Search results for: artificial stock market

Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Yuan-Lin Liu, Ye Li, Tian Xia

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Taxi-calling APPs have been used widely, while brought both benefits and a variety of issues for the taxi market. Many countries do not know whether the benefits are remarkable than the issues or not. This paper established a comparison between the basic scenario (2009-2012) and a taxi-calling software usage scenario (2012-2015) to explain the impact of taxi-calling APPs. The impacts of taxi-calling APPs illustrated by the comparison results are: 1) The supply and demand distribution is more balanced, extending from the city center to the suburb. The availability of taxi service has been improved in low density areas, thin market attribute has also been improved; 2)The ratio of short distance taxi trip decreased, long distance service increased, the utilization of mileage increased, and the rate of empty decreased; 3) The popularity of taxi-calling APPs was able to reduce the average empty distance, cruise time, empty mileage rate and average times of loading passengers, can also enhance the average operating speed, improve the taxi operating level, and reduce social cost although there are some disadvantages. This paper argues that the taxi industry and government can establish an integrated third-party credit information platform based on credit evaluated by the data of the drivers’ driving behaviors to supervise the drivers. Taxi-calling APPs under fully covered supervision in the mobile Internet environment will become a new trend.

Keywords: taxi, taxi-calling APPs, credit, scenario comparison

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Authors: Nadezhda Kvatashidze

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The International Accounting Standards Board updated the conceptual framework for financial reporting. The main reason behind it is to resolve the tasks of the accounting, which are caused by the market development and business-transactions of a new economic content. Also, the investors call for higher transparency of information and responsibility for the results in order to make a more accurate risk assessment and forecast. All these make it necessary to further develop the conceptual framework for financial reporting so that the users get useful information. The market development and certain shortcomings of the conceptual framework revealed in practice require its reconsideration and finding new solutions. Some issues and concepts, such as disclosure and supply of information, its qualitative characteristics, assessment, and measurement uncertainty had to be supplemented and perfected. The criteria of recognition of certain elements (assets and liabilities) of reporting had to be updated, too and all this is set out in the updated edition of the conceptual framework for financial reporting, a comprehensive collection of concepts underlying preparation of the financial statement. The main objective of conceptual framework revision is to improve financial reporting and development of clear concepts package. This will support International Accounting Standards Board (IASB) to set common “Approach & Reflection” for similar transactions on the basis of mutually accepted concepts. As a result, companies will be able to develop coherent accounting policies for those transactions or events that are occurred from particular deals to which no standard is used or when standard allows choice of accounting policy.

Keywords: conceptual framework, measurement basis, measurement uncertainty, neutrality, prudence, stewardship

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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Authors: Ibrahim H. Kilic, A. B. Tugrul

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Energy is a fundamental component in economic development and energy consumption is an index of prosperity and the standard of living. The consumption of energy per capita has increased significantly over the last decades, as the standard of living has improved. Turkey’s geographical location has several advantages for extensive use of wind power. Among the renewable sources, Turkey has very high wind energy potential. Information such as installation capacity of wind power plants in installation, under construction and license stages in the country are reported in detail. Some suggestions are presented in order to increase the wind power installation capacity of Turkey. Turkey’s economic and social development has led to a massive increase in demand for electricity over the last decades. Since the Turkey has no major oil or gas reserves, it is highly dependent on energy imports and is exposed to energy insecurity in the future. But Turkey does have huge potential for renewable energy utilization. There has been a huge growth in the construction of wind power plants and small hydropower plants in recent years. To meet the growing energy demand, the Turkish Government has adopted incentives for investments in renewable energy production. Wind energy investments evaluated the impact of feed-in tariffs (FIT) based on three scenarios that are optimistic, realistic and pessimistic with APLUS software that is developed for rational evaluation for energy market. Results of the three scenarios are evaluated in the view of electricity market for Turkey.

Keywords: APLUS, energy policy, renewable energy, wind power, Turkey

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Authors: Meimei Shi

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Objectives: The identification of endangered species, especially simultaneous detection of multiple species in complex samples, plays a critical role in alleged wildlife crime incidents and prevents illegal trade. This study was to develop a multi-locus DNA metabarcoding method for endangered animal species identification. Methods: Several pairs of universal primers were designed according to the mitochondria conserved gene regions. Experimental mixtures were artificially prepared by mixing well-defined species, including endangered species, e.g., forest musk, bear, tiger, pangolin, and sika deer. The artificial samples were prepared with 1-16 well-characterized species at 1% to 100% DNA concentrations. After multiplex-PCR amplification and parameter modification, the amplified products were analyzed by capillary electrophoresis and used for NGS library preparation. The DNA metabarcoding was carried out based on Illumina MiSeq amplicon sequencing. The data was processed with quality trimming, reads filtering, and OTU clustering; representative sequences were blasted using BLASTn. Results: According to the parameter modification and multiplex-PCR amplification results, five primer sets targeting COI, Cytb, 12S, and 16S, respectively, were selected as the NGS library amplification primer panel. High-throughput sequencing data analysis showed that the established multi-locus DNA metabarcoding method was sensitive and could accurately identify all species in artificial mixtures, including endangered animal species Moschus berezovskii, Ursus thibetanus, Panthera tigris, Manis pentadactyla, Cervus nippon at 1% (DNA concentration). In conclusion, the established species identification method provides technical support for customs and forensic scientists to prevent the illegal trade of endangered animals and their products.

Keywords: DNA metabarcoding, endangered animal species, mitochondria nucleic acid, multi-locus

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Authors: Uzoma Emmanuel Igboji

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The study investigates the effects of cash flow position on corporate performance in the manufacturing sector of Nigeria, using multiple regression techniques. The study involved a survey of five (5) manufacturing companies quoted on the Nigerian Stock Exchange. The data were obtained from the annual reports of the selected companies under study. The result shows that operating and financing cash flow have a significant positive relationship with corporate performance, while investing cash flow position have a significant negative relationship. The researcher recommended that the regulatory authorities should encourage external auditors of these quoted companies to use cash flow ratios in evaluating the performance of a company before expressing an independent opinion on the financial statement. The will give detailed financial information to existing and potential investors to make informed economic decisions.

Keywords: cash flow, financing, performance, operating

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Authors: Mazarine Roquet, Pierre Dewallef

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The building sector, both residential and tertiary, accounts for a significant share of greenhouse gas emissions. In Belgium, partly due to poor insulation of the building stock, but certainly because of the massive use of fossil fuels for heating buildings, this share reaches almost 30%. To reduce carbon emissions from urban building heating, district heating networks emerge as a promising solution as they offer various assets such as improving the load factor, integrating combined heat and power systems, and enabling energy source diversification, including renewable sources and waste heat recovery. However, mainly for sake of simple operation, most existing district heating networks still operate at high or medium temperatures ranging between 120°C and 60°C (the socalled second and third-generations district heating networks). Although these district heating networks offer energy savings in comparison with individual boilers, such temperature levels generally require the use of fossil fuels (mainly natural gas) with combined heat and power. The fourth-generation district heating networks improve the transport and energy conversion efficiency by decreasing the operating temperature between 50°C and 30°C. Yet, to decarbonise the building heating one must increase the waste heat recovery and use mainly wind, solar or geothermal sources for the remaining heat supply. Fifth-generation networks operating between 35°C and 15°C offer the possibility to decrease even more the transport losses, to increase the share of waste heat recovery and to use electricity from renewable resources through the use of heat pumps to generate low temperature heat. The main objective of this contribution is to exhibit on a real-life test case the benefits of replacing an existing third-generation network by a fifth-generation one and to decarbonise the heat supply of the building stock. The second objective of the study is to highlight the difficulties resulting from the use of a fifth-generation, low-temperature, district heating network. To do so, a simulation model of the district heating network including its regulation is implemented in the modelling language Modelica. This model is applied to the test case of the heating network on the University of Liège's Sart Tilman campus, consisting of around sixty buildings. This model is validated with monitoring data and then adapted for low-temperature networks. A comparison of primary energy consumptions as well as CO2 emissions is done between the two cases to underline the benefits in term of energy independency and GHG emissions. To highlight the complexity of operating a lowtemperature network, the difficulty of adapting the mass flow rate to the heat demand is considered. This shows the difficult balance between the thermal comfort and the electrical consumption of the circulation pumps. Several control strategies are considered and compared to the global energy savings. The developed model can be used to assess the potential for energy and CO2 emissions savings retrofitting an existing network or when designing a new one.

Keywords: building simulation, fifth-generation district heating network, low-temperature district heating network, urban building heating

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Authors: Mehmet Ali Topçu, Aydın Ruşen

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Çinkur is the only plant in Turkey that produces zinc from primary ore containing zinc carbonate from its establishment until 1997. After this year, zinc concentrate coming from Iran was used in this plant. Therefore, there are two different leach residues namely Turkish leach residue (TLR) and Iranian leach residue (ILR), in Çinkur stock piles. This paper describes zinc recovery by sulphuric acid (H2SO4) treatment for each leach residue and includes comparison of blended of TLR and ILR. Before leach experiments; chemical, mineralogical and thermal analysis of three different leach residues was carried out by using atomic absorption spectrometry (AAS), X-Ray diffraction (XRD) and differential thermal analysis (DTA), respectively. Leaching experiments were conducted at optimum conditions; 100 oC, 150 g/L H2SO4 and 2 hours. In the experiments, stirring rate was kept constant at 600 r/min which ensures complete mixing in leaching solution. Results show that zinc recovery for Iranian LR was higher than Turkish LR due to having different chemical composition from each other.

Keywords: hydrometallurgy, leaching, metal extraction, metal recovery

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Authors: Björn de Kruijf, Arjen Edzes, Sietske Waslander

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In an ever-quickly changing society, lifelong development is seen as a solution to labor market problems by politicians and policymakers. In this paper, we investigate how policy instruments are used to increase participation in lifelong development and on which behavioral principles policy is based. Digitization, automation, and an aging population change society and the labor market accordingly. Skills that were once most sought after in the workforce can become abundantly present. For people to remain relevant in the working population, they need to continue adapting new skills useful in the current labor market. Many reports have been written that focus on the role of lifelong development in this changing society and how lifelong development can help keep people adapt and stay relevant. Inspired by these reports, governments have implemented a broad range of policies to support participation in lifelong development. The question we ask ourselves is how government policies promote participation in lifelong development. This stems from a complex interplay of policy instruments and learning. Regulation, economic and soft instruments can be combined to promote lifelong development, and different types of education further complex policies on lifelong development. Literature suggests that different stages in people’s lives might warrant different methods of learning. Governments could anticipate this in their policies. In order to influence people’s behavior, the government can tap into a broad range of sociological, psychological, and (behavioral) economic principles. The traditional economic assumption that behavior is rational is known to be only partially true, and the government can use many biases in human behavior to stimulate participation in lifelong development. In this paper, we also try to find which biases the government taps into to promote participation if they tap into any of these biases. The goal of this paper is to analyze government policies intended to promote participation in lifelong development. To do this, we develop a framework to analyze the policies on lifelong development. We specifically incorporate the role of learning and the behavioral principles underlying policy instruments in the framework. We apply this framework to the case of the Netherlands, where we examine a set of policy documents. We single out the policies the government has put in place and how they are vertically and horizontally related. Afterward, we apply the framework and classify the individual policies by policy instrument and by type of learning. We find that the Dutch government focuses on formal and non-formal learning in their policy instruments. However, the literature suggests that learning at a later age is mainly done in an informal manner through experiences.

Keywords: learning, lifelong development, policy analysis, policy instruments

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Authors: Emine Zeytinli

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Ottoman carpets were depicted in Renaissance painting while they were exported commercially. The carpets were highly demanded and used by the middle and upper classes of Western European countries. The motifs, designs, patterns, and ornamentation of these carpets were decorative objects of luxury for Western European residences as well as paintings. Oriental carpets found their way into European market already from the medieval times to the present century. They were considered as luxury items first, however, demanded by middle classes in Europe and North America within the nineteenth century. This century brought unprecedented changes in production and consumption in the world. Expanding industries created quick urbanization, changed the city life and new types of goods dominated the entire century. Increases in income allowed Europeans to spend on luxury items, consumers taste changed in number of ways including furniture and decoration. Use of a carpet in the orient lifestyle often considered as an art object with Western aesthetic sensibility. A carpet with an oriental character, an essential part of home decoration, was highly appreciated for floor, table covering and wall hanging. Turkish carpets with distinctive classical style, patterns, and colours were changed for the tastes of European consumers. This paper attempts to analyse how the taste and preferences of European and American consumers increased their buying of oriental objects namely carpets. The production of local hand woven carpet industry developed, carpet factories were set up and special weaving schools were opened in some major waving centres, and carpet weaving became one of the main manufacturing and export commodity of the empire. All of these attempts increased the reputation and market share in international market. The industry flourished, commercially operated carpet looms, sales revenues and export increased unprecedentedly. British and Ottoman archival documents, parliamentary papers and travel notes were used to analysed above mention effect on how the foreign demand changed designs of carpets and the business itself, how the production in households moved to the commercial premises and a flourished the industry.

Keywords: consumption patterns, carpet weaving, ottoman oriental carpets, commercialisation

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Authors: Zouari Ezzeddine, Ghraieb Ikram

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From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

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Authors: Doaa H. I. Mahmoud, El-Said M. Elsharkawy, Saad Z. Soliman, Soher E. Mustfa

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The opening of new promising foreign markets is one of the objectives of Egypt’s foreign trade policies, especially for agricultural exports. This study aims at the examination of the commodity structure of the Egyptian agricultural imports and exports with the COMESA countries. In addition, estimation of the surplus/deficit of the Egyptian commodities and agricultural balance with these countries is made. Time series data covering the period 2004-2016 is used. Estimation of the growth function along with the derivation of the annual growth rates of the study’s variables is made. Some of the results of the study period display the following: (1) The average total Egyptian exports to the COMESA (Common Market for Eastern and Southern Africa) countries is estimated at 1,491 million dollars, with an annual growth rate of 14.4% (214.7 million dollars). (2) The average annual Egyptian agricultural exports to these economies is estimated at 555 million dollars, with an annual growth rate of 19.4% (107.7 million dollars). (3) The average annual value of agricultural imports from the COMESA countries is set at 289 Million Dollars, with an annual growth rate of 14.4% (41.6 million dollars). (4) The study shows that there is a continuous surplus in the agricultural balance with these economies, whilst having a deficit in the raw-materials agricultural balance, as well as the balance of input requirements with these countries.

Keywords: COMESA, Egypt, growth rates, trade balance

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Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: Shirekha Layangani, Suneth Dharmaparakrama

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When the manufacturing industry is concerned the Environment Management System (EMS) is a common term. Currently most organizations have obtained the environmental standard certification, ISO 14001. In the Sri Lankan context even though the organizations adopt Environmental Management, a very limited number of companies tend to calculate their Carbon Footprints. This research discusses the demotivating factors of manufacturing organizations in Sri Lanka to integrate calculation of carbon footprint into their supply chains. Further it also identifies the benefits that manufacturing organizations can gain by implementing calculation of carbon footprint. The manufacturing companies listed under “ISO 14001” certification were considered in this study in order to investigate the problems mentioned above. 100% enumeration was used when the surveys were carried out. In order to gather essential data two surveys were designed to be done among manufacturing organizations that are currently engaged in calculating their carbon footprint and the organizations that have not. The survey among the first set of manufacturing organizations revealed the benefits the organizations were able to gain by implementing calculation of carbon footprint. The latter set organizations revealed the demotivating factors that have influenced not to integrate calculation of carbon footprint into their supply chains. This paper has summarized the results obtained by the surveys and segregated depending on the market share of the manufacturing organizations. Further it has indicated the benefits that can be obtained by implementing carbon footprint calculation, depending on the market share of the manufacturing entity. Finally the research gives suggestions to manufacturing organizations on applicability of adopting carbon footprint calculation depending on the benefits that can be obtained.

Keywords: carbon footprint, environmental management systems (EMS), benefits of carbon footprint, ISO14001

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Authors: Farid Yuristiawan, Aulina R. Rahmi, Detty Iryani, Gunawan

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Glass ionomer cement is one of the filling material that often used in the field of dentistry because it is relatively less expensive and mostly available. Surface hardness is one of the most important properties of restoration material; it is the ability of material to stand against indentation, which is directly connected to the material compressive strength and its ability to withstand abrasion. The higher surface hardness of a material means it is better to withstand abrasion. The existence of glass ionomer cement in the mouth makes it susceptible to any substance that comes into mouth, one of them is mouthwash which is a solution that used for many purposes such as antiseptic, astringent, to prevent caries, and bad breath. The presence of alcohol in mouthwash could affect the properties of glass ionomer cement, surface hardness. Objective: To determine the comparison of surface hardness of glass ionomer cement which soaked in alcohol containing mouthwash and alcohol-free mouthwash. Methods: This research is a laboratory experimental type study. There were 30 samples made from GC FUJI IX GP EXTRA and then soaked in artificial saliva for the first 24 hours inside incubator which temperature and humidity were controlled. Samples then divided into three groups. The first group will be soaked in alcohol-containing mouthwash; second group will be soaked alcohol-free mouthwash and control group will be soaked in artificial saliva for 6 hours inside incubator. Listerine is the mouthwash that was used on this research and surface hardness was examined using Vickers Hardness Tester. The result of this research shows mean value for surface hardness of the first group is 16.36 VHN, 24.04 VHN for second group, and 43.60 VHN for control group. The result one way ANOVA with post hoc Bonferroni comparing test show significant results p = 0.00. Conclusions: The data showed there were statistically significant differences of surface hardness between each group, which surface hardness of the first group is lower than the second group, and both surface hardness of the first (alcohol mouthwash) and second group (alcohol-free mouthwash) are lowered than control group (p = 0.00).

Keywords: glass ionomer cement, mouthwash, surface hardness, Vickers hardness tester

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Authors: Abdelrhman Elagez, Rolla Monib

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This empirical study investigates the observed risks associated with adopting Artificial Intelligence (AI) technologies in the construction industry and proposes potential mitigation strategies. While AI has transformed several industries, the construction industry is slowly adopting advanced technologies like AI, introducing new risks that lack critical analysis in the current literature. A comprehensive literature review identified a research gap, highlighting the lack of critical analysis of risks and the need for a framework to measure and mitigate the risks of AI implementation in the construction industry. Consequently, an online survey was conducted with 24 project managers and construction professionals, possessing experience ranging from 1 to 30 years (with an average of 6.38 years), to gather industry perspectives and concerns relating to AI integration. The survey results yielded several significant findings. Firstly, respondents exhibited a moderate level of familiarity (66.67%) with AI technologies, while the industry's readiness for AI deployment and current usage rates remained low at 2.72 out of 5. Secondly, the top-ranked barriers to AI adoption were identified as lack of awareness, insufficient knowledge and skills, data quality concerns, high implementation costs, absence of prior case studies, and the uncertainty of outcomes. Thirdly, the most significant risks associated with AI use in construction were perceived to be a lack of human control (decision-making), accountability, algorithm bias, data security/privacy, and lack of legislation and regulations. Additionally, the participants acknowledged the value of factors such as education, training, organizational support, and communication in facilitating AI integration within the industry. These findings emphasize the necessity for tailored risk assessment frameworks, guidelines, and governance principles to address the identified risks and promote the responsible adoption of AI technologies in the construction sector.

Keywords: risk management, construction, artificial intelligence, technology

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

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The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

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Authors: Srinivas Vangari

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In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: E Tolufase

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The demand, high costs and health implications of using energy derived from hydrocarbon compound have necessitated the continuous search for alternative source of energy. The World energy market is facing some challenges viz: depletion of fossil fuel reserves, population explosion, lack of energy security, economic and urbanization growth and also, in Nigeria some rural areas still depend largely on wood, charcoal, kerosene, petrol among others, as the sources of their energy. To overcome these short falls in energy supply and demand, as well as taking into consideration the risks from global climate change due to effect of greenhouse gas emissions and other pollutants from fossil fuels’ combustion, brought a lot of attention on efficiently harnessing the renewable energy sources. A very promising among the renewable energy resources for a clean energy technology for power production, vehicle and domestic usage is biogas. Therefore, optimization of biogas yield and quality is imperative. Hence, this study investigated yield and quality of biogas using low cost bio-digester and combination of various feed stocks referred to as co-digestion. Batch/Discontinuous Bio-digester type was used because it was cheap, easy, plausible and appropriate for different substrates used to get the desired results. Three substrates were used; cow dung, chicken droppings and lemon grass digested in five separate 21 litre digesters, A, B, C, D, and E and the gas collection system was designed using locally available materials. For single digestion we had; cow dung, chicken droppings, lemon grass, in Bio-digesters A, B, and C respectively, the co-digested three substrates in different mixed ratio 7:1:2 in digester D and E in ratio 5:3:2. The respective feed-stocks materials were collected locally, digested and analyzed in accordance with standard procedures. They were pre-fermented for a period of 10 days before being introduced into the digesters. They were digested for a retention period of 28 days, the physiochemical parameters namely; pressure, temperature, pH, volume of the gas collector system and volume of biogas produced were all closely monitored and recorded daily. The values of pH and temperature ranged 6.0 - 8.0, and 220C- 350C respectively. For the single substrate, bio-digester A(Cow dung only) produced biogas of total volume 0.1607m3(average volume of 0.0054m3 daily),while B (Chicken droppings ) produced 0.1722m3 (average of 0.0057m3 daily) and C (lemon grass) produced 0.1035m3 (average of 0.0035m3 daily). For the co-digested substrates in bio-digester D the total biogas produced was 0.2007m³ (average volume of 0.0067m³ daily) and bio-digester E produced 0.1991m³ (average volume of 0.0066m³ daily) It’s obvious from the results, that combining different substrates gave higher yields than when a singular feed stock was used and also mixing ratio played some roles in the yield improvement. Bio-digesters D and E contained the same substrates but mixed with different ratios, but higher yield was noticed in D with mixing ratio of 7:1:2 than in E with ratio 5:3:2.Therefore, co-digestion of substrates and mixing proportions are important factors for biogas production optimization.

Keywords: anaerobic, batch, biogas, biodigester, digestion, fermentation, optimization

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Authors: P. Ghosh, S. B. Sharma

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The growing problem of food waste is causing unacceptable economic, environmental and social impacts across the globe. In Australia, food waste is estimated at about AU$8 billion per year; however, information on the extent of wastage at different stages of the food value chain from farm to fork is very limited. This study aims to identify causes for and extent of food waste at wholesaler stage of the food value chain in the state of Western Australia. It also explores approaches applied to reduce and utilize food waste by the wholesalers. The study was carried out at Perth city market in Caning Vale, the main wholesale distribution centre for fruits and vegetables in Western Australia. A survey questionnaire was prepared and shared with 51 wholesalers and their responses to 10 targeted questions on quantity of produce (fruits and vegetables) delivery received and further supplied, reasons for waste generation and innovations applied or being considered to reduce and utilize food waste. Data were computed using the Statistical Package for the Social Sciences (SPSS version 21). Among the wholesalers 52% were primary wholesalers (buy produce directly from growers) and 48% were secondary wholesalers (buy produce in bulk from major wholesalers and supply to the local retail market, caterers, and customers with specific requirements). Average fruit and vegetable waste was 180 Kilogram per week per primary wholesaler and 30 Kilogram per secondary wholesaler. Based on this survey, the fruit and vegetable waste at wholesaler stage was estimated at about 286 tonnes per year. The secondary wholesalers distributed pre-ordered commodities, which minimized the potential to cause waste. Non-parametric test (Mann Whitney test) was carried out to assess contributions of wholesalers to waste generation. Over 56% of secondary wholesalers generally had nothing to bin as waste. Pearson’s correlation coefficient analysis showed positive correlation (r = 0.425; P=0.01) between the quantity of produce received and waste generated. Low market demand was the predominant reason identified by the wholesalers for waste generation. About a third of the wholesalers suggested that high cosmetic standards for fruits and vegetables - appearance, shape, and size - should be relaxed to reduce waste. Donation of unutilized fruits and vegetables to charity was overwhelmingly (95%) considered as one of the best options for utilization of discarded produce. The extent of waste at other stages of fruit and vegetable supply chain is currently being studied.

Keywords: food waste, fruits and vegetables, supply chain, waste generation

Procedia PDF Downloads 312

Authors: Ning Niu

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The study hinges on consumer taste, food industry (wine production) and cultural consumption (vineyard tourism) which are related to the Chinese market, consumers, and visitors traveling to Australian vineyards. The research topic can be summed up as: the economic importance of the Chinese market on Australian wine production; the economic importance of the Chinese market have an impact on how Australian wine is produced or packaged; the impact of mass Chinese wine tourism on Australian vineyards; the gendered and cultured experience of wine tourism for Chines visitors. This study aims to apply the theories of Pierre Bourdieu into the research in food industry and cultural consumption; investigate Chinese experiences with Australian wine products and vineyard tours; to explore the cultural, gendered and class influences on their experiences. The academic background covers the concepts of habitus, taste, capital proposed by Pierre Bourdieu along with long-lasting concepts within China’s cultural context including mianzi (face, dignity/honor/hierarchy) and guanxi (connections/social network), in order to develop new perspectives to study the tastes of Chinese tourists coming to Australia for wine experiences. The documents cited from Australian government or industries will be interpreted, and the analysis of data will constitute the economic background for this current study. The study applies qualitative research and draws from the fieldwork, choosing ethnographic observation, interviews, personal experiences and discursive analysis of government documents and tourism documents. The expected sample size includes three tourism professionals, two or three local Australian wine producers, and 20 to 30 Chinese wine consumers and visitors travelling to Australian vineyards. An embodied ethnography will be used to observe the Chinese participants’ feelings, thoughts, and experiences of their engagement with Australian wine and vineyards. The researcher will interview with Chinese consumers, tourism professionals, and Australian winemakers to collect primary data. Note-taking, picture-taking, and audio-recording will be adopted with informants’ permissions. Personal or group interview will be last for 30 and 60 minutes respectively. Personal experiences of the researcher have been analyzed to respond to some research questions, and have accumulated part of primary data (e.g., photos and stories) to discover how 'mianzi' and 'guanxi' influence Australian wine and tourism industries to meet the demands’ of Chinese consumers. At current stage, the secondary data from analysis of official and industrial documents has proved the economic importance of Chinese market is influencing Australian wine and tourism industries. And my own experiences related to this study, in some sense, has proved the Chinese cultural concepts (mianzi and guanxi) are influencing the Australian wine production and package along with vineyard tours. Future fieldwork will discover more in this research realm, contribute more to knowledge.

Keywords: habitus, taste, capital, mianzi, guanxi

Procedia PDF Downloads 130

Authors: Mubashar Iqbal, Iqra Anjum, Muhammad Dildar Gogi, Muhammad Jalal Arif

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The present study was carried to screen out the effective entomopathogenic fungi (EPF) inoculation method in maize and to evaluate pathogenicity and oviposition-choice in C. partellus. Three entomopathogenic fungi (EPF) formulations Pacer® (Metarhizium anisopliae), Racer® (Beauveria bassiana) and Meailkil® (Verticillium lecanii) were evaluated at three concentrations (5000, 10000 and 20000 ppm) for their endophytism in maize and pathogenicity in C. partellus. The stock solution of the highest concentration (20,000 ppm) was prepared and next lower from stock solution. In the first experiment, three EPF was inoculated in maize plant by four methods, i.e., leaf-inoculation (LI), whorl-inoculation (WI), shoot-inoculation (SI) and root-inoculation (RI). Leaf-discs and stem-cutting were sampled in all four inoculation methods and placed on fungus growth media in Petri dishes. In the second experiment, pathogenicity, pupal formation, adult emergence, sex ratio, oviposition-choice, and growth index of C. partellus were calculated. The leaves and stem of the inoculated plants were given to the counted number of larvae of C. Partellus. The mortality of larvae was recorded on daily basis till the pupation. The result shows that maximum percent mortality (86.67%) was recorded at high concentration (20000ppm) of Beauveria bassiana by leaf inoculation method. For oviposition choice bioassay, the newly emerged adults were fed on diet (water, honey and yeast in 9:1:1) for 48 hours. One pair of C. Partellus were aspirated from the rearing cages and were detained in large test tube plugged with diet soaked cotton. A set of four plants for each treatment were prepared and randomized inside the large oviposition chamber. The test tubes were opened and fitted in the hole made in the wall of oviposition chamber in front of each treatment. The oviposition chamber was placed in a completely dark laboratory to eliminate the effect of light on moth’s behavior. The plants were removed from the oviposition chamber after the death of adults. The number of eggs deposited on the plant was counted. The results of 2nd experiment revealed that in all EPF and inoculation methods, the fecundity, egg fertility and growth index of C. partellus decreased with the increase in concentration being significantly higher at low concentration (5000ppm) and lower at higher concentration (20000ppm). Application of B. bassiana demonstrated that minimum fecundity (126.83), egg fertility (119.52) and growth index (15%) in C. partellus followed by M. anisopliae with fecundity (135.93), egg fertility (132.29) and growth index (17.50%) while V. lecanii show higher values of fecundity (137.37), egg fertility (1135.42) and growth index (20%). Overall leaf inoculation method showed least fecundity (123.89) with egg fertility (115.36) and growth index (14%) followed by whorl, shoot inoculation method and root inoculation method show higher values of fecundity, egg fertility and growth index.

Keywords: Beauveria bassiana, Chilo partellus, entomopathoganic, Metarhizium anisopliae, Verticillium lecanii

Procedia PDF Downloads 138

Authors: Oleg Sapelnikov, Ruslan Latypov, Darina Ardus, Samvel Aivazian, Andrey Shiryaev, Renat Akchurin

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OBJECTIVE: MAZE procedure is one of the most effective surgical methods in atrial fibrillation (AF) treatment. Nowadays we are all aware of its modifications. In our study we conducted clinical analysis of “Box lesion+” approach during MAZE procedure in two-year follow-up. METHODS: We studied the results of the open-heart on-pump procedures performed in our hospital from 2017 to 2018 years. Thirty-two (32) patients with atrial fibrillation (AF) were included in this study. Fifteen (15) patients had concomitant coronary bypass grafting and seventeen (17) patients had mitral valve repair. Mean age was 62.3±8.7 years; prevalence of men was admitted (56.1%). Mean duration of AF was 4.75±5.44 and 7.07±8.14 years. In all cases, we performed endocardial Cryo-MAZE procedure with one-time myocardium revascularization or mitral-valve surgery. All patients of this study underwent pulmonary vein (PV) isolation and ablation of mitral isthmus with additional isolation of LA posterior wall (Box-lesion+ procedure). Mean follow-up was 2 years. RESULTS: All cases were performed without any complications. Additional isolation of posterior wall did not prolong the operative time and artificial circulation significantly. Cryo-MAZE procedure directly lasted 20±2.1 min, the whole operation time was 192±24 min and artificial circulation time was 103±12 min. According to design of the study, we performed clinical investigation of the patients in 12 months and in 2 years from the initial procedure. In 12 months, the number of AF free patients 81.8% and 75.8% in two years of follow-up. CONCLUSIONS: Isolation of the left atrial posterior wall and perimitral area may considerably improve the efficacy of surgical treatment, which was demonstrated in significant decrease of AF recurrences during the whole period of follow-up.

Keywords: atrial fibrillation, cryoablation, left atrium isolation, open heart procedure

Procedia PDF Downloads 128

Authors: Ben Morrow, Patrick O'Hara, Natalie Ban, Tunai Marques, Molly Fraser, Christopher Bone

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Relative to commercial fisheries, recreational fisheries are often poorly understood and pose various challenges for monitoring frameworks. In British Columbia (BC), Canada, Pacific salmon are heavily targeted by recreational fishers while also being a key source of nutrient flow and crucial prey for a variety of marine and terrestrial fauna, including endangered Southern Resident killer whales (Orcinus orca). Although commercial fisheries were historically responsible for the majority of salmon retention, recreational fishing now comprises both greater effort and retention. The current monitoring scheme for recreational salmon fisheries involves aerial-roving creel surveys. However, this method has been identified as costly and having low predictive power as it is often limited to sampling fragments of fluid and temporally dynamic fisheries. This study used imagery from two shore-based autonomous cameras in a highly active recreational fishery around Sooke, BC, and evaluated their efficacy in supplementing existing aerial-roving surveys for monitoring a recreational salmon fishery. This study involved continuous monitoring and high temporal resolution (over one million images analyzed in a single fishing season), using a deep learning-based vessel detection algorithm and a custom image annotation tool to efficiently thin datasets. This allowed for the quantification of peak-season effort from a busy harbour, species-specific retention estimates, high levels of detected fishing events at a nearby popular fishing location, as well as the proportion of the fishery management area represented by cameras. Then, this study demonstrated how it could substantially enhance the temporal resolution of a fishery through diel activity pattern analyses, scaled monthly to visualize clusters of activity. This work also highlighted considerable off-season fishing detection, currently unaccounted for in the existing monitoring framework. These results demonstrate several distinct applications of autonomous cameras for providing enhanced detail currently unavailable in the current monitoring framework, each of which has important considerations for the managerial allocation of resources. Further, the approach and methodology can benefit other studies that apply shore-based camera monitoring, supplement aerial-roving creel surveys to improve fine-scale temporal understanding, inform the optimal timing of creel surveys, and improve the predictive power of recreational stock assessments to preserve important and endangered fish species.

Keywords: cameras, monitoring, recreational fishing, stock assessment

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Authors: Maharani Yulisti, Amin Mugera, James Fogarty

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Food safety standards have received significant attention in the fisheries global market due to health issues, free trade agreements, and increasing aquaculture production. Vertical coordination throughout the supply chain of fish producing and exporting countries is needed to meet food safety demands imposed by importing countries. However, the complexities of the supply chain governance structures and difficulties in standard implementation can generate safety uncertainty and high transaction costs. Using a Transaction Cost Economics framework, this paper examines the alignment between food safety standards and the governance structures in the shrimp supply chain in Indonesia. We find the supply chain is organized closer to the hierarchy-like governance structure where private standard (organic standard) are implemented and more towards a market-like governance structure where public standard (IndoGAP certification) are more prevalent. To verify the statements, two cases are examined from Sidoarjo district as a centre of shrimp production in Indonesia. The results show that public baseline FSS (Food Safety Standards) need additional mechanism to achieve a coordinated chain-wide response because uncertainty, asset specificity, and performance measurement problems are high in this chain. Organic standard as private chain-wide FSS is more efficient because it has been achieved by hierarchical-like type of governance structure.

Keywords: governance structure, shrimp value chain, food safety standards, transaction costs economics

Procedia PDF Downloads 379

Authors: Barakat Adebisi Raji

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In the workplace, Artificial Intelligence has, in recent years, emerged as a transformative technology that revolutionizes how organizations operate and perform tasks. It is a technology that has a significant impact on transportation, manufacturing, education, cyber security, robotics, agriculture, healthcare, and so many other organizations. By harnessing AI technology, workplaces can enhance productivity, streamline processes, and make more informed decisions. Given the potential of AI to change the way we work and its impact on the labor market in years to come, employers understand that it entails legal challenges and risks despite the advantages inherent in it. Therefore, as AI continues to integrate into various aspects of the workplace, understanding the legal and ethical implications becomes paramount. Also central to this study is the question of who is held liable where AI makes any defaults; the person (company) who created the AI, the person who programmed the AI algorithm or the person who uses the AI? Thus, the aim of this paper is to provide a detailed overview of how AI-related liabilities are addressed under each legal tradition and shed light on potential areas of accord and divergence between the two legal cultures. The objectives of this paper are to (i) examine the ability of Common law and Islamic law to accommodate the issues and damage caused by AI in the workplace and the legality of compensation for such injury sustained; (ii) to discuss the extent to which AI can be described as a legal personality to bear responsibility: (iii) examine the similarities and disparities between Common Law and Islamic Jurisprudence on the liability of AI in the workplace. The methodology adopted in this work was qualitative, and the method was purely a doctrinal research method where information is gathered from the primary and secondary sources of law, such as comprehensive materials found in journal articles, expert-authored books and online news sources. Comparative legal method was also used to juxtapose the approach of Islam and Common Law. The paper concludes that since AI, in its current legal state, is not recognized as a legal entity, operators or manufacturers of AI should be held liable for any damage that arises, and the determination of who bears the responsibility should be dependent on the circumstances surrounding each scenario. The study recommends the granting of legal personality to AI systems, the establishment of legal rights and liabilities for AI, the establishment of a holistic Islamic virtue-based AI ethics framework, and the consideration of Islamic ethics.

Keywords: AI, health- care, agriculture, cyber security, common law, Shari'ah

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Authors: Ana Pinheiro, Fatima Suleman

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Literature has revealed strong awareness of companies in regard of expatriation, but issues associated with repatriation of employees after an international assignment have been overlooked. Repatriation is one of the most challenging human resource practices that affect how companies benefit from acquired skills and high potential employees; and gain competitive advantage through network developed during expatriation. However, empirical evidence achieved so far suggests that expatriates have been disappointed because companies lack an effective repatriation strategy. Repatriates’ professional and emotional needs are often unrecognized, while repatriation is perceived as a non-issue by companies. The underlying assumption is that the return to parent company, and original country, culture and language does not demand for any particular support. Unfortunately, this basic view has non-negligible consequences on repatriates, especially on expatriate retention and turnover rates after expatriation. The goal of our study is to examine the specific policies and practices adopted by companies to support employees after an international assignment. We assume that expatriation is process which ends with repatriation. The latter is such a crucial issue as the expatriation and require due attention through appropriate design of human resource management policies and tools. For this purpose, we use data from a qualitative research based on interviews to a sample of firms operating in Portugal. We attempt to compare how firms accommodate the concerns with repatriation in their policies and practices. Therefore, the interviews collect data on both expatriation and repatriation process, namely the selection and skills of candidates to expatriation, training, mentoring, communication and pay policies. Portuguese labor market seems to be an interesting case study for mainly two reasons. On the one hand, Portuguese Government is encouraging companies to internationalize in the context of an external market-oriented growth model. On the other hand, expatriation is being perceived as a job opportunity in the context of high unemployment rates of both skilled and non-skilled. This is an ongoing research and the data collected until now indicate that companies follow the pattern described in the literature. The interviewed companies recognize the higher relevance of repatriation process than expatriation, but disregard specific human resource policies. They have perceived that unfavorable labor market conditions discourage mobility across companies. It should be stressed that companies underline that employees enhanced the relevance of stable jobs and attach far less importance to career development and other benefits after expatriation. However, there are still cases of turnover and difficulties of retention. Managers’ report non-negligible cases of turnover associated with lack of effective repatriation programs and non-recognition of good performance. Repatriates seem to having acquired entrepreneurial spirit and skills and often create their own company. These results suggest that even in the context of worsening labor market conditions, there should be greater awareness of the need to retain talents, experienced and highly skills employees. Ultimately, other companies poach invaluable assets, while internationalized companies risk being training providers.

Keywords: expatriates, expatriation, international management, repatriation

Procedia PDF Downloads 336