because of its insecurities. Many commercial buildings have been burning down, leaving many young Cameroonians jobless. Education has been hindered, and youths are forced to relocate to nearby cities in order to continue their education. This crisis has created a lot of insecurity throughout the regions thus youths now have one common interest to travel abroad either to seek refuge or to continue their education and even search for jobs. The purpose of this research is to assess the issue of civil disobedience, trying to understand why it is affected only by a specific region in a country while the others are doing fine. A deep research discourse was conducted with randomly selected individuals aging between 15 to 40 years living both in the destination and abroad. Survey questionnaires and interviews were carried out as a method to collect data. The results show that this crisis has impacted the local residents psychologically and has injected a lot of fears into tourists and they are no more willing to visit the destination. In addition, it has brought a negative impact on the county’s economy since tourism is considered as the key sector in a country’s economy. On the other hand, the results showed that many local residents have remained jobless, others have lost family members, and the daily routine life has been affected. Understanding these results, the national government and international bodies might be able to propose possible and efficient solutions in order to attain stability and security in this region.

Keywords: civil disobedience, economic impact, local residents, tourist

Procedia PDF Downloads 99
908 Human Digital Twin for Personal Conversation Automation Using Supervised Machine Learning Approaches

Authors: Aya Salama

Abstract:

Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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907 Forecasting Optimal Production Program Using Profitability Optimization by Genetic Algorithm and Neural Network

Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

Procedia PDF Downloads 426
906 English Grammatical Errors of Arabic Sentence Translations Done by Machine Translations

Authors: Muhammad Fathurridho

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Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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905 Impact of Environmental Pollution on Oxidative Stress Indices in African Cat Fish (Clarias gariepinus) from Araromi River in Ondo State, Nigeria

Authors: Arojojoye Oluwatosin Adetola, Nwaechefu Olajumoke Olufunlayo, Ademola Adetokunbo Oyagbemi, Jeremiah Moyinoluwalogo Afolabi, Asaolu Racheal Oluwabukola

Abstract:

The effects of man’s activities on the environment include depletion of natural resources alongside pollution of water bodies. Petroleum exploration in the Niger Delta region of Nigeria has compromised the aquatic environment with grave consequences on the entire ecosystem. In this study, we assessed the environmental safety of Araromi River, located in an oil-producing area in Ondo State, in the Niger Delta region of Nigeria by determining the levels of heavy metals (copper, cadmium, chromium, nickel, lead) and some biomarkers of oxidative stress (malondialdehyde, glutathione-S-transferase, glutathione peroxidase, catalase, superoxide dismutase, myeloperoxidase and reduced glutathione) in Clarias gariepinus (350-400g) from the river using standard methods. Clarias gariepinus from a clean fish farm in the same geographical location as the reference site (Ilesannmi fishery) was used as a control. Water samples from both sites were also analysed for some physicochemical parameters, heavy metals, and bacterial contamination. Our findings show a significant increase in malondialdehyde level (index of lipid peroxidation) as well as alterations in antioxidant status in the organs of Clarias gariepinus from Araromi River compared with control. A significant increase in bacterial contaminants, heavy metal pollutants, and particulate matter deposits were also observed in the water sample from Araromi River compared with control. In conclusion, high levels of indicators of environmental pollution observed in the water sample from Araromi River coupled with induction of oxidative stress in Clarias gariepinus from the river show that Araromi River is polluted; therefore, consumption of fishes and other aquatic organisms from the river may be unsafe for the people in that community.

Keywords: Araromi River, Clarias gariepinus, environmental pollution, heavy metals, oxidative stress

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904 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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903 ‘BEST BARK’ Dog Care and Owner Consultation System

Authors: Shalitha Jayasekara, Saluk Bawantha, Dinithi Anupama, Isuru Gunarathne, Pradeepa Bandara, Hansi De Silva

Abstract:

Dogs have been known as "man's best friend" for generations, providing friendship and loyalty to their human counterparts. However, due to people's busy lives, they are unaware of the ailments that can affect their pets. However, in recent years, mobile technologies have had a significant impact on our lives, and with technological improvements, a rule-based expert system allows the end-user to enable new types of healthcare systems. The advent of Android OS-based smartphones with more user-friendly interfaces and lower pricing opens new possibilities for continuous monitoring of pets' health conditions, such as healthy dogs, dangerous ingestions, and swallowed objects. The proposed ‘Best Bark’ Dog care and owner consultation system is a mobile application for dog owners. Four main components for dog owners were implemented after a questionnaire was distributed to the target group of audience and the findings were evaluated. The proposed applications are widely used to provide health and clinical support to dog owners, including suggesting exercise and diet plans and answering queries about their dogs. Additionally, after the owner uploads a photo of the dog, the application provides immediate feedback and a description of the dog's skin disease.

Keywords: Convolution Neural Networks, Artificial Neural Networks, Knowledgebase, Sentimental Analysis.

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902 Establishing a Drug Discovery Platform to Progress Compounds into the Clinic

Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

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901 Comparative Study of Dermal Regeneration Template Made by Bovine Collagen with and without Silicone Layer in the Treatment of Post-Burn Contracture

Authors: Elia Caldini, Cláudia N. Battlehner, Marcelo A. Ferreira, Rolf Gemperli, Nivaldo Alonso, Luiz P. Vana

Abstract:

The advent of dermal regenerate templates has fostered major advances in the treatment of acute burns and their sequelae, in the last two decades. Both data on morphological aspects of the newly-formed tissue, and clinical trials comparing different templates, are still lacking. The goal of this study was to prospectively analyze the outcome of patients treated with two of the existing templates, followed by thin skin autograft. They are both made of bovine collagen, one includes a superficial silicone layer. Surgery was performed on patients with impaired mobility resulting from burn sequelae (n = 12 per template). Negative pressure therapy was applied post-surgically; patients were monitored for 12 months. Data on scar skin quality (Vancouver and POSAS evaluation scales), rate of joint mobility recovery, and graft contraction were recorded. Improvement in mobility and skin quality were demonstrated along with graft contraction, in all patients. The silicone-coupled template showed the best performance in all aspects.

Keywords: dermal regeneration template, artificial skin, skin quality, scar contracture

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900 Deep Learning to Improve the 5G NR Uplink Control Channel

Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

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The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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899 The Evolution of Amazon Alexa: From Voice Assistant to Smart Home Hub

Authors: Abrar Abuzaid, Maha Alaaeddine, Haya Alesayi

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This project is centered around understanding the usage and impact of Alexa, Amazon's popular virtual assistant, in everyday life. Alexa, known for its integration into devices like Amazon Echo, offers functionalities such as voice interaction, media control, providing real-time information, and managing smart home devices. Our primary focus is to conduct a straightforward survey aimed at uncovering how people use Alexa in their daily routines. We plan to reach out to a wide range of individuals to get a diverse perspective on how Alexa is being utilized for various tasks, the frequency and context of its use, and the overall user experience. The survey will explore the most common uses of Alexa, its impact on daily life, features that users find most beneficial, and improvements they are looking for. This project is not just about collecting data but also about understanding the real-world applications of a technology like Alexa and how it fits into different lifestyles. By examining the responses, we aim to gain a practical understanding of Alexa's role in homes and possibly in workplaces. This project will provide insights into user satisfaction and areas where Alexa could be enhanced to meet the evolving needs of its users. It’s a step towards connecting technology with everyday life, making it more accessible and user-friendly

Keywords: Amazon Alexa, artificial intelligence, smart speaker, natural language processing

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898 Inerting and Upcycling of Foundry Fines

Authors: Chahinez Aissaoui, Cecile Diliberto, Jean-Michel Mechling

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The manufacture of metal foundry products requires the use of sand moulds, which are destroyed, and new ones made each time metal is poured. However, recycled sand requires a regeneration process that produces a polluted fine mineral phase. Particularly rich in heavy metals and organic residues, this foundry co-product is disposed of in hazardous waste landfills and requires an expensive stabilisation process. This paper presents the results of research that valorises this fine fraction of foundry sand by inerting it in a cement phase. The fines are taken from the bag filter suction systems of a foundry. The sample is in the form of filler, with a fraction of less than 140µm, the D50 is 43µm. The Blaine fineness is 3120 cm²/g, and the fines are composed mainly of SiO₂, Al₂O₃ and Fe₂O₃. The loss on ignition at 1000°C of this material is 20%. The chosen inerting technique is to manufacture cement pastes which, once hardened, will be crushed for use as artificial aggregates in new concrete formulations. Different percentages of volume substitutions of Portland cement were tested: 30, 50 and 65%. The substitution rates were chosen to obtain the highest possible recycling rate while satisfying the European discharge limits (these values are assessed by leaching). They were also optimised by adding water-reducing admixtures to increase the compressive strengths of the mixes.

Keywords: leaching, upcycling, waste, residuals

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897 Tender Systems and Processes within the Mauritian Construction Industry: Investigating the Predominance of International Firms and the Lack of Absorptive Capacity in Local Firms

Authors: K. Appasamy, P. Paul

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Mauritius, a developing small-island-state, is facing a recession which is having a considerable economic impact particularly on its construction sector. Further, the presence of foreign entities, both as companies and workers, within this sector is creating a very competitive environment for local firms. This study investigates the key drivers that allow foreign firms to participate in this sector, in particular looking at the international and local tender processes, and the capacity of local industry to participate. This study also looks at how the current set up may hinder the latter’s involvement. The methodology used included qualitative semi-structured interviews conducted with established foreign companies, local companies, and public bodies. Study findings indicate: there is an adequate availability of professional skills and expertise within the Mauritian construction industry but a lack of skilled labour especially at the operative level; projects awarded to foreign firms are either due to their uniqueness and hence lack of local knowledge, or due to foreign firms having lower tender bids; tendering systems and processes are weak, including monitoring and enforcement, which encourages corruption and favouritism; a high level of ignorance of this sector’s characteristics and opportunities exists amongst the local population; local entities are very profit oriented and have short term strategies that discourage long term investment in workforce training and development; but most importantly, stakeholders do not grasp the importance of encouraging youngsters to join this sector, they have no long term vision, and there is a lack of mutual involvement and collaboration between them. Although local industry is highly competent, qualified and experienced, the tendering and procurement systems in Mauritius are not conducive enough to allow for effective strategic planning and an equitable allocation of projects during an economic downturn so that the broadest spread of stakeholders’ benefit. It is of utmost importance that all sector and government entities collaborate to formulate strategies and reforms on tender processes and capacity building to ensure fairness and continuous growth of this sector in Mauritius.

Keywords: construction industry, tender process, international firms, local capacity, Mauritius

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896 Single Pole-To-Earth Fault Detection and Location on the Tehran Railway System Using ICA and PSO Trained Neural Network

Authors: Masoud Safarishaal

Abstract:

Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

Procedia PDF Downloads 102