Search results for: Collective Intelligence

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

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In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

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Authors: Lacheheb Dhia Eddine Zakaria, Ballout Amor

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Today, it is necessary to be thrifty for its planet, on one hand the space being a rare, nonrenewable resource, and on the other hand the ecological, economic and social cost of the urban sprawl. It is commonly asserted that the promotion of a more compact and dense city has a positive effect in terms of public costs of investment, functioning and costs for the citizens and the users of the city. It is clear that the modes urban development management have to evolve profoundly, in particular towards a densification favourable to the raising of the urban quality through an ideal urban density on the scale of the individual housing estate. The lot as an individual housing estate was adopted as an alternative development model to the collective housing, thought in an anthropocentric perspective to emerge as a quality model where the density plays an important role, by being included in operations of a global coherence, in an optimal organization without forgetting the main importance of the deadlines of construction and the finalization of the works. The image of eternal construction site inflicted to our cities explains the renewed interest for the application of the regulatory framework and the completion of these limited operations without global coherence, which are summed up in our case to a ground cut in plots of land, sold then built independently without being finished, and support the relevance of the essential question of the improvement of the outside aspect bound to the appearance which can be revealed as a so important factor for a better use and a better acceptance of its housing environment, that the ratio of a number of houses on a plot of land or the number of square meters by house. To demonstrate the impact of the completion degree of the subdivision dwellings, roads system and urban public utilities on the density or the densification and therefore on the urban quality, we studied two residential subdivisions, the private subdivision Sellam and the subdivision El Imane with a common situation, and a different land surface, density and cutting, being occupied by various social classes, with different needs and different household average size. The approach of this work is based on the typo morphological analysis to reveal the differences in the degrees of completions of the subdivision’s built environment and on the investigation, by a household’s survey, to demonstrate importance of the degree of completion and to reveal the conditions of qualitative densification favourable and convenient to a better subdivision’s appropriation.

Keywords: subdivision, degree of completion, densification, urban quality

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Authors: Cristian Pauna

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With few steps away from the 2020, investments in financial markets is a common activity nowadays. In the electronic trading environment, the automated investment software has become a major part in the business intelligence system of any modern financial company. The investment decisions are assisted and/or made automatically by computers using mathematical algorithms today. The complexity of these algorithms requires computer assistance in the investment process. This paper will present several investment strategies that can be automated with algorithmic trading for Deutscher Aktienindex DAX30. It was found that, based on several price action mathematical models used for high-frequency trading some investment strategies can be optimized and improved for automated investments with good results. This paper will present the way to automate these investment decisions. Automated signals will be built using all of these strategies. Three major types of investment strategies were found in this study. The types are separated by the target length and by the exit strategy used. The exit decisions will be also automated and the paper will present the specificity for each investment type. A comparative study will be also included in this paper in order to reveal the differences between strategies. Based on these results, the profit and the capital exposure will be compared and analyzed in order to qualify the investment methodologies presented and to compare them with any other investment system. As conclusion, some major investment strategies will be revealed and compared in order to be considered for inclusion in any automated investment system.

Keywords: Algorithmic trading, automated investment systems, limit conditions, trading principles, trading strategies

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Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

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Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Cita Ayeni

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Following countless violations of Human Rights in Nigeria by the various arms and agencies of government; from the Military to the Federal Police and other law enforcement agencies, Nigeria has been riddled with several reports of acts by these agencies against the citizens, ranging from illegal arrest and imprisonment, torture, disappearing, and extrajudicial killings, just to mention a few. This paper, focuses on SARS (Special Anti-Robbery Squad), a division of the Nigeria Police Force, and its reported threats to the people’s security, particularly the Nigerian youths, with continuous violence, extortion, illegal arrest and imprisonment, terror, and extrajudicial activities resulting in maiming and in most cases death, thus infringing on the human rights of the people it’s sworn to protect. This research further analyses how the activities of SARS has over the years instigated fear on the average Nigerian youth, preventing the free participation in daily life, education, job, and individual development, in turn impeding the realization of their full potentials for growth and participation in collective national development. This research analyzes the executive order by the then Acting President (Vice-President) of Nigeria, directing the overhauling of SARS, and its implementation by the Federal Police Force in determining if it’s enough to prevent or put a stop to the continuous Human Rights abuse and threat to the security of the individual citizen. Concluding that although the order by the Acting President was given with an intent to halt the various violations by SARS, and the Inspector General of Police’s (IGP) subsequent action by releasing a statement following the order, the bureaucracy in Nigeria, with a history of incompetency and a return to 'business as usual' after a reduced public outcry, it’s most likely that there will not be adequate follow up put in place and these violations would be slowly 'swept under the rug' with SARS officials not held accountable. It is recommended therefore that the Federal Government through the NPF, following the reforms made, in collaboration with the mentioned Independent Human Rights and civil societies organizations should periodically produce unbiased and publicly accessible reports on the implementation of these reforms and progress made. This will go a long way in assuring the public of actual fulfillment of the restructuring, reduce fear by the youths and restore some public faith in the government.

Keywords: special anti-robbery squad, youths in Nigeria, overhaul, insecurities, human rights violations

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Authors: Mayank Mishra

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Market Economy can be broadly defined as economic system where supply and demand regulate the economy and in which decisions pertaining to production, consumption, allocation of resources, price and competition are made by collective actions of individuals or organisations with limited government intervention. On the other hand Market Society is one where instead of the economy being embedded in social relations, social relations are embedded in the economy. A market economy becomes a market society when all of land, labour and capital are commodified. This transition also has effect on people’s attitude and values. Such a transition commence impacting the non-material aspect of life such as public education, public health and the like. The inception of neoliberal policies in non-market norms altered the nature of social goods like public health that raised the following questions. What impact would the transition to a market society make on people in terms of accessibility to public health? Is healthcare a commodity that can be subjected to a competitive market place? What kind of private investments are being made in public health and how do private investments alter the nature of a public good like healthcare? This research problem will employ empirical-analytical approach that includes deductive reasoning which will be using the existing concept of market economy and market society as a foundation for the analytical framework and the hypotheses to be examined. The research also intends to inculcate the naturalistic elements of qualitative methodology which refers to studying of real world situations as they unfold. The research will analyse the existing literature available on the subject. Concomitantly the research intends to access the primary literature which includes reports from the World Bank, World Health Organisation (WHO) and the different departments of respective ministries of the countries for the analysis. This paper endeavours to highlight how the issue of commodification of public health would lead to perpetual increase in its inaccessibility leading to stratification of healthcare services where one can avail the better services depending on the extent of one’s ability to pay. Since the fundamental maxim of private investments is to churn out profits, these kinds of trends would pose a detrimental effect on the society at large perpetuating the lacuna between the have and the have-nots.The increasing private investments, both, domestic and foreign, in public health sector are leading to increasing inaccessibility of public health services. Despite the increase in various public health schemes the quality and impact of government public health services are on a continuous decline.

Keywords: commodity, India and Pakistan, market society, public health

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Xiaojing Wang, Ann-Marie Ward, Tony Wall

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The problem of over-indebtedness has increased since deregulation of the banking industry in the 1980s, and now it has become a major problem for most countries in Europe, including Germany. Consumer debt issues have attracted not only the attention of academics but also government and debt counselling institutions. Overall, this research aims to contribute to the knowledge gap regarding the causes of consumer over-indebtedness in Germany and to develop predictive models for assessing consumer over-indebtedness risk at consumer level. The situation of consumer over-indebtedness is serious in Germany. The relatively high level of social welfare support in Germany suggests that consumer debt problems are caused by other factors, other than just over-spending and income volatility. Prior literature suggests that the overall stability of the economy and level of welfare support for individuals from the structural environment contributes to consumers’ debt problems. In terms of cultural influence, the conspicuous consumption theory in consumer behaviour suggests that consumers would spend more than their means to be seen as similar profiles to consumers in a higher socio-economic class. This results in consumers taking on more debt than they can afford, and eventually becoming over-indebted. Studies have also shown that financial literacy is negatively related to consumer over-indebtedness risk. Whilst prior literature has examined structural and cultural influences respectively, no study has taken a collective approach. To address this gap, a model is developed to investigate the association between consumer over-indebtedness and proxies for influences from the structural and cultural environment based on the above theories. The model also controls for consumer demographic characteristics identified as being of influence in prior literature, such as gender and age, and adverse shocks, such as divorce or bereavement in the household. Benefiting from SOEP regional data, this study is able to conduct quantitative empirical analysis to test both structural and cultural influences at a localised level. Using German Socio-Economic Panel (SOEP) study data from 2006 to 2016, this study finds that social benefits, financial literacy and the existence of conspicuous consumption all contribute to being over-indebted. Generally speaking, the risk of becoming over-indebted is high when consumers are in a low-welfare community, have little awareness of their own financial situation and always over-spend. In order to tackle the problem of over-indebtedness, countermeasures can be taken, for example, increasing consumers’ financial awareness, and the level of welfare support. By analysing causes of consumer over-indebtedness in Germany, this study also provides new insights on the nature and underlying causes of consumer debt issues in Europe.

Keywords: consumer, debt, financial literacy, socio-economic

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Authors: Kelvin Lo

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Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Hayam Qayyum

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Print and Broadcast media are considered to be the most powerful social change agents and effective medium that can revolutionize the deter society into the civilized, responsible, composed society. Beside all major roles, imperative role of media is to highlight the human rights’ violation issues in order to provide awareness and to prevent society from the social evils and injustice. So, by pointing out the odds, media can lessen the magnitude of happenings within the society. For centuries, the “Silent Crime” i.e. Child Sexual Abuse (CSA) is gulping down the developing countries. This study will explore that how the appropriate Print and Broadcast media coverage can eliminate Child Sexual Abuse from the society. The immense challenge faced by the journalists today; is the accurate and ethical reporting and appropriate coverage to disclose the facts and deliver right message on the right time to lessen the social evils in the developing countries, by not harming the prestige of the victim. In case of CSA most of the victims and their families are not in favour to expose their children to media due to family norms and respect in the society. Media should focus on in depth information of CSA and use this coverage is to draw attention of the concern authorities to look into the matter for reforms and reviews in the system. Moreover, media as a change agent can bring such issue into the knowledge of the international community to make collective efforts with the affected country to eliminate the ‘Silent Crime’ from the society. The model country selected for this research paper is South Africa. The purpose of this research is not only to examine the existing reporting patterns and content of print and broadcast media coverage of South Africa but also aims to create awareness to eliminate Child Sexual abuse and indirectly to improve the condition of stake holders to overcome this social evil. The literature review method is used to formulate this paper. Trends of media content on CSA will be identified that how much amount and nature of information made available to the public through the media General view of media coverage on child sexual abuse in developing countries like India and Pakistan will also be focused. This research will be limited to the role of print and broadcast media coverage to eliminate child sexual abuse in South Africa. In developing countries, CSA issue needs to be addressed on immediate basis. The study will explore the CSA content of the most influential broadcast and print media outlets of South Africa. Broadcast media will be comprised of TV channels and print media will be comprised of influential newspapers. South Africa is selected as a model for this research paper.

Keywords: child sexual abuse, developing countries, print and broadcast media, South Africa

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Joseph Salim

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This paper proposes the development of a supervised machine learning system to predict the consequences of untreated bruxism (teeth grinding) on gingival (gum) recession and jaw pain (most often bilateral jaw pain with possible headaches and limited ability to open the mouth). As a general dentist in a multi-specialty practice, the author has encountered many patients suffering from these issues due to uncontrolled bruxism (teeth grinding) at night. The most effective treatment for managing this problem involves wearing a nightguard during sleep and receiving therapeutic Botox injections to relax the muscles (the masseter muscle) responsible for grinding. However, some patients choose to postpone these treatments, leading to potentially irreversible and costlier consequences in the future. The proposed machine learning model aims to track patients who forgo the recommended treatments and assess the percentage of individuals who will experience worsening jaw pain, gingival (gum) recession, or both within a 3-to-5-year timeframe. By accurately predicting these outcomes, the model seeks to motivate patients to address the root cause proactively, ultimately saving time and pain while improving quality of life and avoiding much costlier treatments such as full-mouth rehabilitation to help recover the loss of vertical dimension of occlusion due to shortened clinical crowns because of bruxism, gingival grafts, etc.

Keywords: artificial intelligence, machine learning, predictive insights, bruxism, teeth grinding, therapeutic botox, nightguard, gingival recession, gum recession, jaw pain

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Authors: Hang Ju, Changmin Zhu

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The development level of the BeiDou Navigation Satellite System (BDS) can strongly reflect national defense strength as an important spatial information infrastructure. BDS can be not only used for military purposes, such as intelligence gathering, nuclear explosion monitoring, emergency communications, but also for location services, transportation, mapping, precision agriculture. In order to ensure the national defense security and the wide application of BDS in civil and military areas, BDS must be autonomous and controllable. As a complex system of knowledge-intensive, knowledge transformation runs through the whole process of research and development, production, operation, and maintenance of BDS. Based on the perspective of knowledge transformation, this paper expounds on the meaning of socialization, externalization, combination, and internalization of knowledge transformation, and the coupling relationship of autonomy and control on the basis of analyzing the status quo and problems of the autonomy and control of BDS. The autonomous and controllable framework of BDS based on knowledge transformation is constructed from six dimensions of management capability, R&D capability, technical capability, manufacturing capability, service support capability, and application capability. It can provide support for the smooth implementation of information security policy, provide a reference for the autonomy and control of the upstream and downstream industrial chains in Beidou, and provide a reference for the autonomous and controllable research of aerospace components, military measurement test equipment, and other related industries.

Keywords: knowledge transformation, BeiDou Navigation Satellite System, autonomy and control, framework

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Authors: Kapil Khanna, Swee Kuik, Joowon Ban

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The current linear economic system is unsustainable due to its dependence on the uncontrolled exploitation of diminishing natural resources. The integration of business innovation and supply chain management has brought about the redesign of business processes through the implementation of a closed-loop approach. The circular economy (CE) offers a sustainable solution to improve business opportunities in the near future by following the principles of rejuvenation and reuse inspired by nature. Those business owners start to rethink and consider using waste as raw material to make new products for consumers. The implementation of CE helps organisations to incorporate new strategic plans for decreasing the use of virgin materials and nature resources. Supply chain partners that are geographically dispersed rely heavily on innovative approaches to support supply chain management. Presently, numerous studies have attempted to establish the concept of supply chain management (SCM) by integrating CE principles, which are commonly denoted as circular SCM. While many scholars have recognised the challenges of transitioning to CE, there is still a lack of consensus on business best practices that can facilitate companies in embracing CE across the supply chain. Hence, this paper strives to scrutinize the SCM practices utilised for CE, identify the obstacles, and recommend best practices that can enhance a company's ability to incorporate CE principles toward business innovation and supply chain performance. Further, the paper proposes future research in the field of using specific technologies such as artificial intelligence, Internet of Things, and blockchain as business innovation tools for supply chain management and CE adoption.

Keywords: business innovation, challenges, circular supply chain, supply chain management, technology

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Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi

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Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.

Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir

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Authors: Jasmin Cowin

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Augmented reality digital technologies, big data, and the need for a teacher workforce able to meet the demands of a knowledge-based society are poised to lead to major changes in the field of education. This paper explores applications and educational use cases of augmented reality digital technologies for educational organizations during the Fourth Industrial Revolution. The Fourth Industrial Revolution requires vision, flexibility, and innovative educational conduits by governments and educational institutions to remain competitive in a global economy. Educational organizations will need to focus on teaching in and for a digital age to continue offering academic knowledge relevant to 21st-century markets and changing labor force needs. Implementation of contemporary disciplines will need to be embodied through learners’ active knowledge-making experiences while embracing ubiquitous accessibility. The power of distributed ledger technology promises major streamlining for educational record-keeping, degree conferrals, and authenticity guarantees. Augmented reality digital technologies hold the potential to restructure educational philosophies and their underpinning pedagogies thereby transforming modes of delivery. Structural changes in education and governmental planning are already increasing through intelligent systems and big data. Reimagining and redesigning education on a broad scale is required to plan and implement governmental and institutional changes to harness innovative technologies while moving away from the big schooling machine.

Keywords: fourth industrial revolution, artificial intelligence, big data, education, augmented reality digital technologies, distributed ledger technology

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Authors: Susanne Ferschl, Peter Holzmüller, Elisabeth Wacker

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Ageing populations, advances in medical sciences and digitalization, diversity and social disparities, as well as the increasing need for skilled healthcare professionals, are challenging healthcare systems around the globe. To address these challenges, future healthcare systems need to center on human needs taking into account the living environments that shape individuals’ knowledge of and opportunities to access healthcare. Moreover, health should be considered as a common good and an integral part of securing livelihoods for all people. Therefore, the adoption of a systems approach, as well as inter-disciplinary and inter-sectoral cooperation among healthcare providers, are essential. Additionally, the active engagement of target groups in the planning and design of healthcare structures is indispensable to understand and respect individuals’ health and livelihood needs. We will present the research project b4 – identifying needs | building bridges | developing health care in the social space, which is situated within this reasoning and accompanies the cross-sectoral cooperation project Brückenschlag (building bridges) in a Bavarian district. Brückenschlag seeks to explore effective ways of health care linking university medicine (Maximalversorgung | maximum care) with regional inpatient, outpatient, rehabilitative, and preventive care structures (Regionalversorgung | regional care). To create advantages for both (potential) patients and the involved cooperation partners, project b4 qualitatively assesses needs and motivations among professionals, population groups, and political stakeholders at individual and collective levels. Besides providing an overview of the project structure as well as of regional population and healthcare characteristics, the first results of qualitative interviews conducted with different health experts will be presented. Interviewed experts include managers of participating hospitals, nurses, medical specialists working in the hospital and registered doctors operating in practices in rural areas. At the end of the project life and based on the identified factors relevant to the success -and also for failure- of participatory cooperation in health care, the project aims at informing other districts embarking on similar systems-oriented and human-centered healthcare projects. Individuals’ health care needs in dependence on the social space in which they live will guide the development of recommendations.

Keywords: cross-sectoral collaboration in health care, human-centered health care, regional health care, individual and structural health conditions

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: Nawal Yacoub Halim Abdelmasih

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The intersection between development and human rights has been the factor of scholarly debate for a long term. therefore, some of standards, which enlarge from the proper to development to the human rights-based totally method to development, had been adopted to apprehend the dynamics among the two standards. no matter these attempts, the exact relationship among improvement and human rights has not been completely determined but. however, the inevitable interdependence between the two notions and the idea that improvement efforts ought to be undertaken with the aid of giving due regard to human rights ensures has won momentum in recent years. then again, the emergence of sustainable development as a extensively common technique in development dreams and policies makes this unsettled convergence even extra complicated. The vicinity of sustainable improvement in human rights regulation discourse and the function of the latter in making sure the sustainability of development applications name for a scientific observe. as a result, this newsletter seeks to discover the relationship among development and human rights, particularly focusing at the location given to sustainable development principles in international human proper regulation. it'll similarly quest whether or not there is a proper to sustainable improvement diagnosed therein. as a result, the item asserts that the ideas of sustainable improvement are immediately or circuitously diagnosed in diverse human rights contraptions, which affords an affirmative response to the question raised hereinabove. This paintings, therefore, will make expeditions via international and regional human rights devices in addition to case legal guidelines and interpretative hints of human rights bodies to show this speculation.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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Authors: O. V. Jurieva, O. U. Jurieva, R. H. Yagudin, P. B. Chursin

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In the recent scientific researches on the problems of public service the idea of the use of innovative technologies of management of personnel processes is accurately formulated. Authors made an attempt to analyze the changes in the public service organizations and to understand how the studied situation is interpreted by the government employees themselves. For this purpose the strategy of sociological research was carried out on the basis of application of questionnaire developed by M. Rokich and focus group research. For the research purposes it was necessary to get to microlevel in order to include daily activities of employees of an organization, their life experience and values in the focus of the analysis. Based on P. Bourdieu's methodology, authors investigated the established patterns of consciousness and behavior of officials (doxa) and also analyzed the tendencies of re-thinking (change) of the settled content of values (heterodoxy) by them. The distinctive feature of the conducted research is that the public servants who have different length of service in the public service took part in the research procedure. The obtained data helped to answer the following question: what are the specifics of doxs of the public servants who work in the public civil service more than 7-10 years and what perception of values of civil service have junior experts whose work experience doesn't exceed 3 years. Respondents were presented by two groups: (1) public servants of the level of main positions in the public civil service of the Republic of Tatarstan. (2) Public servants of the level of lower positions in the ministries and departments of the Republic of Tatarstan. For the study of doxa or of the existing values of public servants, the research with use of the questionnaire based on M. Rokich's system is conducted. Two types of values are emphasised: terminal and instrumental, which are united by us in the collective concept doxa. Doxa: the instrument of research of the established patterns of consciousness and behavior which can either resist to changes in the organization or, on the contrary, support their implementation. In the following stage an attempt to deepen our understanding of the essence and specifics of doxa of officials by means of the applied sociological research which is carried out by focus group method is made. Information obtained by authors during the research convinces that for the success of policy of changes in the organizations of public service it is necessary to develop special technologies of informing employees about the essence and inevitability of the developed innovations, to involve them in the process of changes, to train and to develop the younger generation of civil servants, seriously to perceive additional training and retraining of officials.

Keywords: innovative technologies, public service organizations, public servants

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Authors: Shivaram P. Arunachalam, Mustafa Y. Sir, Andy Boggust, David M. Nestler, Thomas R. Hellmich, Kalyan S. Pasupathy

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Emergency departments (EDs) provide urgent care to patients throughout the day in a complex and chaotic environment. Real-time location systems (RTLS) are increasingly being utilized in healthcare settings, and have shown to improve safety, reduce cost, and increase patient satisfaction. Radio Frequency Identification Device (RFID) data in an ED has been shown to compute variables such as patient-provider contact time, which is associated with patient outcomes such as 30-day hospitalization. These variables can provide avenues for improving ED operational efficiency. A major challenge with ED financial operations is under-coding of critical care services due to physicians’ difficulty reporting accurate times for critical care provided under Current Procedural Terminology (CPT) codes 99291 and 99292. In this work, the authors propose a framework to optimize ED critical care billing using RFID data. RFID estimated physician-patient contact times could accurately quantify direct critical care services which will help model a data-driven approach for ED critical care billing. This paper will describe the framework and provide insights into opportunities to prevent under coding as well as over coding to avoid insurance audits. Future work will focus on data analytics to demonstrate the feasibility of the framework described.

Keywords: critical care billing, CPT codes, emergency department, RFID

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Amanda Aliende da Matta, Maria del Pilar Fogueiras Bertomeu, Valeria de Ormaechea Otalora, Maria Paz Sandin Esteban, Miriam Comet Donoso

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This communication presents the preliminary emerging themes in a research on political participation of young women. The study follows a qualitative methodology; in particular, the applied hermeneutic phenomenological method, and the general objective of the research is to give an account of the experience of political participation as young women. The study participants are women aged 18 to 35 who have experience in political participation. The techniques of data collection are the descriptive story and the phenomenological interview. With respect to the first methodological steps, these have been: 1) collect and select stories of lived experience in political participation, 2) select descriptions of lived experience (DLEs) in political participation of the chosen stories, 3) to prepare phenomenological interviews from the selected DLEs, 4) to conduct phenomenological thematic analysis (PTA) of the DLEs. We have so far initiated the PTA on 5 vignettes. Hermeneutic phenomenology as a research approach is based on phenomenological philosophy and applied hermeneutics. Phenomenology is a descriptive philosophy of pure experience and essences, through which we seek to capture an experience at its origins without categorizing, interpreting or theorizing it. Hermeneutics, on the other hand, may be defined as a philosophical current that can be applied to data analysis. Max Van Manen wrote that hermeneutic phenomenology is a method of abstemious reflection on the basic structures of the lived experience of human existence. In hermeneutic phenomenology we focus, then, on the way we experience “things” in the first person, seeking to capture the world exactly as we experience it, not as we categorize or conceptualize it. In this study, the empirical methods used were: Lived experience description (written) and conversational interview. For these short stories, participants were asked: “What was your lived experience of participation in politics as a young woman? Can you tell me any stories or anecdotes that you think exemplify or typify your experience?”. The questions were accompanied by a list of guidelines for writing descriptive vignettes. And the analytical method was PTA. Among the provisional results, we found preliminary emerging themes, which could in the advance of the investigation result in meaning structures of political participation of young women. They are the following: - Complicity may be inherent/essential in political participation as a young woman; - Feelings may be essential/inherent in political participation as a young woman; - Hope may be essential in authentic political participation as a young woman; - Frustration may be essential in authentic political participation as a young woman; - Satisfaction may be essential in authentic political participation as a young woman; - There may be tension between individual/collective inherent/essential in political participation as a young woman; - Political participation as a young woman may include moments of public demonstration.

Keywords: applied hermeneutic phenomenology, hermeneutics, phenomenology, political participation

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

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Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

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Authors: Ali Riza Perçin, Eser Bingül

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Internet technologies have created opportunities with which people share their ideologies, thoughts and products. This virtual world, named social media has given the chance of gathering individual users and people from the world's remote locations and establishing an interaction between them. However, to an increasingly higher degree terrorist organizations today use the internet and most notably social-network media to create the effects they desire through a series of on-line activities. These activities, designed to support their activities, include information collection (intelligence), target selection, propaganda, fundraising and recruitment to name a few. Meanwhile, these have been used as the most important tool for recruitment especially from the different region of the world, especially disenfranchised youth, in the West in order to mobilize support and recruit “foreign fighters.” The recruits have obtained the statue, which is not accessible in their society and have preferred the style of life that is offered by the terrorist organizations instead of their current life. Like other terrorist groups, for a while now the terrorist organization Islamic State (IS) in Iraq and Syria has employed a social-media strategy in order to advance their strategic objectives. At the moment, however, IS seems to be more successful in their on-line activities than other similar organizations. IS uses social media strategically as part of its armed activities and for the sustainability of their military presence in Syria and Iraq. In this context, “Generation Y”, which could exist at the critical position and undertake active role, has been examined. Additionally, the explained characteristics of “Generation Y” have been put forward and the duties of families and society have been stated as well.

Keywords: social media, "generation Y", terrorist organization, islamic state IS

Procedia PDF Downloads 427