Search results for: sampling algorithms

Authors: Paloma Mendes Saldanha

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Access to information is a prerequisite for democracy while also guiding the material construction of fundamental rights. The exercise of citizenship requires knowing, understanding, questioning, advocating for, and securing rights and responsibilities. In other words, it goes beyond mere active electoral participation and materializes through awareness and the struggle for rights and responsibilities in the various spaces occupied by the population in their daily lives. In times of hyper-cultural connectivity, active citizenship is shaped through ethical trust processes, most often established between humans and algorithms. Automated decisions, so prevalent in various everyday situations, such as purchase preference predictions, virtual voice assistants, reduction of accidents in autonomous vehicles, content removal, resume selection, etc., have already found their place as a normalized discourse that sometimes does not reveal or make clear what violations of fundamental rights may occur when algorithmic explainability is lacking. In other words, technological and market development promotes a normalization for the use of automated decisions while silencing possible restrictions and/or breaches of rights through a culturally modeled, unethical, and unexplained trust process, which hinders the possibility of the right to a healthy, transparent, and complete exercise of citizenship. In this context, the article aims to identify the violations caused by the absence of algorithmic explainability in the exercise of citizenship through the construction of an unethical and silent trust process between humans and algorithms in automated decisions. As a result, it is expected to find violations of constitutionally protected rights such as privacy, data protection, and transparency, as well as the stipulation of algorithmic explainability as a fundamental right in the exercise of Brazilian citizenship in the era of virtualization, facing a threefold foundation called trust: culture, rules, and systems. To do so, the author will use a bibliographic review in the legal and information technology fields, as well as the analysis of legal and official documents, including national documents such as the Brazilian Federal Constitution, as well as international guidelines and resolutions that address the topic in a specific and necessary manner for appropriate regulation based on a sustainable trust process for a hyperconnected world.

Keywords: artificial intelligence, ethics, citizenship, trust

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Authors: Mohab Magdy Mostafa Mohamed

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The objective of this paper is to introduce a vertical handover (VHO) algorithm between wireless LANs (WLANs) and LTE mobile networks. The proposed algorithm is based on the fuzzy control theory and takes into consideration power level, subscriber velocity, and target cell load instead of only power level in traditional algorithms. Simulation results show that network performance in terms of number of handovers and handover occurrence distance is improved.

Keywords: vertical handover, fuzzy control theory, power level, speed, target cell load

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Authors: Vesta Kohlmeier, George C. Dragan, Juergen Orasche, Juergen Schnelle-Kreis, Dietmar Breuer, Ralf Zimmermann

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Aerosols from hazardous semi-volatile organic compounds (SVOC) may occur in workplace air and can simultaneously be found as particle and gas phase. For health risk assessment, it is necessary to collect particles and gases separately. This can be achieved by using a denuder for the gas phase collection, combined with a filter and an adsorber for particle collection. The study focused on the suitability of carbonaceous monolithic multi-channel denuders, so-called Novacarb™-Denuders (MastCarbon International Ltd., Guilford, UK), to achieve gas-particle separation. Particle transmission efficiency experiments were performed with polystyrene latex (PSL) particles (size range 0.51-3 µm), while the time dependent gas phase collection efficiency was analysed for polar and nonpolar SVOC (mass concentrations 7-10 mg/m3) over 2 h at 5 or 10 l/min. The experimental gas phase collection efficiency was also compared with theoretical predictions. For n-hexadecane (C16), the gas phase collection efficiency was max. 91 % for one denuder and max. 98 % for two denuders, while for diethylene glycol (DEG), a maximal gas phase collection efficiency of 93 % for one denuder and 97 % for two denuders was observed. At 5 l/min higher gas phase collection efficiencies were achieved than at 10 l/min. The deviations between the theoretical and experimental gas phase collection efficiencies were up to 5 % for C16 and 23 % for DEG. Since the theoretical efficiency depends on the geometric shape and length of the denuder, flow rate and diffusion coefficients of the tested substances, the obtained values define an upper limit which could be reached. Regarding the particle transmission through the denuders, the use of one denuder showed transmission efficiencies around 98 % for 1-3 µm particle diameters. The use of three denuders resulted in transmission efficiencies from 93-97 % for the same particle sizes. In summary, NovaCarb™-Denuders are well applicable for sampling aerosols of polar/nonpolar substances with particle diameters ≤3 µm and flow rates of 5 l/min or lower. These properties and their compact size make them suitable for use in personal aerosol samplers. This work is supported by the German Social Accident Insurance (DGUV), research contract FP371.

Keywords: gas phase collection efficiency, particle transmission, personal aerosol sampler, SVOC

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Authors: Ahmed Machmoum, Malika El Kyal

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We consider iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays tobe substantial and unpredictable. Note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: computer, multi-splitting methods, asynchronous mode, differential algebraic systems

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Authors: Lucas L. L. Fortes, Sandro T. M. Gonçalves

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In this work, it is analyzed the wideband performance with the mesh discretization impoverishment of the Conformal Finite Difference Time-Domain (C-FDTD) approaches developed by Raj Mittra, Supriyo Dey and Wenhua Yu for the Finite Difference Time-Domain (FDTD) method. These approaches are a simple and efficient way to optimize the scattering simulation of curved surfaces for Dielectric and Perfect Electric Conducting (PEC) structures in the FDTD method, since curved surfaces require dense meshes to reduce the error introduced due to the surface staircasing. Defined, on this work, as D-FDTD-Diel and D-FDTD-PEC, these approaches are well-known in the literature, but the improvement upon their application is not quantified broadly regarding wide frequency bands and poorly discretized meshes. Both approaches bring improvement of the accuracy of the simulation without requiring dense meshes, also making it possible to explore poorly discretized meshes which bring a reduction in simulation time and the computational expense while retaining a desired accuracy. However, their applications present limitations regarding the mesh impoverishment and the frequency range desired. Therefore, the goal of this work is to explore the approaches regarding both the wideband and mesh impoverishment performance to bring a wider insight over these aspects in FDTD applications. The D-FDTD-Diel approach consists in modifying the electric field update in the cells intersected by the dielectric surface, taking into account the amount of dielectric material within the mesh cells edges. By taking into account the intersections, the D-FDTD-Diel provides accuracy improvement at the cost of computational preprocessing, which is a fair trade-off, since the update modification is quite simple. Likewise, the D-FDTD-PEC approach consists in modifying the magnetic field update, taking into account the PEC curved surface intersections within the mesh cells and, considering a PEC structure in vacuum, the air portion that fills the intersected cells when updating the magnetic fields values. Also likewise to D-FDTD-Diel, the D-FDTD-PEC provides a better accuracy at the cost of computational preprocessing, although with a drawback of having to meet stability criterion requirements. The algorithms are formulated and applied to a PEC and a dielectric spherical scattering surface with meshes presenting different levels of discretization, with Polytetrafluoroethylene (PTFE) as the dielectric, being a very common material in coaxial cables and connectors for radiofrequency (RF) and wideband application. The accuracy of the algorithms is quantified, showing the approaches wideband performance drop along with the mesh impoverishment. The benefits in computational efficiency, simulation time and accuracy are also shown and discussed, according to the frequency range desired, showing that poorly discretized mesh FDTD simulations can be exploited more efficiently, retaining the desired accuracy. The results obtained provided a broader insight over the limitations in the application of the C-FDTD approaches in poorly discretized and wide frequency band simulations for Dielectric and PEC curved surfaces, which are not clearly defined or detailed in the literature and are, therefore, a novelty. These approaches are also expected to be applied in the modeling of curved RF components for wideband and high-speed communication devices in future works.

Keywords: accuracy, computational efficiency, finite difference time-domain, mesh impoverishment

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: N. Taghinejad, F. Dortaj, N. Khodabandeh

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This research aimed at comparing resilience among male and female children with and without parental supervision in Bandar Abbas. The sample consists of 200 subjects selected through cluster sampling. The research method was comparative causal and Conner and Davidson’s questionnaire form resilience was used for data collection. Results indicated that there is no difference between children with and without parental supervision regarding their resilience capacity. These findings may be challenging and useful for psychologists, officials of children’s affairs and legislators.

Keywords: resilience, children , children with parental supervision, children without parental supervision

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Authors: Xue Li, Hui Xu

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Mild cognitive impairment (MCI) is a clinical stage that occurs between normal aging and dementia. Although MCI increases the risk of developing dementia, individuals with MCI may maintain stable cognitive function and even recover to a typical cognitive state. An intervention to prevent or delay the progression to dementia in individuals with MCI may involve promoting social engagement. Social participation is the engagement in socially relevant social exchanges and meaningful activities. Older adults with MCI may encounter restricted cognitive abilities, mood changes, and behavioral difficulties during social participation, influencing their willingness to engage. Therefore, this study aims to employ qualitative research methods to gain an in-depth comprehension of the authentic social participation experiences of older adults with mild cognitive impairment, which will establish a foundation for designing appropriate intervention programs. A phenomenological research was conducted. The study participants were selected using the purposive sampling method in combination with the maximum differentiation sampling strategy. Face-to-face semistructured interviews were conducted among 12 elderly individuals suffering from mild cognitive impairment in a community in Zhengzhou City from May to July 2023. Colaizzi 7-step method was used to analyze the data and extract the theme. The real experience of social participation in older adults with mild cognitive impairment can be summarized into 3 themes: (1) a single social relationship but a strong desire to participate, (2) a dual experience of social participation with both positive and negative aspects, (3) multiple barriers to social participation, including impaired memory capacity, heavy family responsibilities and lack of infrastructure. The study found that elderly individuals with mild cognitive impairment and one social interaction display an increased desire to engage in society. To improve social participation levels and reduce cognitive function decline, healthcare providers should work with relevant government agencies and the community to create a comprehensive social participation system. It is important for healthcare providers to note the social participation status of the elderly with mild cognitive impairment.

Keywords: mild cognitive impairment, the elderly, social participation, qualitative research

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Authors: Mengistu Tulu Balcha, Endale Gadisa Motuma

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The purpose of this study was to assess the effect of leadership styles on employees’ organizational commitments in Ambo Woreda public organizations. The study was guided by a Descriptive survey and correlation research design of the quantitative method. By using simple random sampling techniques, 80 participants of employees and by purposive sampling technique, 32 leaders were involved in research from five purposely selected Woreda public organizations without a non-response rate. Two separate instruments adopted from previous studies, namely the multifactor leadership questionnaire (MLQ), which has 36 items and the Organizational Commitment Questionnaire (OCQ), which has 12 items, were used as a data instrument tool. These items were rated by using a five-point Likert-scale. The survey data was processed by using an SPSS (version 27). Descriptive statistics to calculate mean and standard deviations of leaders’ and employees’ responses to leadership styles dominantly practiced in order to determine their perceptions, MLQ of leaders’ and employees’ responses (independent sample), and multiple linear regressions were used to calculate the effect of leadership styles on organizational commitment. The findings of the study show that the leadership style dominantly practiced in Ambo Woreda public organizations was more transactional than transformational and followed by laissez-faire. The level of EOC was ranked as continuance commitment and had the highest mean score, followed by normative commitment and then affective commitment. There is a strong, positive and significant relationship between leadership style dimensions and employees’ organizational commitment. Leadership styles were found statistically significant to predict employee commitment and there was a significant linear relationship between independent variables and dependent variables. Out of the three leadership variables, the transactional leadership style has the highest contribution, followed by the transformational leadership style, whereas the laissez-faire leadership style has the least contribution in predicting employees’ organizational commitment. Finally, the researcher forwarded possible recommendations for Ambo Woreda public organizational leaders and employees to work on improving leadership styles and employees’ commitment collaboratively.

Keywords: organizations, employee, relations, commitments, style

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Authors: Nan Hu, Chao Wang, Xi Li, Xuehai Zhou

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The field-programmable gate array (FPGA) has been widely adopted in the high-performance computing domain. In recent years, the embedded system-on-a-chip (SoC) contains coarse granularity multi-core CPU (central processing unit) and mobile GPU (graphics processing unit) that can be used as general-purpose accelerators. The motivation is that algorithms of various parallel characteristics can be efficiently mapped to the heterogeneous architecture coupled with these three processors. The CPU and GPU offload partial computationally intensive tasks from the FPGA to reduce the resource consumption and lower the overall cost of the system. However, in present common scenarios, the applications always utilize only one type of accelerator because the development approach supporting the collaboration of the heterogeneous processors faces challenges. Therefore, a systematic approach takes advantage of write-once-run-anywhere portability, high execution performance of the modules mapped to various architectures and facilitates the exploration of design space. In this paper, A servant-execution-flow model is proposed for the abstraction of the cooperation of the heterogeneous processors, which supports task partition, communication and synchronization. At its first run, the intermediate language represented by the data flow diagram can generate the executable code of the target processor or can be converted into high-level programming languages. The instantiation parameters efficiently control the relationship between the modules and computational units, including two hierarchical processing units mapping and adjustment of data-level parallelism. An embedded system of a three-dimensional waveform oscilloscope is selected as a case study. The performance of algorithms such as contrast stretching, etc., are analyzed with implementations on various combinations of these processors. The experimental results show that the heterogeneous computing system with less than 35% resources achieves similar performance to the pure FPGA and approximate energy efficiency.

Keywords: FPGA-CPU-GPU collaboration, design space exploration, heterogeneous computing, intermediate language, parameterized instantiation

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Usman Bawa

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Macro-invertebrates have been used to monitor organic pollution in rivers and streams. Several biotic indices based on macro-invertebrates have been developed over the years including the Biological Monitoring Working Party (BMWP). A new biotic index, the Gammarus:Asellus ratio has been recently proposed as an index of organic pollution. This study tested the validity of the Gammarus:Asellus ratio as an index of organic pollution, by examining the relationship between the Gammarus:Asellus ratio and physical-chemical parameters, and other biotic indices such as BMWP and, Average Score Per Taxon (ASPT) from lakes and streams at Markeaton Park, Allestree Park, and Kedleston Hall, Derbyshire. Macro invertebrates were sampled using the standard five-minute kick sampling techniques physical and chemical environmental variables were obtained based on standard sampling techniques. Eighteen sites were sampled, six sites from Markeaton Park (three sites across the stream and three sites across the lake). Six sites each were also sampled from Allestree Park and Kedleston Hall lakes. The Gammarus:Asellus ratio showed an opposite significant positive correlations with parameters indicative of organic pollution such as the level of nitrates, phosphates, and calcium and also revealed a negatively significant correlations with other biotic indices (BMWP/ASPT). The BMWP score correlated positively significantly with some water quality parameters such as dissolved oxygen and flow rate, but revealed no correlations with other chemical environmental variables. The BMWP score was significantly higher in the stream than the lake in Markeaton Park, also The ASPT scores appear to be significantly higher in the upper Lakes than the middle and lower lakes. This study has further strengthened the use of BMWP/ASPT score as an index of organic pollution. But, additional application is required to validate the use of Gammarus:Asellus as a rapid bio monitoring tool.

Keywords: Asellus, biotic index, Gammarus, macro invertebrates, organic pollution

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Authors: Mavis Ofosuah Asante, Abena Abokoma Asemanyi, Belinda Osei-mensah, Stephen Osei Akyiaw

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The study examined mobile money service fraud experiences and perspectives on control practices at University of Education, Winneba. The objectives of the study included to examine the forms of MoMo fraud strategies experienced by customers of MoMo on UEW Campus, to examine and classify the main perpetrators of the MoMo fraud among UEW students as well as the framework for fraud detection put together by the Telco’s and consumers on UEW Campus. The study adopted the case study research design. The purposive sampling technique was used to select the UEW Campus. Using the convenience sampling technique, five respondents were sampled for the study. The outcome of the in-depth interviews conducted revealed Mobile money fraud was committed in various forms, such as anonymous calls and text messages from scammers, fraudsters calling to deceive subscribers that they are to deliver goods from abroad or from a close relative under false pretexts. Finally, fraudsters sending false cash-out messages to merchants for authorization of which the physical cash is issued by the merchant to the fraudster without the equivalent e-cash. Mobile money fraud has been perpetuated in diverse forms such as mobile money network systems fraud, false promotion fraud, and reversal of erroneous transactions, fortuitous scams, and mobile money agents' fraud. Finally, the frameworks that have been used to detect mobile money fraud include the display of national identifies cards for the transaction, digital identification systems, the use of firewall to protect mobile money accounts, effective information technology architecture for mobile money services, reporting of mobile money fraud to telecoms and the sanctioning of mobile money fraudsters. The study suggested there should be public education and awareness creation on the activities of mobile money fraudsters in Ghana by telecommunication companies in conjunction with the National Communications Authority and the Bank of Ghana. The study, therefore, concluded that the menace of mobile money fraud threatens the integrity of the mobile money financial services.

Keywords: mobile money, fraud, telecommunication, merchant

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Authors: Sudaporn Arundee

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The purposes of this research were to study in three areas: (1) to study political understanding and participating of the constitutional monarchy, (2) to study the level of participation. This paper drew upon data collected from 395 Dusit residents by using questionnaire. In addition, a simple random sampling was utilized to collect data. The findings revealed that 94 percent of respondents had a very good understanding of constitution monarchy with a mean of 4.8. However, the respondents overall had a very low level of participation with the mean score of 1.69 and standard deviation of .719.

Keywords: political participation, constitutional monarchy, management and social sciences

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Authors: Ni'mal Baroya, Andrei Ramani, Irma Prasetyowati

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The access to reproduction health services, including with safe and effective contraception were human rights regardless of social stratum and residence. In addition to individual factors, family and contextual factors were also believed to be the cause in the use of contraceptive methods. This study aimed to assess the determinants of long-term contraceptive methods (LTCM) by considering all the factors at either the individual level or contextual level. Thereby, this study could provide basic information for program development of prevalence enhancement of MKJP in East Java. The research, which used cross-sectional design, utilized Riskesdas 2013 data, particularly in East Java Province for further analysis about multilevel modeling of MKJP application. The sample of this study consisted of 20.601 married women who were not in pregnant that were drawn by using probability sampling following the sampling technique of Riskesdas 2013. Variables in this study were including the independent variables at the individual level that consisted of education, age, occupation, access to family planning services (KB), economic status and residence. As independent variables in district level were the Human Development Index (HDI, henceforth as IPM) in each districts of East Java Province, the ratio of field officers, the ratio of midwives, the ratio of community health centers and the ratio of doctors. As for the dependent variable was the use of Long-Term Contraceptive Method (LTCM or MKJP). The data were analyzed by using chi-square test and Pearson product moment correlation. The multivariable analysis was using multilevel logistic regression with 95% of Confidence Interval (CI) at the significance level of p < 0.05 and 80% of strength test. The results showed a low CPR LTCM was concentrated in districts in Madura Island and the north coast. The women which were 25 to 35 or more than 35 years old, at least high school education, working, and middle-class social status were more likely to use LTCM or MKJP. The IPM and low PLKB ratio had implications for poor CPR LTCM / MKJP.

Keywords: multilevel, long-term contraceptive methods, east java, contextual factor

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Authors: Huey-Kuo Chen

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Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper.

Keywords: travel choices, B algorithm, entropy maximization, dynamic traffic assignment

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Authors: Kaushal Jha

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India is one of the major producers of pineapple contributing a significant part in terms of total world production of pineapple. It has spread throughout tropical and subtropical regions as a commercial fruit crop. In India, the cultivation of pineapple is confined to high rainfall and humid coastal region in the peninsular India and hilly areas of Northeastern region of India. Nagaland, one of the potential states of North-East India is basically an agrarian state having been endowed with favourable agro climatic conditions and a rich bio-diversity of flora and fauna. Agriculture contributes significantly to the state’s economy. Pineapple is an important fruit crop grown in Nagaland and has a very high potential for doubling the income of farmers in comparison to the traditional practices of rice cultivation. This requires improved farm management practices as well as a genre of entrepreneurial intentions and capabilities. The present study aimed at analysing the dimensions of entrepreneurial skill development among the pineapple growers of Nagaland. Medziphema block under Dimapur district is considered as the pineapple valley of Nagaland. Pineapple grown in this area is considered as one of the best in Nagaland in terms of its sweetness as well as quality. A multistage sampling was undertaken for conducting the present study. Medziphema rural development block was selected purposively for this purpose. The sample was drawn from three leading pineapple producing villages under Medziphema block. The respondents were selected based on random sampling procedure. Data were collected from the respondents using a pre-tested structured schedule. Major findings revealed that entrepreneurial skill development was one of the important factors to augment the increase in the sustained flow of income among the target farmers. Development of farm leadership, improving self esteem, innovativeness, economic motivation, orientation towards management of farm resources and value addition were identified as important dimensions for promoting entrepreneurial skill development and bringing prosperity to the farmers.

Keywords: skill development, entrepreneurial attributes, pineapple growers, Nagaland

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Jaber Nikpouri, Arsalan Amralizadeh

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In robotics manipulators, the trajectory should be optimum, thus the torque of the robot can be minimized in order to save power. This paper includes an optimal path planning scheme for a robotic manipulator. Recently, techniques based on metaheuristics of natural computing, mainly evolutionary algorithms (EA), have been successfully applied to a large number of robotic applications. In this paper, the improved BBO algorithm is used to minimize the objective function in the presence of different obstacles. The simulation represents that the proposed optimal path planning method has satisfactory performance.

Keywords: biogeography-based optimization, path planning, obstacle detection, robotic manipulator

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Authors: Sina Saadati

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OpenSim is a well-known software in biomechanical studies. There are worthy algorithms developed in this program which are used for modeling and simulation of human motions. In this research, we analyze the OpenSim application from the computer science perspective. It is important that every application have a user-friendly interface. An effective user interface can decrease the time, costs, and energy needed to learn how to use a program. In this paper, we survey the user interface of OpenSim as an important factor of the software. Finally, we infer that there are many challenges to be addressed in the development of OpenSim.

Keywords: biomechanics, computer engineering, graphical user interface, modeling and simulation, interface effectiveness

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Leila Maleki, Ezatollah Ahmadi

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The aim of this study was to investigate the effectiveness of memory training exercise on cognitive flexibility. The method of this study was experimental. The statistical population selected 40 students 14 years old, samples were chosen by available sampling method and then they were replaced in experimental (training program) group and control group randomly and answered to Wisconsin Card Sorting Test; covariance test results indicated that there were a significant in post-test scores of experimental group (p<0.005).

Keywords: cognitive flexibility, working memory exercises, problem solving, reaction time

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Authors: Malika Elkyal

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We consider an iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm does not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays to be substantial and unpredictable. Accordingly, we note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: parallel methods, asynchronous mode, multisplitting, differential algebraic equations

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Authors: W. Shin, Y. Kim

Abstract:

This study focuses on disconfirming that wide-area networks can be made mobile, highly-available, and wireless. This methodological test shows that IPv7 and context-free grammar are mismatched. In the cases of robots, a similar tendency is also revealed. Further, we also prove that public-private key pairs could be built embedded, adaptive, and wireless. Finally, we disconfirm that although hash tables can be made distributed, interposable, and autonomous, XML and DNS can interfere to realize this purpose. Our experiments soon proved that exokernelizing our replicated Knesis keyboards was more significant than interrupting them. Our experiments exhibited degraded average sampling rate.

Keywords: collaborative communication, DNS, local-area networks, XML

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Authors: M. A. Hernández-Ceballos, M. Marín-Ferrer, G. Cinelli, L. De Felice, T. Tollefsen, E. Nweke, P. V. Tognoli, S. Vanzo, M. De Cort

Abstract:

This study analyses the latitudinal impact of the spatial and temporal distribution on the cosmogenic isotope 7Be in surface air along Europe. The long-term database of the 6 sampling sites (Ivalo, Helsinki, Berlin, Freiburg, Sevilla and La Laguna), that regularly provide data to the Radioactivity Environmental Monitoring (REM) network managed by the Joint Research Centre (JRC) in Ispra, were used. The selection of the stations was performed attending to different factors, such as 1) heterogeneity in terms of latitude and altitude, and 2) long database coverage. The combination of these two parameters ensures a high degree of representativeness of the results. In the later, the temporal coverage varies between stations, being used in the present study sampling stations with a database more or less continuously from 1984 to 2011. The mean values of 7Be activity concentration presented a spatial distribution value ranging from 2.0 ± 0.9 mBq/m3 (Ivalo, north) to 4.8 ± 1.5 mBq/m3 (La Laguna, south). An increasing gradient with latitude was observed from the north to the south, 0.06 mBq/m3. However, there was no correlation with altitude, since all stations are sited within the atmospheric boundary layer. The analyses of the data indicated a dynamic range of 7Be activity for solar cycle and phase (maximum or minimum), having been observed different impact on stations according to their location. The results indicated a significant seasonal behavior, with the maximum concentrations occurring in the summer and minimum in the winter, although with differences in the values reached and in the month registered. Due to the large heterogeneity in the temporal pattern with which the individual radionuclide analyses were performed in each station, the 7Be monthly index was calculated to normalize the measurements and perform the direct comparison of monthly evolution among stations. Different intensity and evolution of the mean monthly index were observed. The knowledge of the spatial and temporal distribution of this natural radionuclide in the atmosphere is a key parameter for modeling studies of atmospheric processes, which are important phenomena to be taken into account in the case of a nuclear accident.

Keywords: Berilium-7, latitudinal impact in Europe, seasonal and monthly variability, solar cycle

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Authors: Z. Abdullah, A. R. Hamdan

Abstract:

This paper is meant to analyze the ranking of University of Malaysia Terengganu, UMT’s website in the World Wide Web. There are only few researches have been done on comparing the ranking of universities’ websites so this research will be able to determine whether the existing UMT’s website is serving its purpose which is to introduce UMT to the world. The ranking is based on hub and authority values which are accordance to the structure of the website. These values are computed using two web-searching algorithms, HITS and SALSA. Three other universities’ websites are used as the benchmarks which are UM, Harvard and Stanford. The result is clearly showing that more work has to be done on the existing UMT’s website where important pages according to the benchmarks, do not exist in UMT’s pages. The ranking of UMT’s website will act as a guideline for the web-developer to develop a more efficient website.

Keywords: algorithm, ranking, website, web structure mining

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Authors: Hussam Ashwi, Magbool Oraiby, Ali Muyidi, Hamad Al-Oufi, Mohammed Al-Oufi, Adel Al-Juhani, Salman Al-Zemaa, Saeed Al-Shahrani, Amal Abuallah, Wedad Sherwani, Mohammed Alattas, Ibraheem Attafi

Abstract:

Ethanol must be accurately identified and quantified to establish their use and contribution in criminal cases and forensic medicine. In some situations, it may be necessary to reanalyze an old specimen; therefore, it is essential to comprehend the effect of storage conditions and how long the result of a reanalyzed specimen can be reliable and reproducible. Additionally, ethanol can be produced via multiple in vivo and in vitro processes, particularly in diabetic patients, and the results can be affected by storage conditions and time. In order to distinguish between in vivo and in vitro alcohol generation in diabetes patient urine samples, various factors should be considered. This study identifies and quantifies ethanol and EtG in diabetic patients' urine samples stored in two different settings over time. Ethanol levels were determined using gas chromatography-headspace (GC-HS), and ethyl glucuronide (EtG) levels were determined using the immunoassay (RANDOX) technique. Ten urine specimens were collected and placed in a standard container. Each specimen was separated into two containers. The specimens were divided into two groups: those kept at room temperature (25 °C) and those kept cold (2-8 °C). Ethanol and EtG levels were determined serially over a two-week period. Initial results showed that none of the specimens tested positive for ethanol or EtG. At room temperature (15-25 °C), 7 and 14 days after the sample was taken, the average concentration of ethanol increased from 1.7 mg/dL to 2 mg/dL, and the average concentration of EtG increased from 108 ng/mL to 186 ng/mL. At 2–8 °C, the average ethanol concentration was 0.4 and 0.5 mg/dL, and the average EtG concentration was 138 and 124 ng/mL seven and fourteen days after the sample was collected, respectively. When ethanol and EtG levels were determined 14 days post collection, they were considerably lower than when stored at room temperature. A considerable increase in EtG concentrations (14-day range 0–186 ng/mL) is produced during room-temperature storage, although negative initial results for all specimens. Because EtG might be produced after a sampling collection, it is not a reliable indicator of recent alcohol consumption. Given the possibility of misleading EtG results due to in vitro EtG production in the urine of diabetic patients.

Keywords: ethyl glucuronide, ethanol, forensic toxicology, diabetic

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Authors: Atin Adhikari, Sushma Kurella, Pratik Banerjee, Nabanita Mukherjee, Yamini M. Chandana Gollapudi, Bushra Shah

Abstract:

Different sharp instruments, drilling machines, and high speed rotary instruments are routinely used in dental clinics during dental cleaning. Therefore, these cleaning procedures release a lot of oral microorganisms including bacteria in clinic air and may cause significant occupational bioaerosol exposure risks for dentists, dental hygienists, patients, and dental clinic employees. Two major goals of this study were to quantify volumetric airborne concentrations of bacteria and to assess overall microbial activity in this type of occupational environment. The study was conducted in several dental clinics of southern Georgia and 15 dental cleaning procedures were targeted for sampling of airborne bacteria and testing of overall microbial activity in settled dusts over clinic floors. For air sampling, a Biostage viable cascade impactor was utilized, which comprises an inlet cone, precision-drilled 400-hole impactor stage, and a base that holds an agar plate (Tryptic soy agar). A high-flow Quick-Take-30 pump connected to this impactor pulls microorganisms in air at 28.3 L/min flow rate through the holes (jets) where they are collected on the agar surface for approx. five minutes. After sampling, agar plates containing the samples were placed in an ice chest with blue ice and plates were incubated at 30±2°C for 24 to 72 h. Colonies were counted and converted to airborne concentrations (CFU/m3) followed by positive hole corrections. Most abundant bacterial colonies (selected by visual screening) were identified by PCR amplicon sequencing of 16S rRNA genes. For understanding overall microbial activity in clinic floors and estimating a general cleanliness of the clinic surfaces during or after dental cleaning procedures, ATP levels were determined in swabbed dust samples collected from 10 cm2 floor surfaces. Concentration of ATP may indicate both the cell viability and the metabolic status of settled microorganisms in this situation. An ATP measuring kit was used, which utilized standard luciferin-luciferase fluorescence reaction and a luminometer, which quantified ATP levels as relative light units (RLU). Three air and dust samples were collected during each cleaning procedure (at the beginning, during cleaning, and immediately after the procedure was completed (n = 45). Concentrations at the beginning, during, and after dental cleaning procedures were 671±525, 917±1203, and 899±823 CFU/m3, respectively for airborne bacteria and 91±101, 243±129, and 139±77 RLU/sample, respectively for ATP levels. The concentrations of bacteria were significantly higher than typical indoor residential environments. Although an increasing trend for airborne bacteria was observed during cleaning, the data collected at three different time points were not significantly different (ANOVA: p = 0.38) probably due to high standard deviations of data. The ATP levels, however, demonstrated a significant difference (ANOVA: p <0.05) in this scenario indicating significant change in microbial activity on floor surfaces during dental cleaning. The most common bacterial genera identified were: Neisseria sp., Streptococcus sp., Chryseobacterium sp., Paenisporosarcina sp., and Vibrio sp. in terms of frequencies of occurrences, respectively. The study concluded that bacterial exposure in dental clinics could be a notable occupational biohazard, and appropriate respiratory protections for the employees are urgently needed.

Keywords: bioaerosols, hospital hygiene, indoor air quality, occupational biohazards

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Authors: Majid Afkhami, Maryam Ehsanpour, Reza Khoshnood, Zahra Khoshnood, Rastin Afkhami

Abstract:

Marine pollution is a global environmental problem. Different human activities on land, in the water and in the air contribute to the contamination of seawater, sediments and organisms with potentially toxic substances. Contaminants can be natural substances or artificially produced compounds. After discharge into the sea, contaminants can stay in the water in dissolved form or they can be removed from the water column through sedimentation to the bottom sediments. Histopathological alterations can be used as indicators for the effects of various anthropogenic pollutants on organisms and are a reflection of the overall health of the entire population in the ecosystem. These histo pathological biomarkers are closely related to other biomarkers of stress since many pollutants have to undergo metabolic activation in order to be able to provoke cellular change in the affected organism. In order to make evaluation of the effects of oil pollution, some heavy metals bioaccumulation and explore their histopathological effects on hepatocytes of Oriental sole (Euryglossa orientalis) and Deep flounder (Psettodes erumei), fishes caught from two areas of north coast of the Persian Gulf: Bandar Abbass and Bandar Lengeh. Concentrations of Ni and V in liver of both species in two sampling regions were in following order: Bandar abbass Bandar lengeh; also between two species, these quantities were higher in P. erumei than E. orientalis in both sampling regions. Histopathology of the liver shows some cellular alterations including: degeneration, necrosis and tissue disruption, and histopathological effects were severe in P. erumei than E. orientalis. Results showed that Bandar Abbass region was more polluted than Bandar Lengeh, and because Ni and V were oil pollution indicators, and two flat fishes were benthic, they can receive considerable amount of oil pollution through their biological activities like feeding. Also higher amounts of heavy metal concentrations and major histopathological effects in E. orientalis showed strong relationship between benthic habitat of the fish and amounts of received pollutants from water and sediments, because E. orientalis is more related to the bottom than P. erumei.

Keywords: heavy metals, flatfishes, Persian Gulf, oil pollution

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Authors: David Lindström

Abstract:

We evaluate the performance of a numerical method for global optimization of expensive functions. The method is using a response surface to guide the search for the global optimum. This metamodel could be based on radial basis functions, kriging, or a combination of different models. We discuss how to set the cycling parameters of the optimization method to get a balance between local and global search. We also discuss the eventual problem with Runge oscillations in the response surface.

Keywords: expensive function, infill sampling criterion, kriging, global optimization, response surface, Runge phenomenon

Procedia PDF Downloads 580