Search results for: sequential decision making

Authors: Eric Pla Erra, Mariana Jimenez Martinez

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While aggregated loads at a community level tend to be easier to predict, individual household load forecasting present more challenges with higher volatility and uncertainty. Furthermore, the drastic changes that our behavior patterns have suffered due to the COVID-19 pandemic have modified our daily electrical consumption curves and, therefore, further complicated the forecasting methods used to predict short-term electric load. Load forecasting is vital for the smooth and optimized planning and operation of our electric grids, but it also plays a crucial role for individual domestic consumers that rely on a HEMS (Home Energy Management Systems) to optimize their energy usage through self-generation, storage, or smart appliances management. An accurate forecasting leads to higher energy savings and overall energy efficiency of the household when paired with a proper HEMS. In order to study how COVID-19 has affected the accuracy of forecasting methods, an evaluation of the performance of a state-of-the-art LGBM (Light Gradient Boosting Model) will be conducted during the transition between pre-pandemic and lockdowns periods, considering day-ahead electric load forecasting. LGBM improves the capabilities of standard Decision Tree models in both speed and reduction of memory consumption, but it still offers a high accuracy. Even though LGBM has complex non-linear modelling capabilities, it has proven to be a competitive method under challenging forecasting scenarios such as short series, heterogeneous series, or data patterns with minimal prior knowledge. An adaptation of the LGBM model – called “resilient LGBM” – will be also tested, incorporating a concept drift detection technique for time series analysis, with the purpose to evaluate its capabilities to improve the model’s accuracy during extreme events such as COVID-19 lockdowns. The results for the LGBM and resilient LGBM will be compared using standard RMSE (Root Mean Squared Error) as the main performance metric. The models’ performance will be evaluated over a set of real households’ hourly electricity consumption data measured before and during the COVID-19 pandemic. All households are located in the city of Barcelona, Spain, and present different consumption profiles. This study is carried out under the ComMit-20 project, financed by AGAUR (Agència de Gestiód’AjutsUniversitaris), which aims to determine the short and long-term impacts of the COVID-19 pandemic on building energy consumption, incrementing the resilience of electrical systems through the use of tools such as HEMS and artificial intelligence.

Keywords: concept drift, forecasting, home energy management system (HEMS), light gradient boosting model (LGBM)

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Authors: Saddam Hussain, Ghadeer Mohsen Albadrani

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Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.

Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain

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Authors: Enes Huylu, Sude Erkin, Nur A. Özdemir, Hatice K. Güney, Cemre S. Atılgan, Hüseyin Y. Altıntaş, Aysemin Top, Muammer Yılman, Özak Durmuş

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Remanufacturing (reman) applications allow manufacturers to contribute to the circular economy and help to introduce products with almost the same quality, environment-friendly, and lower cost. The objective of this study is to present that the carbon footprint of automotive spare parts used in vehicles could be reduced by reman applications based on Life Cycle Analysis which was framed with ISO 14040 principles. In that case, it was aimed to investigate reman applications for 21 parts in total. So far, research and calculations have been completed for the alternator, turbocharger, starter motor, compressor, manual transmission, auto transmission, and DPF (diesel particulate filter) parts, respectively. Since the aim of Ford Motor Company and Ford OTOSAN is to achieve net zero based on Science-Based Targets (SBT) and the Green Deal that the European Union sets out to make it climate neutral by 2050, the effects of reman applications are researched. In this case, firstly, remanufacturing articles available in the literature were searched based on the yearly high volume of spare parts sold. Paper review results related to their material composition and emissions released during incoming production and remanufacturing phases, the base part has been selected to take it as a reference. Then, the data of the selected base part from the research are used to make an approximate estimation of the carbon footprint reduction of the relevant part used in Ford OTOSAN. The estimation model is based on the weight, and material composition of the referenced paper reman activity. As a result of this study, it was seen that remanufacturing applications are feasible to apply technically and environmentally since it has significant effects on reducing the emissions released during the production phase of the vehicle components. For this reason, the research and calculations of the total number of targeted products in yearly volume have been completed to a large extent. Thus, based on the targeted parts whose research has been completed, in line with the net zero targets of Ford Motor Company and Ford OTOSAN by 2050, if remanufacturing applications are preferred instead of recent production methods, it is possible to reduce a significant amount of the associated greenhouse gas (GHG) emissions of spare parts used in vehicles. Besides, it is observed that remanufacturing helps to reduce the waste stream and causes less pollution than making products from raw materials by reusing the automotive components.

Keywords: greenhouse gas emissions, net zero targets, remanufacturing, spare parts, sustainability

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Authors: D. Mulligan, D. Casey

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Introductory Statement: Delegation is when a registered nurse (RN) transfers a task or activity that is normally within their scope of practice to another person (delegatee). RN delegation is common practice with unregistered staff, e.g., student nurses and health care assistants (HCAs). As the role of the HCA is increasingly embedded as a direct care and support role, especially in long-term residential care for older adults, there is RN uncertainty as to their role as a delegator. The assignment is when a task is transferred to a person that is within the role specification of the delegatee. RNs in long-term care (LTC) for older people are increasingly working in teams where there are less RNs and more HCAs providing direct care to the residents. The RN is responsible and accountable for their decision to delegate and assign tasks to HCAs. In an interpretive, multiple case studies to explore how delegation of tasks by RNs to HCAs occurred in long-term care settings in Ireland the importance of the RN understanding their scope of practice emerged. Methodology: Focus group interviews and individual interviews were undertaken as part of a multiple case study. Both cases, anonymized as Case A and Case B, were within the public health service in Ireland. The case study sites were long-term care settings for older adults located in different social care divisions, and in different geographical areas. Four focus group interviews with staff nurses and three individual interviews with CNMs were undertaken. The interactive data analysis approach was the analytical framework used, with within-case and cross-case analysis. The theoretical lens of organizational role theory, applying the role episode model (REM), was used to understand, interpret, and explain the findings. Study Findings: RNs and CNMs understood the role of the nurse regulator and the scope of practice. RNs understood that the RN was accountable for the care and support provided to residents. However, RNs and CNM2s could not describe delegation in the context of their scope of practice. In both cases, the RNs did not have a standardized process for assessing HCA competence to undertake nursing tasks or interventions. RNs did not routinely supervise HCAs. Tasks were assigned and not delegated. There were differences between the cases in relation to understanding which nursing tasks required delegation. HCAs in Case A undertook clinical vital sign assessments and documentation. HCAs in Case B did not routinely undertake these activities. Delegation and assignment were influenced by the organizational factors, e.g., model of care, absence of delegation policies, inadequate RN education on delegation, and a lack of RN and HCA role clarity. Concluding Statement: Nurse staffing levels and skill mix in long-term care settings continue to change with more HCAs providing more direct care and support. With decreasing RN staffing levels RNs will be required to delegate and assign more direct care to HCAs. There is a requirement to distinguish between RN assignment and delegation at policy, regulation, and organizational levels.

Keywords: assignment, delegation, registered nurse, scope of practice

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Authors: Janice Keener, Christine Houlihan

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Over the last several years, there has been an increase in children identified as having Autism Spectrum Disorder (ASD). Specialists across several disciplines: mental health and medical professionals have been tasked with ensuring accurate and timely evaluations for children with suspected ASD. Due to the nature of the ASD symptom presentation, an interdisciplinary assessment and treatment approach best addresses the needs of the whole child. During the unprecedented COVID-19 Pandemic, clinicians were faced with how to continue with interdisciplinary assessments in a telehealth arena. Instruments that were previously used to assess ASD in-person were no longer appropriate measures to use due to the safety restrictions. For example, The Autism Diagnostic Observation Schedule requires examiners and children to be in very close proximity of each other and if masks or face shields are worn, they render the evaluation invalid. Similar issues arose with the various cognitive measures that are used to assess children such as the Weschler Tests of Intelligence and the Differential Ability Scale. Thus the need arose to identify measures that are able to be safely and accurately administered using safety guidelines. The incidence of ASD continues to rise over time. Currently, the Center for Disease Control estimates that 1 in 59 children meet the criteria for a diagnosis of ASD. The reasons for this increase are likely multifold, including changes in diagnostic criteria, public awareness of the condition, and other environmental and genetic factors. The rise in the incidence of ASD has led to a greater need for diagnostic and treatment services across the United States. The uncertainty of the diagnostic process can lead to an increased level of stress for families of children with suspected ASD. Along with this increase, there is a need for diagnostic clarity to avoid both under and over-identification of this condition. Interdisciplinary assessment is ideal for children with suspected ASD, as it allows for an assessment of the whole child over the course of time and across multiple settings. Clinicians such as Psychologists and Developmental Pediatricians play important roles in the initial evaluation of autism spectrum disorder. An ASD assessment may consist of several types of measures such as standardized checklists, structured interviews, and direct assessments such as the ADOS-2 are just a few examples. With the advent of telehealth clinicians were asked to continue to provide meaningful interdisciplinary assessments via an electronic platform and, in a sense, going to the family home and evaluating the clinical symptom presentation remotely and confidently making an accurate diagnosis. This poster presentation will review the benefits, limitations, and interpretation of these various instruments. The role of other medical professionals will also be addressed, including medical providers, speech pathology, and occupational therapy.

Keywords: Autism Spectrum Disorder Assessments, Interdisciplinary Evaluations , Tele-Assessment with Autism Spectrum Disorder, Diagnosis of Autism Spectrum Disorder

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Authors: Ronit Chakraborty

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Kolkata, formerly known as Calcutta, is the capital of West Bengal state and the former capital of India (1722-1911) of British India. Located at the heart of Hugli river (one of the main channels of Ganges river), the city is the heart of the state, which forms a base for commerce, transport and manufacture. The large and vibrant city thrives amidst the economic, social and political issues arising from the pages of history to the contemporary times. The unique nature, grandeurs, public debates on tea-stalls and obviously the charismatic scenic beauty and heritage keep the city to be criticized in all horizons, across the world. Movies in India are a big source of knowledge, which can be used as a powerful tool for political mobilization and to indirectly communicate with voters since cinema can be used as a tool of propaganda as it has a wide range of public interests. History proves the fact that films produced in India have been apt enough in making public interests be deeply portrayed through their content in a versatile manner. Such is the portrayal of India’s first capital, Kolkata and its ultimate truth being organizingly laid over by the trilogy of two international fame directors-Mrinal Sen and Satyajit Ray, through their ‘magnum opus- the ‘Kolkata trilogy’. Mrinal Sen’s Interview(1971), Calcutta 71(1972), Padatik(The Guerilla Fighter)(1973) and Satyajit Ray’s Pratidwandi (The Adversary)(1970), Seemabaddha(Company Limited)(1971), Jana Aranya(1976). These films picturized the contemporary Kolkata trends, issues and crises arising amidst the political set-up both by the positive and negative variables attributing to the day-to-day happenings of the city. The movies have been set amidst the turmoil that the nation was going through during Indira Gandhi’s declaration of Emergency, resulting from the general sense of disillusionment that prevailed during that time. Ray wasn't affiliated to any political party and his films largely contributed towards the contemporary conditions prevailing in the society. Mrinal Sen, being a Marxist was in constant search of the bitter truth that the society had to offer through his lens under the prevailing darkness through his trilogy. The research paper attempts to widely view and draw a comparative study of the overall description of the city of Kolkata as portrayed by Sen and Ray in their respective trilogies. By the usage of the visual content analysis method, the researcher has explored the six movies; both the trilogies of Mrinal Sen and Satyajit Ray and tried to analyse the differences as well as the similarities pertaining to understand India’s first capital city Kolkata in various dimensions along with its circumference.

Keywords: Kolkata, trilogy, Satyajit Ray, Mrinal Sen, films, comparative study

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Authors: Pui Hong Chung, Cyrus Leung, Jun Li, Kin On Kwok, Ek Yeoh

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Introduction: Studies for TB control in intermediate tuberculosis burden countries (IBCs) comprise a relatively small proportion in TB control literature, as compared to the effort put in high and low burden counterparts. It currently lacks of consensus in the optimal weapons and strategies we can use to combat TB in IBCs; guidelines of TB control are inadequate and thus posing a great obstacle in eliminating TB in these countries. To fill-in the research and services gap, we need to summarize the findings of the effort in this regard and to seek consensus in terms of policy making for TB control, we have devised a series of scoping and Delphi studies for these purposes. Method: The scoping and Delphi studies are conducted in parallel to feed information for each other. Before the Delphi iterations, we have invited three local experts in TB control in Hong Kong to participate in the pre-assessment round of the Delphi study to comments on the validity, relevance, and clarity of the Delphi questionnaire. Result: Two scoping studies, regarding LTBI control in health care workers in IBCs and TB control in elderly of IBCs respectively, have been conducted. The result of these two studies is used as the foundation for developing the Delphi questionnaire, which tapped on seven areas of question, namely: characteristics of IBCs, adequacy of research and services in LTBI control in IBCs, importance and feasibility of interventions for TB control and prevention in hospital, screening and treatment of LTBI in community, reasons of refusal to/ default from LTBI treatment, medical adherence of LTBI treatment, and importance and feasibility of interventions for TB control and prevention in elderly in IBCs. The local experts also commented on the two scoping studies conducted, thus act as the sixth phase of expert consultation in Arksey and O’Malley framework of scoping studies, to either nourish the scope and strategies used in these studies or to supplement ideas for further scoping or systematic review studies. In the subsequent stage, an international expert panel, comprised of 15 to 20 experts from IBCs in Western Pacific Region, will be recruited to join the two-round anonymous Delphi iterations. Four categories of TB control experts, namely clinicians, policy makers, microbiologists/ laboratory personnel, and public health clinicians will be our target groups. A consensus level of 80% is used to determine the achievement of consensus on particular issues. Key messages: 1. Scoping review and Delphi method are useful to identify gaps and then achieve consensus in research. 2. Lots of resources are put in the high burden countries now. However, the usually neglected intermediate-burden countries with TB is an indispensable part for achieving the ambitious WHO End TB 2035 target.

Keywords: dephi questionnaire, tuberculosis, WHO, latent TB infection

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Authors: Jill Round

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In the economic system, the financial sector plays a crucial role as an intermediary between market participants, other financial institutions, and customers. Financial institutions such as banks have to make decisions to satisfy the demands of all the participants by keeping abreast of regulatory change. In recent years, progress has been made regarding frameworks, development of rules, standards, and processes to manage risks in the banking sector. The increasing focus of regulators and policymakers placed on risk management, corporate governance, and the organization’s culture is of special interest as it requires a well-resourced risk controlling function, compliance function, and internal audit function. In the past years, the relevance of these functions that make up the so-called Three Lines of Defense has moved from the backroom to the boardroom. The approach of the model can vary based on the various organizational characteristics. Due to the intense regulatory requirements, organizations operating in the financial sector have more mature models. In less regulated industries there is more cloudiness about what tasks are allocated where. All parties strive to achieve their objectives through the effective management of risks and serve the identical stakeholders. Today, the Three Lines of Defense model is used throughout the world. The research looks at trends and emerging issues in the professions of the Three Lines of Defense within the banking sector. The answers are believed to helping to explain the increasing regulatory requirements for the banking sector. While the number of supervisory practices increases the risk management requirements intensify and demand more regulatory compliance at the same time. The Structural Equation Modeling (SEM) is applied by making use of conducted surveys in the research field. It aims to describe (i) the theoretical model regarding the applicable linearity relationships, (ii) the causal relationship between multiple predictors (exogenous) and multiple dependent variables (endogenous), (iii) taking into consideration the unobservable variables and (iv) the measurement errors. The surveys conducted on the research field suggest that the observable variables are caused by various latent variables. The SEM consists of the 1) measurement model and the 2) structural model. There is a detectable correlation regarding the cause-effect relationship among the performed supervisory practices and the increasing scope of regulation. Supervisory practices reinforce the regulatory density. In the past, controls were placed after supervisory practices were conducted or incidents occurred. In further research, it is of interest to examine, whether risk management is proactive, reactive to incidents and supervisory practices or can be both at the same time.

Keywords: risk management, structural equation model, supervisory practice, three lines of defense

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Authors: Elizabeth Parrott, Harry Pointon, Frederic Bezombes, Heather Panter

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Unmanned aerial vehicles (UAV’s) are making a profound effect within policing, forensic and fire service procedures worldwide. These intelligent devices have already proven useful in photographing and recording large-scale outdoor and indoor sites using orthomosaic and three-dimensional (3D) modelling techniques, for the purpose of capturing and recording sites during and post-incident. UAV’s are becoming an established tool as they are extending the reach of the photographer and offering new perspectives without the expense and restrictions of deploying full-scale aircraft. 3D reconstruction quality is directly linked to the resolution of captured images; therefore, close proximity flights are required for more detailed models. As technology advances deployment of UAVs in confined spaces is becoming more common. With this in mind, this study investigates the effects of UAV operation within active crimes scenes with regard to the dispersal of particulate evidence. To date, there has been little consideration given to the potential effects of using UAV’s within active crime scenes aside from a legislation point of view. Although potentially the technology can reduce the likelihood of contamination by replacing some of the roles of investigating practitioners. There is the risk of evidence dispersal caused by the effect of the strong airflow beneath the UAV, from the downwash of the propellers. The initial results of this study are therefore presented to determine the height of least effect at which to fly, and the commercial propeller type to choose to generate the smallest amount of disturbance from the dataset tested. In this study, a range of commercially available 4-inch propellers were chosen as a starting point due to the common availability and their small size makes them well suited for operation within confined spaces. To perform the testing, a rig was configured to support a single motor and propeller powered with a standalone mains power supply and controlled via a microcontroller. This was to mimic a complete throttle cycle and control the device to ensure repeatability. By removing the variances of battery packs and complex UAV structures to allow for a more robust setup. Therefore, the only changing factors were the propeller and operating height. The results were calculated via computer vision analysis of the recorded dispersal of the sample particles placed below the arm-mounted propeller. The aim of this initial study is to give practitioners an insight into the technology to use when operating within confined spaces as well as recognizing some of the issues caused by UAV’s within active crime scenes.

Keywords: dispersal, evidence, propeller, UAV

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Authors: Shimeles Terefe Mengistue, Ascensión Del Olmo, Paola Marziani, Mirjana Pović, María Angeles Martínez-Carballo, Jaime Perea, Isabel M. Árquez

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Quasars have historically been classified into two distinct classes, radio-loud (RL) and radio-quiet (RQ), taking into account the presence and absence of relativistic radio jets, respectively. The absence of spectra with a high S/N ratio led to the impression that all quasars (QSOs) are spectroscopically similar. Although different attempts were made to unify these two classes, there is a long-standing open debate involving the possibility of a real physical dichotomy between RL and RQ quasars. In this work, we present new high S/N spectra of 11 extremely powerful jetted quasars with radio-to-optical flux density ratio > 1000 that concomitantly cover the low-ionization emission of Mgii𝜆2800 and Hbeta𝛽 as well as the Feii blends in the redshift range 0.35 < z < 1, observed at Calar Alto Observatory (Spain). This work aims to quantify broad emission line differences between RL and RQ quasars by using the four-dimensional eigenvector 1 (4DE1) parameter space and its main sequence (MS) and to check the effect of powerful radio ejection on the low ionization broad emission lines. Emission lines are analysed by making two complementary approaches, a multicomponent non-linear fitting to account for the individual components of the broad emission lines and by analysing the full profile of the lines through parameters such as total widths, centroid velocities at different fractional intensities, asymmetry, and kurtosis indices. It is found that broad emission lines show large reward asymmetry both in Hbeta𝛽 and Mgii2800A. The location of our RL sources in a UV plane looks similar to the optical one, with weak Feii UV emission and broad Mgii2800A. We supplement the 11 sources with large samples from previous work to gain some general inferences. The result shows, compared to RQ, our extreme RL quasars show larger median Hbeta full width at half maximum (FWHM), weaker Feii emission, larger 𝑀BH, lower 𝐿bol/𝐿Edd, and a restricted space occupation in the optical and UV MS planes. The differences are more elusive when the comparison is carried out by restricting the RQ population to the region of the MS occupied by RL quasars, albeit an unbiased comparison matching 𝑀BH and 𝐿bol/𝐿Edd suggests that the most powerful RL quasars show the highest redward asymmetries in Hbeta.

Keywords: galaxies, active, line, profiles, quasars, emission lines, supermassive black holes

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Authors: Amir Hossein Ashari, Sedighe Erfan Manesh

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One of the problems in developing countries is renovating the historical context and inducing behaviors appropriate to modern life to such a context. This study was conducted using field and library methods in 2012. Similar cases carried out in Iran and developing countries were compared to unveil the strengths and weaknesses of these projects. At present, in the historical context of Shiraz, the distance between two religious shrines of Shahcheragh (Ahmad ibn Musa) and Astaneh (Sayed Alaa al-Din Hossein), which are significant places in religious, cultural, social, and economic terms, is an area full of historic places called Bein Al-Haramein. Unfortunately, some of these places have been worn out and are not appropriate for common uses. The basic strategy of Bein Al-Haramein was to improve social development of Shiraz, to enhance the vitality and dynamism of the historical context of Bein Al-Haramein and to create tourist attractions in order to boost the city's economic and social stability. To this end, the project includes the huge Bein Al-Haramein Commercial Complex which is under construction now. To construct the complex, officials have decided to demolish places of historical value which can lead to irreparable consequences. Iranian urban design has always been based on three elements of bazaars, mosques and government facilities with bazaars being the organic connector of the other elements. Therefore, the best strategy in the above case is to provide for a commercial connection between the two poles. Although this strategy is included in the project, lack of attention to renovation principles in this area and complete destruction of the context will lead to its irreversible damage and will destroy its cultural and historical identity. In urban planning of this project, some important issues have been neglected including: preserving valuable buildings and special old features of the city, rebuilding worn buildings and context to attract trust and confidence of the people, developing new models according to changes, improving the structural position of old context with minimal degradation, attracting partnerships of residents and protecting their rights and finally using potential facilities of the old context. The best strategy for achieving sustainability in Bein Al-Haramein can be the one used in the distance between Santa Maria Novella and Santa Maria Del Fiore churches in historical context where while protecting the historic context and constructions, old buildings were renovated and given different commercial and service uses making them sustainable and dynamic places. Similarly, in Bein Al-Haramein, renovating old constructions and monuments and giving different commercial and other uses to them can help improve the economic and social sustainability of the area.

Keywords: Bein Al-Haramein, sustainability, historical context, historical context

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Chrysthia Papacleovoulou

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The era of de-regulation, off-shore and tax haven jurisdictions, and shelf companies has come to an end. The usage of complex corporate structures involving trust instruments, special purpose vehicles, holding-subsidiaries in offshore haven jurisdictions, and taking advantage of tax treaties is soaring. States which raced to introduce corporate friendly legislation, tax incentives, and creative international trust law in order to attract greater FDI are now faced with regulatory challenges and are forced to revisit the corporate form and its tax treatment. The fiduciary services industry, which dominated over the last 3 decades, is now striving to keep up with the new regulatory framework as a result of a number of European and international legislative measures. This article considers the challenges to the company and the corporate form as a result of the legislative measures on tax planning and tax avoidance, CRS reporting, FATCA, CFC rules, OECD’s BEPS, the EU Commission's new transparency rules for intermediaries that extends to tax advisors, accountants, banks & lawyers who design and promote tax planning schemes for their clients, new EU rules to block artificial tax arrangements and new transparency requirements for financial accounts, tax rulings and multinationals activities (DAC 6), G20's decision for a global 15% minimum corporate tax and banking regulation. As a result, states are found in a race of over-regulation and compliance. These legislative measures constitute a global up-side down tax-harmonisation. Through the adoption of the OECD’s BEPS, states agreed to an international collaboration to end tax avoidance and reform international taxation rules. Whilst the idea was to ensure that multinationals would pay their fair share of tax everywhere they operate, an indirect result of the aforementioned regulatory measures was to attack private clients-individuals who -over the past 3 decades- used the international tax system and jurisdictions such as Marshal Islands, Cayman Islands, British Virgin Islands, Bermuda, Seychelles, St. Vincent, Jersey, Guernsey, Liechtenstein, Monaco, Cyprus, and Malta, to name but a few, to engage in legitimate tax planning and tax avoidance. Companies can no longer maintain bank accounts without satisfying the real substance test. States override the incorporation doctrine theory and apply a real seat or real substance test in taxing companies and their activities, targeting even the beneficial owners personally with tax liability. Tax authorities in civil law jurisdictions lift the corporate veil through the public registries of UBO Registries and Trust Registries. As a result, the corporate form and the doctrine of limited liability are challenged in their core. Lastly, this article identifies the development of new instruments, such as funds and private placement insurance policies, and the trend of digital nomad workers. The baffling question is whether industry and states can meet somewhere in the middle and exit this over-regulation frenzy.

Keywords: company, regulation, TAX, corporate structure, trust vehicles, real seat

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Authors: Rommila Chandra, Harshika Choudhary

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The value of integrated, participatory, and community based sustainable development strategies is eminent, but in practice, it still remains fragmentary and often leads to short-lived results. Despite the global presence of climate change, its impacts are felt differently by different communities based on their vulnerability. The developing countries have the low adaptive capacity and high dependence on environmental variables, making them highly susceptible to outmigration and poverty. We need to understand how to enable these approaches, taking into account the various governmental and non-governmental stakeholders functioning at different levels, to deliver long-term socio-economic and environmental well-being of local communities. The research assessed the financial and natural vulnerability of Himalayan networks, focusing on their potential to adapt to various changes, through accessing their perceived reactions and local knowledge. The evaluation was conducted by testing indices for vulnerability, with a major focus on indicators for adaptive capacity. Data for the analysis were collected from the villages around Govind National Park and Wildlife Sanctuary, located in the Indian Himalayan Region. The villages were stratified on the basis of connectivity via road, thus giving two kinds of human settlements connected and isolated. The study focused on understanding the complex relationship between outmigration and the socio-cultural sentiments of local people to not abandon their land, assessing their adaptive capacity for livelihood opportunities, and exploring their contribution that integrated participatory methodologies can play in delivering sustainable development. The result showed that the villages having better road connectivity, access to market, and basic amenities like health and education have a better understanding about the climatic shift, natural hazards, and a higher adaptive capacity for income generation in comparison to the isolated settlements in the hills. The participatory approach towards environmental conservation and sustainable use of natural resources were seen more towards the far-flung villages. The study helped to reduce the gap between local understanding and government policies by highlighting the ongoing adaptive practices and suggesting precautionary strategies for the community studied based on their local conditions, which differ on the basis of connectivity and state of development. Adaptive capacity in this study has been taken as the externally driven potential of different parameters, leading to a decrease in outmigration and upliftment of the human environment that could lead to sustainable livelihood development in the rural areas of Himalayas.

Keywords: adaptive capacity, Indian Himalayan region, participatory, sustainable livelihood development

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Stephanie Wall, Guido Wimmers

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The construction and operation of buildings greatly contribute to environmental degradation through resource and energy consumption and greenhouse gas emissions. The design of the envelope system affects the environmental impact of a building in two major ways; 1) high thermal performance and air tightness can significantly reduce the operational energy of the building and 2) the material selection for the envelope largely impacts the embodied energy of the building. Life cycle assessment (LCA) is a scientific methodology that is used to systematically analyze the environmental load of processes or products, such as buildings, over their life. The paper will discuss the results of a comparative LCA of different envelope designs and the long-term monitoring of the Wood Innovation Research Lab (WIRL); a Passive House (PH), industrial building under construction in Prince George, Canada. The WIRL has a footprint of 30m x 30m on a concrete raft slab foundation and consists of shop space as well as a portion of the building that includes a two-story office/classroom space. The lab building goes beyond what was previously thought possible in regards to energy efficiency of industrial buildings in cold climates due to their large volume to surface ratio, small floor area, and high air change rate, and will be the first PH certified industrial building in Canada. These challenges were mitigated through the envelope design which utilizes solar gains while minimizing overheating, reduces thermal bridges with thick (570mm) prefabricated truss walls filled with blown in mineral wool insulation and a concrete slab and roof insulated with EPS rigid insulation. The envelope design results in lower operational and embodied energy when compared to buildings built to local codes or with steel. The LCA conducted using Athena Impact Estimator for Buildings identifies project specific hot spots as well illustrates that for high-efficiency buildings where the operational energy is relatively low; the embodied energy of the material selection becomes a significant design decision as it greatly impacts the overall environmental footprint of the building. The results of the LCA will be reinforced by long-term monitoring of the buildings envelope performance through the installation of temperature and humidity sensors throughout the floor slab, wall and roof panels and through detailed metering of the energy consumption. The data collected from the sensors will also be used to reinforce the results of hygrothermal analysis using WUFI®, a program used to verify the durability of the wall and roof panels. The WIRL provides an opportunity to showcase the use of wood in a high performance envelope of an industrial building and to emphasize the importance of considering the embodied energy of a material in the early stages of design. The results of the LCA will be of interest to leading researchers and scientists committed to finding sustainable solutions for new construction and high-performance buildings.

Keywords: high performance envelope, life cycle assessment, long term monitoring, passive house, prefabricated panels

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Authors: R. S. Giraddi, C. M. Poleshi

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Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

Procedia PDF Downloads 388

Authors: Saiful Islam, Deuk Jong Bae

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The purpose of this study is to examine citizen satisfaction and competitiveness of a Public Private Partnership project. The study focuses on PPP in the transport sector and investigates the New Bundang Subway Line (NBL) in South Korea as the object of a case study. Most PPP studies are dominated by the study of public and private sector interests, which are classified in to three major areas comprising of policy, finance, and management. This study will explore the user perspective by assessing customer satisfaction upon NBL cost and service quality, also the competitiveness of NBL compared to other alternative transport modes which serve the Jeongja – Gangnam trip or vice versa. The regular Bundang Subway Line, New Bundang Subway Line, bus and private vehicle are selected as the alternative transport modes. The study analysed customer satisfaction of NBL and citizen’s preference of alternative transport modes based on a survey in Bundang district, South Korea. Respondents were residents and employees who live or work in Bundang city, and were divided into the following areas Pangyo, Jeongjae – Sunae, Migeun – Ori – Jukjeon, and Imae – Yatap – Songnam. The survey was conducted in January 2015 for two weeks, and 753 responses were gathered. By applying the Hedonic Utility approach, the factors which affect the frequency of using NBL were found to be overall customer satisfaction, convenience of access, and the socio economic demographic of the individual. In addition, by applying the Analytic Hierarchy Process (AHP) method, criteria factors influencing the decision to select alternative transport modes were identified. Those factors, along with the author judgement of alternative transport modes, and their associated criteria and sub-criteria produced a priority list of user preferences regarding their alternative transport mode options. The study found that overall the regular Bundang Subway Line (BL), which was built and operated under a conventional procurement method was selected as the most preferable transport mode due to its cost competitiveness. However, on the sub-criteria level analysis, the NBL has competitiveness on service quality, particularly on journey time. By conducting a sensitivity analysis, the NBL can become the first choice of transport by increasing the NBL’s degree of weight associated with cost by 0,05. This means the NBL would need to reduce either it’s fare cost or transfer fee, or combine those two cost components to reduce the total of the current cost by 25%. In addition, the competitiveness of NBL also could be obtained by increasing NBL convenience through escalating access convenience such as constructing an additional station or providing more access modes. Although these convenience improvements would require a few extra minutes of journey time, the user found this to be acceptable. The findings and policy suggestions can contribute to the next phase of NBL development, showing that consideration should be given to the citizen’s voice. The case study results also contribute to the literature of PPP projects specifically from a user side perspective.

Keywords: public private partnership, customer satisfaction, public transport, new Bundang subway line

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Authors: Mokhlisur Rahman

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The growing consensus among scientists and world leaders indicates that immediate action should be considered regarding the climate change phenomenon. However, climate change is no more a global issue but a personal one. Thus, individual participation is necessary to address such a significant issue. Studies show that individuals who perceive climate change as a personal issue are more likely to act toward it. This abstract presents augmented reality (A.R.) technology in the social media platform Facebook video advertising. The idea involves creating a video advertisement that enables users to interact with the video by navigating its features and experiencing the result uniquely and engagingly. This advertisement uses A.R. to bring changes, such as people making changes in real-life scenarios by simple clicks on the video and hearing an instant rewarding fact about their choices. The video shows three options: room, lawn, and driveway. Users select one option and engage in interaction based on while holding the camera in their personal spaces: Suppose users select the first option, room, and hold their camera toward spots such as by the windows, balcony, corners, and even walls. In that case, the A.R. offers users different plants appropriate for those unoccupied spaces in the room. Users can change the options of the plants and see which space at their house deserves a plant that makes it more natural. When a user adds a natural element to the video, the video content explains a piece of beneficiary information about how the user contributes to the world more to be livable and why it is necessary. With the help of A.R., if users select the second option, lawn, and hold their camera toward their lawn, the options are various small trees for their lawn to make it more environmentally friendly and decorative. The video plays a beneficiary explanation here too. Suppose users select the third option, driveway, and hold their camera toward their driveway. In that case, the A.R. video option offers unique recycle bin designs using A.I. measurement of spaces. The video plays audio information on anthropogenic contribution to greenhouse gas emission. IoT embeds tracking code in the video ad on Facebook, which stores the exact number of views in the cloud for data analysis. An online survey at the end collects short qualitative answers. This study helps understand the number of users involved and willing to change their behavior; It makes personalized advertising in social media. Considering the current state of climate change, the urgency for action is increasing. This ad increases the chance to make direct connections with individuals and gives a sense of personal responsibility for climate change to act

Keywords: motivations, climate, iot, personalized-advertising, action

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Authors: Mojtaba Eshraghi Arani

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The freight forwarders, who are known as the Architect of Transportation, play a vital role in the supply chain management. The package of various services which they provide has made the legal nature of freight forwarders very controversial, so that they might be qualified once as principal or carrier and, on other occasions, as agent of the shipper as the case may be. They could even be involved in the transportation process as the agent of shipping line, which makes the situation much more complicated. The courts in all countries have long had trouble in distinguishing the “forwarder as agent” from “forwarder as principal” (as it is outstanding in the prominent case of “Vastfame Camera Ltd v Birkart Globistics Ltd And Others” 2005, Hong Kong). It is not fully known that in the case of a claim against the forwarder, what particular parameter would be used by the judge among multiple, and sometimes contradictory, tests for determining the scope of the forwarder liability. In particular, every country has its own legal parameters for qualifying the freight forwarders that is completely different from others, as it is the case in France in comparison with Germany and England. The unpredictability of the courts’ decisions in this regard has provided the freight forwarders with the opportunity to impose any limitation or exception of liability while pretending to play the role of a principal, consequently making the cargo interests incur ever-increasing damage. The transportation industry needs to remove such uncertainty by unifying national laws governing freight forwarders liability. A long time ago, in 1967, The International Institute for Unification of Private Law (UNIDROIT) prepared a draft convention called “Draft Convention on Contract of Agency for Forwarding Agents Relating to International Carriage of Goods” (hereinafter called “UNIDROIT draft convention”). The UNIDROIT draft convention provided a clear and certain framework for the liability of freight forwarder in each capacity as agent or carrier, but it failed to transform to a convention, and eventually, it was consigned to oblivion. Today, after nearly 6 decades from that era, the necessity of such convention can be felt apparently. However, one might reason that the same grounds, in particular, the resistance by forwarders’ association, FIATA, exist yet, and thus it is not logical to revive a forgotten draft convention after such long period of time. It is argued in this article that the main reason for resisting the UNIDROIT draft convention in the past was pending efforts for developing the “1980 United Nation Convention on International Multimodal Transport of Goods”. However, the latter convention failed to become in force on due time in a way that there was no new accession since 1996, as a result of which the UNIDROIT draft convention must be revived strongly and immediately submitted to the relevant diplomatic conference. A qualitative method with the concept of interpretation of data collection has been used in this manuscript. The source of the data is the analysis of international conventions and cases.

Keywords: freight forwarder, revival, agent, principal, uidroit, draft convention

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Authors: T. J. O Ceallaigh

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Subject matter driven programs such as immersion programs are increasingly popular across the world. These programs have allowed for extensive experimentation in the realm of second language teaching and learning and have been at the centre of many research agendas since their inception. Even though immersion programs are successful, especially in terms of second language development, they remain complex to implement and not always as successful as what we would hope them to be. Among all the challenges these varied programs face, research indicates that the primary issue lies in the difficulty to create well-balanced programs where both content instruction and language/literacy instruction can be targeted simultaneously. Initial teacher education and professional development experiences are key drivers of successful language immersion education globally. They are critical to the supply of teachers with the mandatory linguistic and cultural competencies as well as associated pedagogical practices required to ensure learners’ success. However, there is a significant dearth of research on professional development experiences of immersion teachers. We lack an understanding of the nature of their expertise and their needs in terms of professional development as well as their perceptions of the primary challenges they face as they attempt to formulate a coherent pedagogy of integrated language and content instruction. Such an understanding is essential if their specific needs are to be addressed appropriately and thus improve the overall quality of immersion programs. This paper reports on immersion teacher perceptions of online professional development experiences that have a positive impact on their ability to facilitate language and content connections in instruction. Twenty Irish-medium immersion teachers engaged in the instructional integration of language and content in a systematic and developmental way during a year-long online professional development program. Data were collected from a variety of sources e.g., an extensive online questionnaire, individual interviews, reflections, assignments and focus groups. This study provides compelling evidence of the potential of online professional development experiences as a pedagogical framework for understanding the complex and interconnected knowledge demands that arise in content and language integration in immersion. Findings illustrate several points of access to classroom research and pedagogy and uncover core aspects of high impact online experiences. Teachers identified aspects such as experimentation and risk-taking, authenticity and relevance, collegiality and collaboration, motivation and challenge and teacher empowerment. The potential of the online experiences to foster teacher language awareness was also identified as a contributory factor to success. The paper will conclude with implications for designing meaningful and effective online CLIL professional development experiences.

Keywords: content and language integrated learning , immersion pedagogy, professional development, teacher language awareness

Procedia PDF Downloads 166

Authors: Kedar J. Mahadeshwar

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Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Ahlam Ali, Katrina Lappin, Jaine Blayney, Ken Mills

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Leukaemia is the most frequently (30%) occurring type of paediatric cancer. Of these, approximately 80% are acute lymphoblastic leukaemia (ALL) with acute myeloid leukaemia (AML) cases making up the remaining 20% alongside other leukaemias. Unfortunately, children with AML do not have promising prognosis with only 60% surviving 5 years or longer. It has been highlighted recently the need for age-specific therapies for AML patients, with paediatric AML cases having a different mutational landscape compared with AML diagnosed in adult patients. Drug Repurposing is a recognized strategy in drug discovery and development where an already approved drug is used for diseases other than originally indicated. We aim to identify novel combination therapies with the promise of providing alternative more effective and less toxic induction therapy options. Our in-silico analysis highlighted ‘cell death and survival’ as an aberrant, potentially targetable pathway in paediatric AML patients. On this basis, 83 apoptotic inducing compounds were screened. A preliminary single agent screen was also performed to eliminate potentially toxic chemicals, then drugs were constructed into a pooled library with 10 drugs per well over 160 wells, with 45 possible pairs and 120 triples in each well. Seven cell lines were used during this study to represent the clonality of AML in paediatric patients (Kasumi-1, CMK, CMS, MV11-14, PL21, THP1, MOLM-13). Cytotoxicity was assessed up to 72 hours using CellTox™ Green reagent. Fluorescence readings were normalized to a DMSO control. Z-Score was assigned to each well based on the mean and standard deviation of all the data. Combinations with a Z-Score <2 were eliminated and the remaining wells were taken forward for further analysis. A well was considered ‘successful’ if each drug individually demonstrated a Z-Score <2, while the combination exhibited a Z-Score >2. Each of the ten compounds in one well (155) had minimal or no effect as single agents on cell viability however, a combination of two or more of the compounds resulted in a substantial increase in cell death, therefore the ten compounds were de-convoluted to identify a possible synergistic pair/triple combinations. The screen identified two possible ‘novel’ drug pairing, with BCL2 inhibitor ABT-737, combined with either a CDK inhibitor Purvalanol A, or AKT/ PI3K inhibitor LY294002. (ABT-737- 100 nM+ Purvalanol A- 1 µM) (ABT-737- 100 nM+ LY294002- 2 µM). Three possible triple combinations were identified (LY2409881+Akti-1/2+Purvalanol A, SU9516+Akti-1/2+Purvalanol A, and ABT-737+LY2409881+Purvalanol A), which will be taken forward for examining their efficacy at varying concentrations and dosing schedules, across multiple paediatric AML cell lines for optimisation of maximum synergy. We believe that our combination screening approach has potential for future use with a larger cohort of drugs including FDA approved compounds and patient material.

Keywords: AML, drug repurposing, ABT-737, apoptosis

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Authors: Mustafa M. Donma, Orkide Donma

Abstract:

The number of indices developed for the evaluation of obesity both in adults and pediatric population is ever increasing. These indices are also used in cases with metabolic syndrome (MetS), mostly the ultimate form of morbid obesity. Aside from anthropometric measurements, formulas constituted using these parameters also find clinical use. These formulas can be listed as two groups; being weight-dependent and –independent. Some are extremely sophisticated equations and their clinical utility is questionable in routine clinical practice. The aim of this study is to compare presently available obesity indices and find the most practical one. Their associations with MetS components were also investigated to determine their capacities in differential diagnosis of morbid obesity with and without MetS. Children with normal body mass index (N-BMI) and morbid obesity were recruited for this study. Three groups were constituted. Age- and sex- dependent BMI percentiles for morbid obese (MO) children were above 99 according to World Health Organization tables. Of them, those with MetS findings were evaluated as MetS group. Children, whose values were between 85 and 15 were included in N-BMI group. The study protocol was approved by the Ethics Committee of the Institution. Parents filled out informed consent forms to participate in the study. Anthropometric measurements and blood pressure values were recorded. Body mass index, hip index (HI), conicity index (CI), triponderal mass index (TPMI), body adiposity index (BAI), body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), waist-to-hip ratio (WHR) and waist circumference+hip circumference/2 ((WC+HC)/2) were the formulas examined within the scope of this study. Routine biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein-cholesterol (HDL-C) were performed. Statistical package program SPSS was used for the evaluation of study data. p<0.05 was accepted as the statistical significance degree. Hip index did not differ among the groups. A statistically significant difference was noted between N-BMI and MetS groups in terms of ABSI. All the other indices were capable of making discrimination between N-BMI-MO, N-BMI- MetS and MO-MetS groups. No correlation was found between FBG and any obesity indices in any groups. The same was true for INS in N-BMI group. Insulin was correlated with BAI, TPMI, CI, BRI, AVI and (WC+HC)/2 in MO group without MetS findings. In MetS group, the only index, which was correlated with INS was (WC+HC)/2. These findings have pointed out that complicated formulas may not be required for the evaluation of the alterations among N-BMI and various obesity groups including MetS. The simple easily computable weight-independent index, (WC+HC)/2, was unique, because it was the only index, which exhibits a valuable association with INS in MetS group. It did not exhibit any correlation with other obesity indices showing associations with INS in MO group. It was concluded that (WC+HC)/2 was pretty valuable practicable index for the discrimination of MO children with and without MetS findings.

Keywords: children, insulin, metabolic syndrome, obesity indices

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Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

Abstract:

The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

Procedia PDF Downloads 67

Authors: Celine Davis

Abstract:

The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

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Authors: Maureen Kamau, Gulnaz Mohamoud, Adelaide Lusambili, Njeri Nyanja

Abstract:

Life expectancy has increased over the last century amongst older individuals, and in particular, those 60 years and over. The World Health Organization estimates that the world's population of persons over 60 years will rise to 22 per cent by the year 2050. Ageing is associated with increasing disability, multiple chronic conditions, and an increase in the use of health services. These multiple chronic conditions are managed with polypharmacy. Polypharmacy has numerous adverse effects including non-adherence, poor compliance to the various medications, reduced appetite, and risk of fall. Studies on polypharmacy and ageing are few and poorly understood especially in low and middle - income countries. The aim of this study was to explore the knowledge, attitudes and beliefs of older people towards polypharmacy. A qualitative study of 15 patients aged 60 years and above, taking more than five medications per day were conducted at the Aga Khan University using Semi-structured in-depth interviews. Three interviews were pilot interviews, and data analysis was performed on 12 interviews. Data were analyzed using NVIVO 12 software. A thematic qualitative analysis was carried out guided by Braun and Clarke (2006) framework. Themes identified; - knowledge of their co-morbidities and of the medication that older persons take, sources of information about medicines, and storage of the medication, experiences and attitudes of older patients towards polypharmacy both positive and negative, older peoples beliefs and their coping mechanisms with polypharmacy. The study participants had good knowledge on their multiple co-morbidities, and on the medication they took. The patients had positive attitudes towards medication as it enhanced their health and well-being, and enabled them to perform their activities of daily living. There was a strong belief among older patients that the medications were necessary for their health. All these factors enhanced compliance to the multiple medication. However, some older patients had negative attitudes due to the pill burden, side effects of the medication, and stigma associated with being ill. Cost of healthcare was a concern, with most of the patients interviewed relying on insurance to cover the cost of their medication. Older patients had accepted that the medication they were prescribed were necessary for their health, as it enabled them to complete their activities of daily living. Some concerns about the side effects of the medication arose, and brought about the need for patient education that would ensure that the patients are aware of the medications they take, and potential side effects. The effect that the COVID 19 pandemic had in the healthcare of the older patients was evident by the number of the older patients avoided coming to the hospital during the period of the pandemic. The relationship with the primary care physician and the older patients is an important one, especially in LMICs such as Kenya, as many of the older patients trusted the doctors wholeheartedly to make the best decision about their health and about their medication. Prescription review is important to avoid the use of potentially inappropriate medication.

Keywords: polypharmacy, older patients, multiple chronic conditions, Kenya, Africa, qualitative study, indepth interviews, primary care

Procedia PDF Downloads 82