Search results for: Heisenberg uncertainty principle

Authors: Hung-Chun Lin, Tzu-Yuan Chao

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As the population aging has become an inevitable trend globally, issues of improving the well-being of elderly people in urban areas have been a challenging task for urban planners. Recent studies of ageing trend have also expended to explore the relationship between the built environment and mental condition of elderly people. These studies have proved that even though the built environment may not necessarily play the decisive role in affecting mental health, it can have positive impacts on individual mental health by promoting social linkages and social networks among older adults. There has been a great amount of relevant research examined the impact of the built environment attributes on depression in the elderly; however, most were conducted in the Western countries. Little attention has been paid in Asian cities with contrarily high density and mix-use urban contexts such as Taiwan regarding how the built environment attributes related to depression in elderly people. Hence, more empirical cross-principle studies are needed to explore the possible impacts of Asia urban characteristics on older residents’ mental condition. This paper intends to focus on Tainan city, the fourth biggest metropolis in Taiwan. We first analyze with data from National Health Insurance Research Database to pinpoint the empirical study area where residing most elderly patients, aged over 65, with depressive disorders. Secondly, we explore the relationship between specific attributes of the built environment collected from previous studies and elderly individuals who suffer from depression, under different socio-cultural and networking circumstances. To achieve the results, the research methods adopted in this study include questionnaire and database analysis, and the results will be proceeded by correlation analysis. In addition, through literature review, by generalizing the built environment factors that have been used in Western research to evaluate the relationship between built environment and older individuals with depressive disorders, a set of local evaluative indicators of the built environment for future studies will be proposed as well. In order to move closer to develop age-friendly cities and improve the well-being for the elderly in Taiwan, the findings of this paper can provide empirical results to grab planners’ attention for how built environment makes the elderly feel and to reconsider the relationship between them. Furthermore, with an interdisciplinary topic, the research results are expected to make suggestions for amending the procedures of drawing up an urban plan or a city plan from a different point of view.

Keywords: built environment, depression, elderly, Tainan

Procedia PDF Downloads 100

Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Rebecca Zahra, Joseph G. Vella, Ernest Cachia

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The notion of cloud computing is rapidly gaining ground in the IT industry and is appealing mostly due to making computing more adaptable and expedient whilst diminishing the total cost of ownership. This paper focuses on the software as a service (SaaS) architecture of cloud computing which is used for the outsourcing of databases with their associated business processes. One approach for offering SaaS is basing the system’s architecture on multi-tenancy. Multi-tenancy allows multiple tenants (users) to make use of the same single application instance. Their requests and configurations might then differ according to specific requirements met through tenant customisation through the software. Despite the known advantages, companies still feel uneasy to opt for the multi-tenancy with data security being a principle concern. The fact that multiple tenants, possibly competitors, would have their data located on the same server process and share the same database tables heighten the fear of unauthorised access. Security is a vital aspect which needs to be considered by application developers, database administrators, data owners and end users. This is further complicated in cloud-based multi-tenant system where boundaries must be established between tenants and additional access control models must be in place to prevent unauthorised cross-tenant access to data. Moreover, when altering the database state, the transactions need to strictly adhere to the tenant’s known business processes. This paper focuses on the fact that security in cloud databases should not be considered as an isolated issue. Rather it should be included in the initial phases of the database design and monitored continuously throughout the whole development process. This paper aims to identify a number of the most common security risks and threats specifically in the area of multi-tenant cloud systems. Issues and bottlenecks relating to security risks in cloud databases are surveyed. Some techniques which might be utilised to overcome them are then listed and evaluated. After a description and evaluation of the main security threats, this paper produces a list of software requirements to ensure that proper security policies are implemented by a software development team when designing and implementing a multi-tenant based SaaS. This would then assist the cloud service providers to define, implement, and manage security policies as per tenant customisation requirements whilst assuring security for the customers’ data.

Keywords: cloud computing, data management, multi-tenancy, requirements, security

Procedia PDF Downloads 131

Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. This paper will try to introduce another way of calculating reliability by using R statistical software. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The R programming environment is a widely used open source system for statistical analysis and statistical programming. It includes thousands of functions for the implementation of both standard and new statistical methods. R does not limit user only to operation related only to these functions. This program has many benefits over other similar programs: it is free and, as an open source, constantly updated; it has built-in help system; the R language is easy to extend with user-written functions. The significance of the work is calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. Seventy generators were studied. For each one, the number of hours of running time from its first being put into service until fan failure or until the end of the study (whichever came first) was recorded. Dataset consists of two variables: hours and status. Hours show the time of each fan working and status shows the event: 1- failed, 0- censored data. Censored data represent cases when we cannot track the specific case, so it could fail or success. Gaining the result by using R was easy and quick. The program will take into consideration censored data and include this into the results. This is not so easy in hand calculation. For the purpose of the paper results from R program have been compared to hand calculations in two different cases: censored data taken as a failure and censored data taken as a success. In all three cases, results are significantly different. If user decides to use the R for further calculations, it will give more precise results with work on censored data than the hand calculation.

Keywords: censored data, R statistical software, reliability analysis, time to failure

Procedia PDF Downloads 379

Authors: Cath Grimley, Debra Bick, Sarah Hillman, Louise Clarke, Helen Atherton, Jo Parsons

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The problem: Women in the UK are offered influenza (flu), pertussis (whooping cough) and COVID-19 vaccinations during their pregnancy but uptake of all three vaccines is below the desired rate. These vaccines are offered during pregnancy as pregnant women are at an increased risk of hospitalisation, morbidity, and mortality from these illnesses. Exposure to these diseases during pregnancy can also have a negative impact on the unborn baby with an increased risk of serious complications both while in utero and following birth. The research aims to explore perceptions about the vaccinations offered in pregnancy both from the perspectives of pregnant women and midwives. To determine factors that influence pregnant women’s decisions about whether or not to accept the vaccines following the Covid-19 pandemic and to explore midwives’ experiences of recommending and delivering vaccines. The approach: This research follows a qualitative design involving semi-structured interviews with pregnant women and midwives in the UK. Interviews with midwives explored vaccination discussions they routinely have with pregnant women and identified some of the barriers to vaccination that pregnant women discuss with them. Interviews with pregnant women explored their views since the COVID-19 pandemic about vaccinations offered during pregnancy, and whether the pandemic has influenced perceptions of vulnerability to illness in pregnant women. Midwives were recruited via participating hospitals and midwife specific social media groups. Pregnant women were recruited via participating hospitals and community groups. All interviews were conducted remotely (using telephone or Microsoft Teams) and analysed using thematic analysis. Findings: 43 pregnant women and 16 midwives were recruited and interviewed. The findings presented here will focus on data from midwives. Topics identified included three key themes for midwives. These were 1) Delivery of vaccinations which includes the convenience of offering vaccinations while attending standard antenatal appointments and practical barriers faced in delivering these vaccinations at hospital. 2) Messages and guidance included the importance of up-to-date informational needs for midwives to deliver vaccines and that uncertainty and conflicting messages about the COVID-19 vaccine during pregnancy were a barrier to delivery. 3) Recommendations to have vaccines look at all aspects of recommendations such as how recommendations are communicated, the contents of the recommendation, the importance of the vaccine and the impact of those recommendations on whether women accept the vaccine. Implications: Findings highlight the importance for midwives to receive clear and consistent information so they can feel confident in relaying this information while recommending and delivering vaccines to pregnant women. Emphasising why vaccines are important when recommending vaccinations to pregnant women in addition to standard information on the availability and timing will add to the strength and impact of that recommendation in helping women to make informed decisions about accepting vaccines. The findings of this study will inform the development of an intervention to increase vaccination uptake amongst pregnant women.

Keywords: vaccination, pregnancy, qualitative, interviews, Covid-19, midwives

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Authors: J. Hakula

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Discussion on euthanasia is a continuous process. Euthanasia is defined as 'deliberately ending a patient's life by administering life-ending drugs at the patient's explicit request'. With few exceptions, worldwide in most countries human societies have not been able to agree on some fundamental issues concerning ultimate decisions of life and death. Outranking methods in voting oriented social choice theory and multicriteria decision-making (MCDM) can be applied to issues in medical ethics. There is a wide range of voting methods, and using different methods the same group of voters can end up with different outcomes. In the MCDM context, decision alternatives can be substituted for candidates, and criteria for voters. The view chosen here is that of a single decision-maker. Initially, three alternatives and three criteria are chosen. Pairwise and basic positional voting rules - plurality, anti-plurality and the Borda count - are applied. In the MCDM solution, criteria are put weights by giving them the more 'votes'; the more important the decision-maker ranks them. A hypothetical example on evaluating properties of euthanasia consists of three alternatives A, B, and C, which are ranked according to three criteria - the patient’s willingness to cooperate, general action orientation (active/passive), and cost-effectiveness - the criteria having weights 7, 5, and 4, respectively. Using the plurality rule and the weights given to criteria, A is the best alternative, B and C thereafter. In pairwise comparisons, both B and C defeat A with weight scores 7 to 9. On the other hand, B is defeated by C with weights 11 to 5. Thus, C (i.e. the so-called Condorcet winner) defeats both A and B. The best alternative using the plurality principle is not necessarily the best in the pairwise sense, the conflict remaining unsolved with or without additional weights. Positional rules are sensitive to variations in alternative sets. In the example above, the plurality rule gives the rank ABC. If we leave out C, the plurality ranking between A and B results in BA. Withdrawing B or A the ranking is CA and CB, respectively. In pairwise comparisons an analogous problem emerges when the number of criteria is varied. Cyclic preferences may lead to a total tie, and no (rational) choice between the alternatives can be made. In conclusion, the choice of the best commitment to re-evaluate euthanasia, with criteria left unchanged, depends entirely on the evaluation method used. The right strategies matter, too. Future studies might concern the problem of an abstention - a situation where voters do not vote - and still their best candidate may win. Or vice versa, actively giving the ballot to their first rank choice might lead to a total loss. In MCDM terms, a decision might occur where some central criteria are not actively involved in the best choice made.

Keywords: medical ethics, euthanasia, voting methods, multicriteria decision-making

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Authors: Sushmita Roy Chowdhury, Steve Holding, Sujoy Khan

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The immunogenic responses of the lung towards the fungus Aspergillus fumigatus may range from invasive aspergillosis in the immunocompromised, fungal ball or infection within a cavity in the lung in those with structural lung lesions, or allergic bronchopulmonary aspergillosis (ABPA). Patients with asthma or cystic fibrosis are particularly predisposed to ABPA. There are consensus guidelines that have established criteria for diagnosis of ABPA, but uncertainty remains on the serologic cut-off values that would increase the diagnostic specificity of ABPA. We retrospectively analyzed 80 patients with severe asthma and evidence of peripheral blood eosinophilia ( > 500) over the last 3 years who underwent all serologic tests to exclude ABPA. Total IgE, specific IgE and specific IgG levels against Aspergillus fumigatus were measured using ImmunoCAP Phadia-100 (Thermo Fisher Scientific, Sweden). The Modified ISHAM working group 2013 criteria (obligate criteria: asthma or cystic fibrosis, total IgE > 1000 IU/ml or > 417 kU/L and positive specific IgE Aspergillus fumigatus or skin test positivity; with ≥ 2 of peripheral eosinophilia, positive specific IgG Aspergillus fumigatus and consistent radiographic opacities) was used in the clinical workup for the final diagnosis of ABPA. Patients were divided into 3 groups - definite, possible, and no evidence of ABPA. Specific IgG Aspergillus fumigatus levels were not used to assign the patients into any of the groups. Of 80 patients (males 48, females 32; mean age 53.9 years ± SD 15.8) selected for the analysis, there were 30 patients who had positive specific IgE against Aspergillus fumigatus (37.5%). 13 patients fulfilled the Modified ISHAM working group 2013 criteria of ABPA (‘definite’), while 15 patients were ‘possible’ ABPA and 52 did not fulfill the criteria (not ABPA). As IgE levels were not normally distributed, median levels were used in the analysis. Median total IgE levels of patients with definite and possible ABPA were 2144 kU/L and 2597 kU/L respectively (non-significant), while median specific IgE Aspergillus fumigatus at 4.35 kUA/L and 1.47 kUA/L respectively were significantly different (comparison of standard deviations F-statistic 3.2267, significance level p=0.040). Mean levels of IgG anti-Aspergillus fumigatus in the three groups (definite, possible and no evidence of ABPA) were compared using ANOVA (Statgraphics Centurion Professional XV, Statpoint Inc). Mean levels of IgG anti-Aspergillus fumigatus (Gm3) in definite ABPA was 125.17 mgA/L ( ± SD 54.84, with 95%CI 92.03-158.32), while mean Gm3 levels in possible and no ABPA were 18.61 mgA/L and 30.05 mgA/L respectively. ANOVA showed a significant difference between the definite group and the other groups (p < 0.001). This was confirmed using multiple range tests (Fisher's least significant difference procedure). There was no significant difference between the possible ABPA and not ABPA groups (p > 0.05). The study showed that a sizeable proportion of patients with asthma are sensitized to Aspergillus fumigatus in this part of India. A higher cut-off value of Gm3 ≥ 80 mgA/L provides a higher serologic specificity towards definite ABPA. Long-term studies would provide us more information if those patients with 'possible' APBA and positive Gm3 later develop clear ABPA, and are different from the Gm3 negative group in this respect. Serologic testing with clear defined cut-offs are a valuable adjunct in the diagnosis of ABPA.

Keywords: allergic bronchopulmonary aspergillosis, Aspergillus fumigatus, asthma, IgE level

Procedia PDF Downloads 180

Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Pirta Palola, Richard Bailey, Lisa Wedding

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Societies and economies worldwide fundamentally depend on natural capital. Alarmingly, natural capital assets are quickly depreciating, posing an existential challenge for humanity. The development of robust natural capital accounting systems is essential for transitioning towards sustainable economic systems and ensuring sound management of capital assets. However, the accurate, equitable and comprehensive estimation of natural capital asset stocks and their accounting values still faces multiple challenges. In particular, the representation of socio-cultural values held by groups or communities has arguably been limited, as to date, the valuation of natural capital assets has primarily been based on monetary valuation methods and assumptions of individual rationality. People relate to and value the natural environment in multiple ways, and no single valuation method can provide a sufficiently comprehensive image of the range of values associated with the environment. Indeed, calls have been made to improve the representation of multiple types of value (instrumental, intrinsic, and relational) and diverse ontological and epistemological perspectives in environmental valuation. This study addresses this need by establishing a novel valuation framework, Environmental Value Functions (EVF), that allows for the integration of multiple types of value in natural capital accounting systems. The EVF framework is based on the estimation and application of value functions, each of which describes the relationship between the value and quantity (or quality) of an ecosystem component of interest. In this framework, values are estimated in terms of change relative to the current level instead of calculating absolute values. Furthermore, EVF was developed to also support non-marginalist conceptualizations of value: it is likely that some environmental values cannot be conceptualized in terms of marginal changes. For example, ecological resilience value may, in some cases, be best understood as a binary: it either exists (1) or is lost (0). In such cases, a logistic value function may be used as the discriminator. Uncertainty in the value function parameterization can be considered through, for example, Monte Carlo sampling analysis. The use of EVF is illustrated with two conceptual examples. For the first time, EVF offers a clear framework and concrete methodology for the representation of multiple types of value in natural capital accounting systems, simultaneously enabling 1) the complementary use and integration of multiple valuation methods (monetary and non-monetary); 2) the synthesis of information from diverse knowledge systems; 3) the recognition of value incommensurability; 4) marginalist and non-marginalist value analysis. Furthermore, with this advancement, the coupling of EVF and ecosystem modeling can offer novel insights to the study of spatial-temporal dynamics in natural capital asset values. For example, value time series can be produced, allowing for the prediction and analysis of volatility, long-term trends, and temporal trade-offs. This approach can provide essential information to help guide the transition to a sustainable economy.

Keywords: economics of biodiversity, environmental valuation, natural capital, value function

Procedia PDF Downloads 162

Authors: Grace C. Kuroki, Yixin Hu, Bailey Surtees, Rebecca Krimins, Nicholas J. Durr, Dara L. Kraitchman

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The purpose of this study was to perform a Phase I veterinary clinical trial with a low-cost, carbon-dioxide-based, passive thaw cryoablation device as proof-of-principle for application in pets and translation to third-world treatment of breast cancer. This study was approved by the institutional animal care and use committee. Client-owned dogs with subcutaneous masses, primarily lipomas or mammary cancers, were recruited for the study. Inclusion was based on clinical history, lesion location, preanesthetic blood work, and fine needle aspirate or biopsy confirmation of mass. Informed consent was obtained from the owners for dogs that met inclusion criteria. Ultrasound assessment of mass extent was performed immediately prior to mass cryoablation. Dogs were placed under general anesthesia and sterilely prepared. A stab incision was created to insert a custom 4.19 OD x 55.9 mm length cryoablation probe (Kubanda Cryotherapy) into the mass. Originally designed for treating breast cancer in low resource settings, this device has demonstrated potential in effectively necrosing subcutaneous masses. A dose escalation study of increasing freeze-thaw cycles (5/4/5, 7/5/7, and 10/7/10 min) was performed to assess the size of the iceball/necrotic extent of cryoablation. Each dog was allowed to recover for ~1-2 weeks before surgical removal of the mass. A single mass was treated in seven dogs (2 mammary masses, a sarcoma, 4 lipomas, and 1 adnexal mass) with most masses exceeding 2 cm in any dimension. Mass involution was most evident in the malignant mammary and adnexal mass. Lipomas showed minimal shrinkage prior to surgical removal, but an area of necrosis was evident along the cryoablation probe path. Gross assessment indicated a clear margin of cryoablation along the cryoprobe independent of tumor type. Detailed histopathology is pending, but complete involution of large lipomas appeared to be unlikely with a 10/7/10 protocol. The low-cost, carbon dioxide-based cryotherapy device permits a minimally invasive technique that may be useful for veterinary applications but is also informative of the unlikely resolution of benign adipose breast masses that may be encountered in third world countries.

Keywords: cryoablation, cryotherapy, interventional oncology, veterinary technology

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Authors: Tal Braverman Uriel, Tal Litvak Hirsch

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Background and Objectives: Little or only partial emphasis has been placed on exploring the complexity of consensual non-monogamous relationships. The term "polyamory" refers to consensual non-monogamy, and it is defined as having emotional and/or sexual relations simultaneously with two or more people, the consent and knowledge of all the partners concerned. Managing multiple romantic relationships with different people evokes more emotions, leads to more emotional conflicts arising from different interests, and demands practical strategies. An individual's transition from a monogamous lifestyle to a consensual non-monogamous lifestyle yields new challenges, accompanied by stress, uncertainty, and question marks, as do other life-changing events, such as divorce or transition to parenthood. The study examines both the process of transition and adaptation to a consensually non-monogamous relationship, as well as the coping mechanism involved in the daily conduct of this lifestyle. The research focuses on understanding the consequences, challenges, and coping methods from a personal, marital, and familial point of view and focuses on 40 middle-aged individuals (20 men and 20 women ages 40-60). The research sheds light on a way of life that has not been previously studied in Israel and is still considered unacceptable. Theories of crisis (e.g., as Folkman and Lazarus) were applied, and as a result, a deeper understanding of the subject was reached, all while focusing on multiple aspects of dealing with stress. The basic research question examines the consequences of entering a polyamorous life from a personal point of view as an individual, partner, and parent and the ways of coping with these consequences. Method: The research is conducted with a narrative qualitative approach in the interpretive paradigm, including semi-structured in-depth interviews. The method of analysis is thematic. Results: The findings indicate that in most cases, an individual's motivation to open the relationship is mainly a longing for better sexuality and for an added layer of excitement to their lives. Most of the interviewees were assisted by their spouses in the process, as well as by social networks and podcasts on the subject. Some of them therapeutic professionals from the field are helpful. It also clearly emerged that among those who experienced acute emotional crises with the primary partner or painful separations from secondary partners, all believed polyamory to be the adequate way of life for them. Finally, a key resource for managing tension and stress is the ability to share and communicate with the primary partner. Conclusions: The study points to the challenges and benefits of a non-monogamous lifestyle as well as the use of coping mechanisms and resources that are consistent with the existing theory and research in the field in the context of life changes. The study indicates the need to expand the research canvas in the future in the context of parenting and the consequences for children.

Keywords: a-monogamy, consent, family, stress, tension

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: Marta Ribo, Ian D. Goodwin, Thomas Mortlock, Phil O’Brien

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Coastal behavior is best investigated using a sediment budget approach, based on the identification of sediment sources and sinks. Grain size distribution over the New South Wales (NSW) continental shelf has been widely characterized since the 1970’s. Coarser sediment has generally accumulated on the outer shelf, and/or nearshore zones, with the latter related to the presence of nearshore reef and bedrocks. The central part of the NSW shelf is characterized by the presence of fine sediments distributed parallel to the coastline. This study presents new grain size distribution maps along the NSW continental shelf, built using all available NSW and Commonwealth Government holdings. All available seabed bathymetric data form prior projects, single and multibeam sonar, and aerial LiDAR surveys were integrated into a single bathymetric surface for the NSW continental shelf. Grain size information was extracted from the sediment sample data collected in more than 30 studies. The information extracted from the sediment collections varied between reports. Thus, given the inconsistency of the grain size data, a common grain size classification was her defined using the phi scale. The new sediment distribution maps produced, together with new detailed seabed bathymetric data enabled us to revise the delineation of sediment compartments to more accurately reflect the true nature of sediment movement on the inner shelf and nearshore. Accordingly, nine primary mega coastal compartments were delineated along the NSW coast and shelf. The sediment compartments are bounded by prominent nearshore headlands and reefs, and major river and estuarine inlets that act as sediment sources and/or sinks. The new sediment grain size distribution was used as an input in the morphological modelling to quantify the sediment transport patterns (and indicative rates of transport), used to investigate sand supply rates and processes from the lower shoreface to the NSW coast. The rate of sand supply to the NSW coast from deep water is a major uncertainty in projecting future coastal response to sea-level rise. Offshore transport of sand is generally expected as beaches respond to rising sea levels but an onshore supply from the lower shoreface has the potential to offset some of the impacts of sea-level rise, such as coastline recession. Sediment exchange between the lower shoreface and sub-aerial beach has been modelled across the south, central, mid-north and far-north coast of NSW. Our model approach is that high-energy storm events are the primary agents of sand transport in deep water, while non-storm conditions are responsible for re-distributing sand within the beach and surf zone.

Keywords: New South Wales coast, off-shore transport, sand supply, sediment distribution maps

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Authors: Rene Hellmuth

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The requirements for the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Restrictions regarding new areas, shorter life cycles of product and production technology as well as a VUCA (volatility, uncertainty, complexity and ambiguity) world cause more frequently occurring rebuilding measures within a factory. Restructuring of factories is the most common planning case today. Restructuring is more common than new construction, revitalization and dismantling of factories. The increasing importance of restructuring processes shows that the ability to change was and is a promising concept for the reaction of companies to permanently changing conditions. The factory building is the basis for most changes within a factory. If an adaptation of a construction project (factory) is necessary, the inventory documents must be checked and often time-consuming planning of the adaptation must take place to define the relevant components to be adapted, in order to be able to finally evaluate them. The different requirements of the planning participants from the disciplines of factory planning (production planner, logistics planner, automation planner) and industrial construction planning (architect, civil engineer) come together during reconstruction and must be structured. This raises the research question: Which requirements do the disciplines involved in the reconstruction planning place on a digital factory model? A subordinate research question is: How can model-based decision support be provided for a more efficient design of the conversion within a factory? Because of the high adaptation rate of factories and its building described above, a methodology for rescheduling factories based on the requirements engineering method from software development is conceived and designed for practical application in factory restructuring projects. The explorative research procedure according to Kubicek is applied. Explorative research is suitable if the practical usability of the research results has priority. Furthermore, it will be shown how to best use a digital factory model in practice. The focus will be on mobile applications to meet the needs of factory planners on site. An augmented reality (AR) application will be designed and created to provide decision support for planning variants. The aim is to contribute to a shortening of the planning process and model-based decision support for more efficient change management. This requires the application of a methodology that reduces the deficits of the existing approaches. The time and cost expenditure are represented in the AR tablet solution based on a building information model (BIM). Overall, the requirements of those involved in the planning process for a digital factory model in the case of restructuring within a factory are thus first determined in a structured manner. The results are then applied and transferred to a construction site solution based on augmented reality.

Keywords: augmented reality, digital factory model, factory planning, restructuring

Procedia PDF Downloads 104

Authors: Muhammad Bilal, Amelia Jane Llyod, Habsah Mohamad, Jia Hui Wong, Abdul Aziz Mohamed Yusoff, Jafri Malin Abdullah, Jingli Zhang

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Epilepsy is one of the major brain afflictions occurs with uncontrolled excitation of cortex; disturbed 50 million of world’s population. About 25 percent of patients subjected to adverse effects from antiepileptic drugs (AEDs) such as depression, nausea, tremors, gastrointestinal symptoms, osteoporosis, dizziness, weight change, drowsiness, fatigue are commonly observed indications; therefore, new drugs are required to cure epilepsy. GABA is principle inhibitory neurotransmitter, control excitation of the brain. Mutation or dysfunction of GABA receptor is one of the primary causes of epilepsy, which is confirmed from many acquired models of epilepsy like traumatic brain injury, kindling, and status epilepticus models of epilepsy. GABA receptor has 3 distinct types such as GABA (A), GABA (B), GABA(C).GABA (A) receptor has 20 different subunits, α1β2γ2 subunits composition of GABA (A) receptor is the most used combination of subunits for screening of compounds against epilepsy. We expressed α1β2γ2s subunits of GABA (A) Receptor in Xenopus leavis oocytes and examined the enhancement potential of 4-Hydroxybenzoic acid compound on GABA (A) receptor via two-electrode voltage clamp current recording technique. Bamboo shoots are the young, tender offspring of bamboo, which are usually harvested after a cultivating period of 2 weeks. Proteins, acids, fat, starch, carbohydrate, fatty acid, vitamin, dietary fiber, and minerals are the major constituent found systematically in bamboo shoots. These shoots reported to have anticancer, antiviral, antibacterial activity, also possess antioxidant properties due to the presence of phenolic compounds. Student t-test analysis suggested that 4- hydroxybenzoic acid positively allosteric GABA (A) receptor, increased normalized current amplitude to 1.0304±0.0464(p value 0.032) compared with vehicle. 4-Hydrobenzoic acid, a compound from Dendrocalamus Asper bamboo shoot gives new insights for future studies on bamboo shoots with motivation for extraction of more compounds to investigate their effects on human and rodents against epilepsy, insomnia, and anxiety.

Keywords: α1β2γ2S, antiepileptic, bamboo shoots, epilepsy GABA (A) receptor, two-microelectrode voltage clamp, xenopus laevis oocytes

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Authors: Lorenza Sganzetta, Nunzia Borrelli

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The research intends to reflect on the current mapping of the Food Strategies, on the reasons why in the planning objectives panorama, such sustainability priorities are located in those geographic areas and on the evolutions of these priorities of the Mediterranean planning dispositions. The whirling population growth that is affecting global cities is causing an enormous challenge to conventional resource-intensive food production and supply and the urgent need to face food safety, food security and sustainability concerns. Urban or Territorial Food Strategies can provide an interesting path for the development of this new agenda within the imperative principle of sustainability. In the specific, it is relevant to explore what ‘sustainability’ means within these policies. Most of these plans include actions related to four main components and interpretations of sustainability that are food security and safety, food equity, environmental sustainability itself and cultural identity and, at the designing phase, they differ slightly from each other according to the degree of approximation to one of these dimensions. Moving from these assumptions, the article would analyze some practices and policies representatives of different Food Strategies of the world and focus on the Mediterranean ones, on the problems and negative externalities from which they start, on the first interventions that are implementing and on their main objectives. We will mainly use qualitative data from primary and secondary collections. So far, an essential observation could have been made about the relationship between these sustainability dimensions and geography. In statistical terms, the US and Canadian policies tended to devote a large research space to health issues and access to food; those northern European showed a special attention to the environmental issues and the shortening of the chain; and finally the policies that, even in limited numbers, were being developed in the Mediterranean basin, were characterized by a strong territorial and cultural imprint and their major aim was to preserve local production and the contact between the productive land and the end consumer. Recently, though, Mediterranean food planning strategies are focusing more on health related and food accessibility issues and analyzing our diets not just as a matter of culture and territorial branding but as tools for reducing public health costs and accessibility to fresh food for everyone. The article would reflect then on how Food Safety, Food Security and Health are entering the new agenda of the Mediterranean Food Strategies. The research hypothesis suggests that the economic crisis that in the last years invested both producers and consumers had a significant impact on the nutrition habits and on the redefinition of food poverty, even in the fatherland of the healthy Mediterranean diet. This trend and other variables influenced the orientation and the objectives of the food strategies.

Keywords: food security, food strategy, health, sustainability

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

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Authors: Maria Debora Braga, Luigi Riso, Maria Grazia Zoia

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Risk-based approaches to asset allocation are portfolio construction methods that do not rely on the input of expected returns for the asset classes in the investment universe and only use risk information. They include the Minimum Variance Strategy (MV strategy), the traditional (volatility-based) Risk Parity Strategy (SRP strategy), the Most Diversified Portfolio Strategy (MDP strategy) and, for many, the Equally Weighted Strategy (EW strategy). All the mentioned approaches were based on portfolio volatility as a reference risk measure but in 2023, the Kurtosis-based Risk Parity strategy (KRP strategy) and the Minimum Kurtosis strategy (MK strategy) were introduced. Understandably, they used the fourth root of the portfolio-fourth moment as a proxy for portfolio kurtosis to work with a homogeneous function of degree one. This paper contributes mainly theoretically and methodologically to the framework of risk-based asset allocation approaches with two steps forward. First, a new and more flexible objective function considering a linear combination (with positive coefficients that sum to one) of portfolio volatility and portfolio kurtosis is used to alternatively serve a risk minimization goal or a homogeneous risk distribution goal. Hence, the new basic idea consists in extending the achievement of typical risk-based approaches’ goals to a combined risk measure. To give the rationale behind operating with such a risk measure, it is worth remembering that volatility and kurtosis are expressions of uncertainty, to be read as dispersion of returns around the mean and that both preserve adherence to a symmetric framework and consideration for the entire returns distribution as well, but also that they differ from each other in that the former captures the “normal” / “ordinary” dispersion of returns, while the latter is able to catch the huge dispersion. Therefore, the combined risk metric that uses two individual metrics focused on the same phenomena but differently sensitive to its intensity allows the asset manager to express, in the context of an objective function by varying the “relevance coefficient” associated with the individual metrics, alternatively, a wide set of plausible investment goals for the portfolio construction process while serving investors differently concerned with tail risk and traditional risk. Since this is the first study that also implements risk-based approaches using a combined risk measure, it becomes of fundamental importance to investigate the portfolio effects triggered by this innovation. The paper also offers a second contribution. Until the recent advent of the MK strategy and the KRP strategy, efforts to highlight interesting properties of risk-based approaches were inevitably directed towards the traditional MV strategy and SRP strategy. Previous literature established an increasing order in terms of portfolio volatility, starting from the MV strategy, through the SRP strategy, arriving at the EQ strategy and provided the mathematical proof for the “equalization effect” concerning marginal risks when the MV strategy is considered, and concerning risk contributions when the SRP strategy is considered. Regarding the validity of similar conclusions when referring to the MK strategy and KRP strategy, the development of a theoretical demonstration is still pending. This paper fills this gap.

Keywords: risk parity, portfolio kurtosis, risk diversification, asset allocation

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Authors: Francesca Nardi, Kashish Aneja, Katherine Ginsbach

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The COVID-19 pandemic has demonstrated both a need for evidence-based and rights-based public health policy and how challenging it can be to make effective decisions with limited information, evidence, and data. The O’Neill Institute, in conjunction with several partners, has been working since the beginning of the pandemic to collect, analyze, and distribute critical data on public health policies enacted in response to COVID-19 around the world in the COVID-19 Law Lab. Well-designed laws and policies can help build strong health systems, implement necessary measures to combat viral transmission, enforce actions that promote public health and safety for everyone, and on the individual level have a direct impact on health outcomes. Poorly designed laws and policies, on the other hand, can fail to achieve the intended results and/or obstruct the realization of fundamental human rights, further disease spread, or cause unintended collateral harms. When done properly, laws can provide the foundation that brings clarity to complexity, embrace nuance, and identifies gaps of uncertainty. However, laws can also shape the societal factors that make disease possible. Law is inseparable from the rest of society, and COVID-19 has exposed just how much laws and policies intersects all facets of society. In the COVID-19 context, evidence-based and well-informed law and policy decisions—made at the right time and in the right place—can and have meant the difference between life or death for many. Having a solid evidentiary base of legal information can promote the understanding of what works well and where, and it can drive resources and action to where they are needed most. We know that legal mechanisms can enable nations to reduce inequities and prepare for emerging threats, like novel pathogens that result in deadly disease outbreaks or antibiotic resistance. The collection and analysis of data on these legal mechanisms is a critical step towards ensuring that legal interventions and legal landscapes are effectively incorporated into more traditional kinds of health science data analyses. The COVID-19 Law Labs see a unique opportunity to collect and analyze this kind of non-traditional data to inform policy using laws and policies from across the globe and across diseases. This global view is critical to assessing the efficacy of policies in a wide range of cultural, economic, and demographic circumstances. The COVID-19 Law Lab is not just a collection of legal texts relating to COVID-19; it is a dataset of concise and actionable legal information that can be used by health researchers, social scientists, academics, human rights advocates, law and policymakers, government decision-makers, and others for cross-disciplinary quantitative and qualitative analysis to identify best practices from this outbreak, and previous ones, to be better prepared for potential future public health events.

Keywords: public health law, surveillance, policy, legal, data

Procedia PDF Downloads 123

Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

Procedia PDF Downloads 196

Authors: Fabrizio Ascione, Martina Borrelli, Rosa Francesca De Masi, Silvia Ruggiero, Giuseppe Peter Vanoli

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The refurbishment of public buildings is one of the key factors of energy efficiency policy of European States. Educational buildings account for the largest share of the oldest edifice with interesting potentialities for demonstrating best practice with regards to high performance and low and zero-carbon design and for becoming exemplar cases within the community. In this context, this paper discusses the critical issue of dealing the energy refurbishment of a university building in heating dominated climate of South Italy. More in detail, the importance of using validated models will be examined exhaustively by proposing an analysis on uncertainties due to modelling assumptions mainly referring to the adoption of stochastic schedules for occupant behavior and equipment or lighting usage. Indeed, today, the great part of commercial tools provides to designers a library of possible schedules with which thermal zones can be described. Very often, the users do not pay close attention to diversify thermal zones and to modify or to adapt predefined profiles, and results of designing are affected positively or negatively without any alarm about it. Data such as occupancy schedules, internal loads and the interaction between people and windows or plant systems, represent some of the largest variables during the energy modelling and to understand calibration results. This is mainly due to the adoption of discrete standardized and conventional schedules with important consequences on the prevision of the energy consumptions. The problem is surely difficult to examine and to solve. In this paper, a sensitivity analysis is presented, to understand what is the order of magnitude of error that is committed by varying the deterministic schedules used for occupation, internal load, and lighting system. This could be a typical uncertainty for a case study as the presented one where there is not a regulation system for the HVAC system thus the occupant cannot interact with it. More in detail, starting from adopted schedules, created according to questioner’ s responses and that has allowed a good calibration of energy simulation model, several different scenarios are tested. Two type of analysis are presented: the reference building is compared with these scenarios in term of percentage difference on the projected total electric energy need and natural gas request. Then the different entries of consumption are analyzed and for more interesting cases also the comparison between calibration indexes. Moreover, for the optimal refurbishment solution, the same simulations are done. The variation on the provision of energy saving and global cost reduction is evidenced. This parametric study wants to underline the effect on performance indexes evaluation of the modelling assumptions during the description of thermal zones.

Keywords: energy simulation, modelling calibration, occupant behavior, university building

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Authors: Ameni Mejri, Moufida Hajjaj, Salem Hasnaoui, Ridha Bouallegue

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The technology advances have most lately made the millimeter wave (mmWave) communication possible. Due to the huge amount of spectrum that is available in MmWave frequency bands, this promising candidate is considered as a key technology for the deployment of 5G cellular networks. In order to enhance system capacity and achieve spectral efficiency, very large antenna arrays are employed at mmWave systems by exploiting array gain. However, it has been shown that conventional beamforming strategies are not suitable for mmWave hardware implementation. Therefore, new features are required for mmWave cellular applications. Unlike traditional multiple-input-multiple-output (MIMO) systems for which only digital precoders are essential to accomplish precoding, MIMO technology seems to be different at mmWave because of digital precoding limitations. Moreover, precoding implements a greater number of radio frequency (RF) chains supporting more signal mixers and analog-to-digital converters. As RF chain cost and power consumption is increasing, we need to resort to another alternative. Although the hybrid precoding architecture has been regarded as the best solution based on a combination between a baseband precoder and an RF precoder, we still do not get the optimal design of hybrid precoders. According to the mapping strategies from RF chains to the different antenna elements, there are two main categories of hybrid precoding architecture. Given as a hybrid precoding sub-array architecture, the partially-connected structure reduces hardware complexity by using a less number of phase shifters, whereas it sacrifices some beamforming gain. In this paper, we treat the hybrid precoder design in mmWave MIMO systems as a problem of matrix factorization. Thus, we adopt the alternating minimization principle in order to solve the design problem. Further, we present our proposed algorithm for the partially-connected structure, which is based on the iterative hard thresholding method. Through simulation results, we show that our hybrid precoding algorithm provides significant performance gains over existing algorithms. We also show that the proposed approach reduces significantly the computational complexity. Furthermore, valuable design insights are provided when we use the proposed algorithm to make simulation comparisons between the hybrid precoding partially-connected structure and the fully-connected structure.

Keywords: alternating minimization, hybrid precoding, iterative hard thresholding, low-complexity, millimeter wave communication, partially-connected structure

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Authors: Heather Warfield, Brad Genereux

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Military personnel encounter a number of challenges when separating from military service to include career uncertainty, relational/family dynamics, trauma as a result of military experiences, reconceptualization of identity, and existential issues related to purpose, meaning making and framing of the military experience(s). Embedded within military culture are well-defined rites of passage and a significant sense of belonging. Consequently, transition out of the military can result in the loss of such rites of passage and belongingness. However, a pilgrimage journey can provide the time and space to engage in a new rite of passage, to construct a new pilgrim identity, and a to develop deep social relationships that lead to a sense of belongingness to a particular pilgrim community as well as to the global community of pilgrims across numerous types of pilgrimage journeys. The aims of the current paper are to demonstrate the rationale for why pilgrimage journeys are particularly significant for military veterans, provide an overview of an innovative program that facilitates the Camino de Santiago pilgrimage for military veterans, and discusses the lessons learned from the initial pilot project of a recently established program. Veterans on the Camino (VOC) is an emerging nongovernmental organization in the USA. Founded by a military veteran, after leaving his military career, the primary objective of the organization is to facilitate healing for veterans via the Camino de Santiago pilgrimage journey. As part of the program, participants complete a semi-structured interview at three time points – pre, during, and post journey. The interview items are based on ongoing research by the principal investigator and address such constructs as meaning-making, wellbeing, therapeutic benefits and transformation. In addition, program participants complete The Sources of Meaning and Meaning in Life Questionnaire (SoMe). The pilot program occurred in the spring of 2017. Five participants were selected after an extensive application process and review by a three-person selection board. The selection criteria included demonstrated compatibility with the program objectives (i.e., prior military experience, availability for a 40 day journey, and awareness of the need for a transformational intervention). The participants were connected as a group through a private Facebook site and interacted with one another for several months prior to the pilgrimage. Additionally, the participants were interviewed prior to beginning the pilgrimage, at one point during the pilgrimage and immediately following the conclusion of the pilgrimage journey. The interviews yielded themes related to loss, meaning construction, renewed hope in humanity, and a commitment to future goals. The lessons learned from this pilot project included a confirmation of the need for such a program, a need for greater focus on logistical details, and the recognition that the pilgrimage experience needs to continue in some manner once the veterans return home.

Keywords: pilgrimage, healing, military veterans, Camino de Santiago

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Authors: Muhammad Nouman, Salim Gul, Karim Ullah

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Partnership has been understood as the essence of Islamic banking. However, in practice, the non-partnership paradigm dominates the operations of Islamic banks. Islamic banks adopt partnership contracts for the scheme of deposits, especially for term deposit accounts. However, they do not adopt partnership contracts (i.e., Musharakah and Mudarabah) as the main financing scheme. In practice, non-partnership contracts including Murabahah and Ijara are widely used for financing. Many authors have provided different explanations for the less utilization of the partnership contracts as a scheme of financing. However, the typology of constraints remains missing. The extant literature remains scattered, with diverse studies focused on different dimensions of the issue. Therefore, there is no unified understanding of the constraints in the application of the partnership contracts. This paper aims to highlight the major factors hindering the application of partnership contracts, and produce a coherent view by synthesizing different explanations provided in several studies conducted around the globe. The present study employs insights form the extant literature using a systematic review and provides academia, practitioners, and policy makers with a holistic framework to name and make sense of what is making partnership contracts a less attractive option for Islamic banks. A total of 84 relevant publications including 11 books, 14 chapters of edited books, 48 journal articles, 8 conference papers and 3 IMF working papers were selected using a systematic procedure. Analysis of these selected publications followed three steps: i) In the first step of analysis the constraints explicitly appearing in the literature set of 84 articles were extracted, ii) In the second step 27 factors hindering the application of partnership contracts were identified from the constraints extracted in the first step with the overlapping items either eliminated or combined, iii) In the last step the factors identified in the second step were classified into three distinct categories. Our intention was to develop the typology of constraints by connecting the rather abstract concepts into the broader sets of constraints for better conceptualization and policy implications. Our framework highlights that there are mainly three facets of lower preference for partnership contracts of financing. First, there are several factors in the contemporary business settings, prevailing social setting, and the bank’s internal environment that underpin uncertainty in the success of partnership contracts of financing. Second, partnership contracts have lower demand i.e., entrepreneurs prefer to use non-partnership contracts for financing their ventures due to the inherent restraining characteristics of the partnership contracts. Finally, there are certain factors in the regulatory framework that restraint the extensive utilization of partnership contracts of financing by Islamic banks. The present study contributes to the Islamic banking literature in many ways. It provides clarification to the heavily criticized operations of Islamic banks, integrates the scattered literature, and provides a holistic framework for better conceptualization of the key constraints in the application of the partnership contracts and policy implications. Moreover, it demonstrates an application of systematic review in Islamic banking research.

Keywords: Islamic banking, Islamic finance, Mudarabah, Musharakah, partnership, systematic review

Procedia PDF Downloads 244

Authors: Dalal Albudaiwi, Mike Allen, Talal Alhaji, Shahnaz Khadimehzadah

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As a pandemic, COVID-19 has impacted the whole world since November 2019. In other words, every organization, industry, and institution has been negatively affected by the Coronavirus. The uncertainty of how long the pandemic will last caused chaos at all levels. As with any other institution, public libraries were affected and transmitted into online services and resources. As internationally, have been witnessed that some public libraries were well-prepared for such disasters as the pandemic, and therefore, collections, users, services, technologies, staff, and budgets were all influenced. Public libraries’ policies did not mention any plan regarding such a pandemic. Instead, there are several rules in the guidelines about disasters in general, such as natural disasters. In this pandemic situation, libraries have been involved in different uneasy circumstances. However, it has always been apparent to public libraries the role they play in serving their communities in excellent and critical times. It dwells into the traditional role public libraries play in providing information services and sources to satisfy their information-based community needs. Remarkably increasing people’s awareness of the importance of informational enrichment and enhancing society’s skills in dealing with information and information sources. Under critical circumstances, libraries play a different role. It goes beyond the traditional part of information providers to the untraditional role of being a social institution that serves the community with whatever capabilities they have. This study takes two significant directions. The first focuses on investigating how libraries have responded to COVID-19 and how they manage disasters within their organization. The second direction focuses on how libraries help their communities to act during disasters and how to recover from the consequences. The current study examines how libraries prepare for disasters and the role of public libraries during disasters. We will also propose “measures” to be a model that libraries can use to evaluate the effectiveness of their response to disasters. We intend to focus on how libraries responded to this new disaster. Therefore, this study aims to develop a comprehensive policy that includes responding to a crisis such as Covid-19. An analytical lens inside the libraries as an organization and outside the organization walls will be documented based on analyzing disaster-related literature published in the LIS publication. The study employs content analysis (CA) methodology. CA is widely used in the library and information science. The critical contribution of this work is to propose solutions it provides to libraries and planers to prepare crisis management plans/ policies, specifically to face a new global disaster such as the COVID-19 pandemic. Moreover, the study will help library directors to evaluate their strategies and to improve them properly. The significance of this study lies in guiding libraries’ directors to enhance the goals of the libraries to guarantee crucial issues such as: saving time, avoiding loss, saving budget, acting quickly during a crisis, maintaining libraries’ role during pandemics, finding out the best response to disasters, and creating plan/policy as a sample for all libraries.

Keywords: Covid-19, policy, preparedness, public libraries

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Authors: Alba Barbara-i-Molinero, Rosalia Cascon-Pereira, Ana Beatriz Hernandez

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Students’ transitions from high school to the university have been challenged by the lack of continuity between both contexts. This mismatch directly affects students by generating feelings of anxiety and uncertainty, which increases the dropout rates and reduces students’ academic success. This discontinuity emanates because ‘transitions concern a restructuring of what the person does and who the person perceives him or herself to be’. Hence, identity becomes essential in these transitions. Generally, identity is the answer to questions such as who am I? or who are we? This is integrated by personal identity, and as many social identities as groups, the individual feels he/she is a part. A case in point to construct a social identity is the identification with a profession. For this reason, a way to lighten the generated tension during transitions is applying strategies orientated to enhance students’ professional identity in their point of entry to the higher education institution. That would create a sense of continuity between high school and higher education contexts, increasing their Professional Identity Strength. To develop the strategies oriented to enhance students Professional Identity, it is important to analyze what influences it. There exist several influencing factors that influence Professional Identity (e.g., professional status, the recommendation of family and peers, the academic environment, or the chosen bachelor degree). There is a gap in the literature analyzing the impact of these factors on more than one bachelor degree. In this regards, our study takes an additional step with the aim of evaluating the influence of several factors on Professional Identity using a cohort of university students from multiple degrees between the ages of 17-19 years. To do so, we used hierarchical regression analyses to assess the impact of the following factors: External Motivation Conditionals (EMC), Educational Experience Conditionals (EEC) and Personal Motivational Conditional (PMP). After conducting the analyses, we found that the assessed factors influenced students’ professional identity differently according to their bachelor degree and discipline. For example, PMC and EMC positively affected science students, while architecture, law and economics and engineering students were just influenced by PMC. Basing on that influences, we proposed three different strategies aimed to enhance students’ professional identity, in the short and long term. These strategies are: to enhance students’ professional identity before the incorporation to university through campuses and icebreaker activities; to apply recruitment strategies aimed to provide realistic information of the bachelor degree; and to incorporate different activities, such as in-vitro, in situ and self-directed activities aimed to enhance longitudinally students’ professional identity from the university. From these results, theoretical contributions and practical implications arise. First, we contribute to the literature by identifying which factors influence students from different bachelor degrees since there is still no evidence. And, second, using as a benchmark the obtained results, we contribute from a practical perspective, by proposing several alternative strategies to increase students’ professional identity strength aiming to lighten their transition from high school to higher education.

Keywords: professional identity, higher education, educational strategies , students

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Authors: Sumeyra Yakar

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The idea of this research had its genesis from the writer's interest in Shi'i school and religio-political atmosphere in contemporary Iran. The research aims to identify how the past dynamics between political and legal figures and their relationship between each other affect contemporary relationship between political and religious authorities at the local and global level. It attempts to explore religio-politic Shi'i figures and their relationship with the official jurisprudence from the 15th century to the contemporary period. The mutual interaction between the opinion and acts of political figures and jurisprudential institutions enlightens the role of religious values to control the mass population. After the collapse of the Safawīd Dynasty, Shi'i believers lost their political guardian and legal independence, and the situation gave them the inspiration to create unique ideologies or political approaches to solve the governance crisis. The analysis of authoritative political figures and their scholastic contributions elucidate the connection between political powers and religious doctrines under the protection of sectarian oriented theocratic governments. Additionally, understanding the incremental influence of political (historical) Shi'i figures into religious doctrines shed lights on the chronological development of peculiar government style and authoritative hierarchy in contemporary Shi’i communities. The research as being interdisciplinary one offers to create an academic awareness between legal and political factors in Shi’i school of thought and encompasses political, religious, social, financial and cultural atmospheres of the countries in which the political figures lived. The Iranian regime enshrines the principle of vilāyāt-i faqīh (guardianship of the jurist) which enables jurists to solve the conflict between law as an ideal system, in theory, and law in practice. The paper aims to show how the religious, educational system works in harmony with the governmental authorities with the concept of vilāyāt-i faqīh in Iran and contributes to the creation of religious custom in the society. Contemporary relationship between the political figures and religious authorities in Iran will be explained by religio-legal dimensions. The methodology that will be applied by the study has been chosen in order to acquire information and deduce conclusions from the opinions of the scholars. Thus, the research method is mainly descriptive and qualitative. Three lines of description are pursued throughout the study; the explanation of political ideas belonging to the religio-political figures theoretically depending on written texts; the description of approaches adopted by contemporary Iranian and Saudi scholars relating to the legal systems (theoretically); and the explanation of the responses of governmental authorities.

Keywords: clergy (‘ulamā), guardianship of the jurist (vilāyāt-i faqīh), Iran, Shi’i figures

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Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy

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The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.

Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems

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Authors: Adewale O. Adegbenjo, Elsie Nsiah-Baafi, Mxolisi B. Shongwe, Mercy Ramakokovhu, Peter A. Olubambi

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The sintering step in powder metallurgy (P/M) processes is very sensitive as it determines to a large extent the properties of the final component produced. Spark plasma sintering over the past decade has been extensively used in consolidating a wide range of materials including metallic alloy powders. This novel, non-conventional sintering method has proven to be advantageous offering full densification of materials, high heating rates, low sintering temperatures, and short sintering cycles over conventional sintering methods. Ti6Al4V has been adjudged the most widely used α+β alloy due to its impressive mechanical performance in service environments, especially in the aerospace and automobile industries being a light metal alloy with the capacity for fuel efficiency needed in these industries. The P/M route has been a promising method for the fabrication of parts made from Ti6Al4V alloy due to its cost and material loss reductions and the ability to produce near net and intricate shapes. However, the use of this alloy has been largely limited owing to its relatively poor hardness and wear properties. The effect of sintering temperature on the densification, hardness, and wear behaviors of spark plasma sintered Ti6Al4V powders was investigated in this present study. Sintering of the alloy powders was performed in the 650–850°C temperature range at a constant heating rate, applied pressure and holding time of 100°C/min, 50 MPa and 5 min, respectively. Density measurements were carried out according to Archimedes’ principle and microhardness tests were performed on sectioned as-polished surfaces at a load of 100gf and dwell time of 15 s. Dry sliding wear tests were performed at varied sliding loads of 5, 15, 25 and 35 N using the ball-on-disc tribometer configuration with WC as the counterface material. Microstructural characterization of the sintered samples and wear tracks were carried out using SEM and EDX techniques. The density and hardness characteristics of sintered samples increased with increasing sintering temperature. Near full densification (99.6% of the theoretical density) and Vickers’ micro-indentation hardness of 360 HV were attained at 850°C. The coefficient of friction (COF) and wear depth improved significantly with increased sintering temperature under all the loading conditions examined, except at 25 N indicating better mechanical properties at high sintering temperatures. Worn surface analyses showed the wear mechanism was a synergy of adhesive and abrasive wears, although the former was prevalent.

Keywords: hardness, powder metallurgy, spark plasma sintering, wear

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