Search results for: data storage

Authors: Matheus Müller, Delma Vidal

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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.

Keywords: consolidation, dewatering, geotextile drying bed, geotextile tube

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Authors: Cristian Matti, Valerie Fowles, Eva Enyedi, Piotr Pogorzelski

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The system mapping process can be defined as a knowledge service where a team of facilitators, experts and practitioners facilitate a guided conversation, enable the exchange of information and support an iterative curation process. System mapping processes rely on science-based tools to introduce and simplify a variety of components and concepts of socio-technical systems through metaphors while facilitating an interactive dialogue process to enable the design of co-created maps. System maps work then as “artifacts” to provide information and focus the conversation into specific areas around the defined challenge and related decision-making process. Knowledge management facilitates the curation of that data gathered during the system mapping sessions through practices of documentation and subsequent knowledge co-production for which common practices from data science are applied to identify new patterns, hidden insights, recurrent loops and unexpected elements. This study presents empirical evidence on the application of these techniques to explore mechanisms by which visual tools provide guiding principles to portray system components, key variables and types of data through the lens of climate change. In addition, data science facilitates the structuring of elements that allow the analysis of layers of information through affinity and clustering analysis and, therefore, develop simple indicators for supporting the decision-making process. This paper addresses methodological and empirical elements on the horizontal learning process that integrate system mapping through visual tools, interpretation, cognitive transformation and analysis. The process is designed to introduce practitioners to simple iterative and inclusive processes that create actionable knowledge and enable a shared understanding of the system in which they are embedded.

Keywords: indicators, knowledge management, system mapping, visual tools

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Authors: Virginia Martin Torrejon, Binjie Wu

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Gelatine is a protein biopolymer obtained from the partial hydrolysis of animal tissues which contain collagen, the primary structural component in connective tissue. Gelatine hydrogels have attracted considerable research in recent years as an alternative to synthetic materials due to their outstanding gelling properties, biocompatibility and compostability. Surfactants, such as sodium dodecyl sulfate (SDS), are often used in hydrogels solutions as surface modifiers or solubility enhancers, and their incorporation can influence the hydrogel’s viscoelastic properties and, in turn, its processing and applications. Literature usually focuses on studying the impact of formulation parameters (e.g., gelatine content, gelatine strength, additives incorporation) on gelatine hydrogels properties, but processing parameters, such as curing temperature, are commonly overlooked. For example, some authors have reported a decrease in gel strength at lower curing temperatures, but there is a lack of research on systematic viscoelastic characterisation of high strength gelatine and gelatine-SDS systems at a wide range of curing temperatures. This knowledge is essential to meet and adjust the technological requirements for different applications (e.g., viscosity, setting time, gel strength or melting/gelling temperature). This work investigated the effect of curing temperature (10, 15, 20, 23 and 25 and 30°C) on the elastic modulus (G’) and melting temperature of high strength gelatine-SDS hydrogels, at 10 wt% and 20 wt% gelatine contents, by small-amplitude oscillatory shear rheology coupled with Fourier Transform Infrared Spectroscopy. It also correlates the gel strength obtained by rheological measurements with the gel strength measured by texture analysis. Gelatine and gelatine-SDS hydrogels’ rheological behaviour strongly depended on the curing temperature, and its gel strength and melting temperature can be slightly modified to adjust it to given processing and applications needs. Lower curing temperatures led to gelatine and gelatine-SDS hydrogels with considerably higher storage modulus. However, their melting temperature was lower than those gels cured at higher temperatures and lower gel strength. This effect was more considerable at longer timescales. This behaviour is attributed to the development of thermal-resistant structures in the lower strength gels cured at higher temperatures.

Keywords: gelatine gelation kinetics, gelatine-SDS interactions, gelatine-surfactant hydrogels, melting and gelling temperature of gelatine gels, rheology of gelatine hydrogels

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Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

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Data in IT systems in enterprises has been growing at a phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several artificial intelligence (AI/ML) and business intelligence (BI) tools and technologies available in the marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information, and intelligence components, and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise

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Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: multi-temporal satellite image, urban growth, non-stationary, stochastic model

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Authors: Hanefi Cinar, Musa Cibuk, Ismail Erturk, Fikri Aggun, Munip Geylani

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Mobile Wireless Sensor Networks (MWSNs) carry heterogeneous data traffic with different urgency and quality of service (QoS) requirements. There are a lot of studies made on energy efficiency, bandwidth, and communication methods in literature. But delay, high throughput, utility parameters are not well considered. Increasing demand for real-time data transfer makes these parameters more important. In this paper we design new MAC protocol which is delay constrained and targets for improving delay, utility, and throughput performance of the network and finding solutions on collision and interference problems. Protocol improving QoS requirements by using TDMA, FDM, and OFDMA hybrid communication methods with multi-channel communication.

Keywords: MWSN, delay, hybrid MAC, TDMA, FDM, OFDMA

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Authors: M. B. Sokoto, L. Tanko, Y. M. Abdullahi

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The study aimed at examining the impact of climatic factors (rainfall, minimum and maximum temperature) on the productivity of major cereals in Sokoto state, Nigeria. Secondary data from 1997-2008 were used in respect of annual yield of Major cereals crops (maize, millet, rice, and sorghum (t ha-1). Data in respect of climate was collected from Sokoto Energy Research Centre (SERC) for the period under review. Data collected was analyzed using descriptive statistics, correlation and regression analysis. The result of the research reveals that there is variation in the trend of the climatic factors and also variation in cereals output. The effect of average temperature on yields has a negative effect on crop yields. Similarly, rainfall is not significant in explaining the effect of climate on cereal crops production. The study has revealed to some extend the effect of climatic variables, such as rainfall, relative humidity, maximum and minimum temperature on major cereals production in Sokoto State. This will assist in planning ahead in cereals production in the area. Other factors such as soil fertility, correct timing of planting and good cultural practices (such as spacing of strands), protection of crops from weeds, pests and diseases and planting of high yielding varieties should also be taken into consideration for increase yield of cereals.

Keywords: cereals, climate, impact, major, productivity

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Authors: Hanaa A. Al-Gaoudi, Hassan Ebeid

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The research investigates the materials and processes used in the manufacturing of an Egyptian polychrome cartonnage mummy mask with the aim of dating this object and establishing trade patterns of certain materials that were used and available at the time of ancient Egypt. This anonymous-source object was held in the basement storage of the Egyptian Museum in Cairo (EMC) and has never been on display. Furthermore, there is no information available regarding its owner, provenance, date, and even the time of its possession by the museum. Moreover, the object is in a very poor condition where almost two-thirds of the mask was bent and has never received any previous conservation treatment. This research has utilized well-established multi-analytical methods to identify the considerable diversity of materials that have been used in the manufacturing of this object. These methods include Computed Tomography Scan (CT scan) to acquire detailed pictures of the inside physical structure and condition of the bended layers. Dino-Lite portable digital microscope, scanning electron microscopy with energy dispersive X-ray spectrometer (SEM-EDX), and the non-invasive imaging technique of multispectral imaging (MSI) to obtain information about the physical characteristics and condition of the painted layers and to examine the microstructure of the materials. Portable XRF Spectrometer (PXRF) and X-Ray powder diffraction (XRD) to identify mineral phases and the bulk element composition in the gilded layer, ground, and pigments; Fourier-transform infrared (FTIR) to identify organic compounds and their molecular characterization; accelerator mass spectrometry (AMS 14C) to date the object. Preliminary results suggest that there are no human remains inside the object, and the textile support is linen fibres with tabby weave 1/1 and these fibres are in a very bad condition. Several pigments have been identified, such as Egyptian blue, Magnetite, Egyptian green frit, Hematite, Calcite, and Cinnabar; moreover, the gilded layers are pure gold and the binding media in the pigments is Arabic gum and animal glue in the textile support layer.

Keywords: analytical methods, Egyptian museum, mummy mask, pigments, textile

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Authors: Ya-Mei Chang

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This research is intended to apply spatio-temporal point process methods to the dengue fever data in Tainan. The spatio-temporal intensity function of the dataset is assumed to be separable. The kernel estimation is a widely used approach to estimate intensity functions. The intensity function is very helpful to study the relation of the spatio-temporal point process and some covariates. The covariate effects might be nonlinear. An nonparametric smoothing estimator is used to detect the nonlinearity of the covariate effects. A fitted parametric model could describe the influence of the covariates to the dengue fever. The correlation between the data points is detected by the K-function. The result of this research could provide useful information to help the government or the stakeholders making decisions.

Keywords: dengue fever, spatial point process, kernel estimation, covariate effect

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Evagelia Makri, Maria Tsourela, Dimitris Paschaloudis, Dafni M. Nerantzaki

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One of the biggest financial and social problems, which at the same time constitute one of the greater challenges that Greek society faces today, is the illegal avoidance of tax payments. Tax evasion may negate financial data and community budgets, as well as breed financial chaos. This research seeks to reflect Greek reality concerning tax measures. Also, there will be an effort to record the factors surrounding tax evasion. Greek tax system’s data will be rendered in financial terms. Questionnaires will be handed out to tax payers, and interviews will be conducted to taxmen. The quantitative analysis of the questionnaire answers will define the tax payers’ opinion towards the existence of tax evasion. The qualitative analysis of the interviews will reveal the main reason that boosts tax evasion. At the end, there will be some realistic proposals about how to better collect taxes, through the creation of a strong regulatory mechanism.

Keywords: tax evasion, tax collection measures, insurance recovery measures, Greek tax system

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Authors: Rudra Prasad Khanal

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Introduction: Non-communicable disease, such as cancer, has spread all over the world for some last decades. However, every nation has experienced a burden from the development of technology. In the context of Nepal, 10 to 15 thousand new cancer incidences are being registered in different hospitals for treatment. Since the date of starting nuclear medicine at Bir Hospital in 1998, cancer patients have been getting treatment regularly. According to the data of the population-based cancer registry, approximately 60% of the population having a middle-class income is being affected by cancer in Nepal. Methods and Materials: The study is aimed to find out the particular place where the population density of new cancer incidence is highest in Nepal and to inform the concerned regulatory body that is working on cancer screening and early detection for the proper treatment from the beginning. In order to identify the areas with the highest population density of new cancer incidence, all the data of cancer patients were collected from five different renowned hospitals and also from the population-based cancer registry center and then analyzed the data. The history of cancer patients was studied from 2003 to 2020, but here the data are analyzed from 2015 to 2020 only to find the latest trend in cancer incidence. Results: In the five major hospitals in Nepal, the total new cancer incidence was 61783 from 2015 to 2020. Out of those, 34617 were female, and 27176 were male. This research shows that female cancer patients were more every year. In the male, lung cancer patients more than cancer of other organs, but in females, the number of breast cancer patients was greatest. The age-adjusted mortality rate for males in Kathmandu valley was 36.3, and for females was 27.0 per 100,000 population. The cancer incidence and mortality rate were slightly lesser in other districts of Nepal. This rate increased with the increase in the age of people. Over 60 years, cancer incidence and mortality rates have been found to increase rapidly. Conclusion: This research supports conducting the program of cancer screening and early detection at Kathmandu valley with high priority and then Morang, Rukum, SSDM, etc., to control cancer.

Keywords: cancer incidence, research scholar, Tribhuvan University, Bhaktapur Cancer Hospital, Nepal

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Authors: Renata Josipovic, Ante Cvitkovic

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Particulate matter belongs to pollutants that can lead to respiratory problems or premature death due to exposure (long-term, short-term) to these substances, all depending on the severity of the effects. The importance of the study is to determine whether the existing climatic conditions in the period from January 1st to August 31st, 2018 increased the number of emergency interventions in Slavonski Brod with regard to pollutants hydrogen sulfide and particles less than 10 µm (PM10) and less than 2.5 µm (PM2.5). Analytical data of the concentration of pollutants are collected from the Croatian Meteorological and Hydrological Service, which monitors the operation of two meteorological stations in Slavonski Brod, as well as climatic conditions. Statistics data of emergency interventions were collected from the Emergency Medicine Department of Slavonski Brod. All data were compared (air pollution, emergency interventions) according to climatic conditions (air humidity and air temperature) and statistically processed. Statistical significance, although weak positive correlation PM2.5 (correlation coefficient 0.147; p = 0.036), determined PM10 (correlation coefficient 0.122; p = 0.048), hydrogen sulfide (correlation coefficient 0.141; p = 0.035) with max. temperature (correlation coefficient 0.202; p = 0.002) with number of interventions. The association between mean air humidity was significant but negative (correlation coefficient - 0.172; p = 0.007). The values of the influence of air pressure are not determined. As the problem of air pollution is very complex, coordinated action at many levels is needed to reduce air pollution in Slavonski Brod and consequences that can affect human health.

Keywords: emergency interventions, human health, hydrogen sulfide, particulate matter

Procedia PDF Downloads 157

Authors: J. Cadby, K. Miyazawa

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Information and Communication Technology (ICT) has been widely adopted into the agricultural landscape with advancements of mobile connectivity and data accessibility. In developed nations, mobile-technology is well integrated into marketing transactions, and also plays a crucial role in making data-driven decisions on-farm. In developing nations, mobile banking and access to agricultural extension services allow for informed decision-making and smoother transactions. In addition, the availability of updated and readily available market and climate data provides a negotiation platform, reducing economic risks for farmers worldwide. The total usage of mobile technology has risen over the past 20 years, and almost three-quarters of the world’s population subscribes to mobile technology. This study reviewed mobile technology integration into agricultural systems in developing and developed nations. Data from secondary sources were collected and investigated. The objectives of the study include a review of the success of mobile banking transactions in developing nations, and a review of application and SMS based services for direct marketing in both developed and developing nations. Rural farmers in developing countries with access to diverse m-banking options experienced increased access to farm investment resources with the use of mobile banking technology. Rural farmers involved in perishable crop production were also more likely to benefit from mobile platform sales participation. ICT programs reached through mobile application and SMS increased access to agricultural extension materials and marketing tools for demographics that faced literacy-challenges and isolated markets. As mobile technology becomes more ubiquitous in the global agricultural system, training and market opportunities to facilitate mobile usage in developing agricultural systems are necessary. Digital skills training programs are necessary in order to improve equal global adoption of ICT in agriculture.

Keywords: market participation, mobile banking, mobile technology, rural farming

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgianna Duarte

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The social problems of early adolescents in Northeast China were examined with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). In this study, the data consisted of 2532 early adolescents. The relevant variables such as sports activities, hobbies, chores and the number of close friends, as independent variables have been included in this study. The stratified sampling method was used to collect data from 2532 participants. The analysis results indicated that sports activities, hobbies, chores and the number of close friends, as predictors can be used in a predictive model, which significantly predict the social problem T-score.

Keywords: social problems, ASEBA, early adolescents, predictive Model

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Authors: D. S. Fardhyanti, Megawati, W. B. Sediawan

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Coal tar is a liquid by-product of the process of coal gasification and carbonation. This liquid oil mixture contains various kinds of useful compounds such as aromatic compounds and phenolic compounds. These compounds are widely used as raw material for insecticides, dyes, medicines, perfumes, coloring matters, and many others. This research investigates thermodynamic modelling of liquid-liquid equilibria (LLE) in the separation of phenol from the coal tar by solvent extraction. The equilibria are modeled by ternary components of Wohl, Van Laar, and Three-Suffix Margules models. The values of the parameters involved are obtained by curve-fitting to the experimental data. Based on the comparison between calculated and experimental data, it turns out that among the three models studied, the Three-Suffix Margules seems to be the best to predict the LLE of p-Cresol mixtures for those system.

Keywords: coal tar, phenol, Wohl, Van Laar, Three-Suffix Margules

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Navpreet Kaur, Himkusha Thakur, Nirmal Prabhakar

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The most controversial issue in crop production is the use of Organophosphate insecticides. This is evident in many reports that Organophosphate (OP) insecticides, among the broad range of pesticides are mainly involved in acute and chronic poisoning cases. OPs detection is of crucial importance for health protection, food and environmental safety. In our study, a nanocomposite of poly (3,4 ethylenedioxythiophene) (PEDOT) and multi-walled carbon nanotubes (MWCNTs) has been deposited electrochemically onto the surface of fluorine doped tin oxide sheets (FTO) for the analysis of malathion OP. The -COOH functionalization of MWCNTs has been done for the covalent binding with amino groups of AChE enzyme. The use of PEDOT-MWCNT films exhibited an excellent conductivity, enables fast transfer kinetics and provided a favourable biocompatible microenvironment for AChE, for the significant malathion OP detection. The prepared biosensors were characterized by Fourier transform infrared spectrometry (FTIR), Field emission-scanning electron microscopy (FE-SEM) and electrochemical studies. Various optimization studies were done for different parameters including pH (7.5), AChE concentration (50 mU), substrate concentration (0.3 mM) and inhibition time (10 min). Substrate kinetics has been performed and studied for the determination of Michaelis Menten constant. The detection limit for malathion OP was calculated to be 1 fM within the linear range 1 fM to 1 µM. The activity of inhibited AChE enzyme was restored to 98% of its original value by 2-pyridine aldoxime methiodide (2-PAM) (5 mM) treatment for 11 min. The oxime 2-PAM is able to remove malathion from the active site of AChE by means of trans-esterification reaction. The storage stability and reusability of the prepared biosensor is observed to be 30 days and seven times, respectively. The application of the developed biosensor has also been evaluated for spiked lettuce sample. Recoveries of malathion from the spiked lettuce sample ranged between 96-98%. The low detection limit obtained by the developed biosensor made them reliable, sensitive and a low cost process.

Keywords: PEDOT-MWCNT, malathion, organophosphates, acetylcholinesterase, biosensor, oxime (2-PAM)

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Authors: Chen Chuanzhi, Guo Yunyun

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The large linear array feeding parabolic cylindrical antenna of the satellite has the ability of large-area line focusing, multi-directional beam clusters simultaneously in a certain azimuth plane and elevation plane, corresponding quickly to different orientations and different directions in a wide frequency range, dual aiming of frequency and direction, and combining space power. Therefore, the large-diameter parabolic cylindrical antenna has become one of the new development directions of spaceborne antennas. Limited by the size of the rocked fairing, the large-diameter spaceborne antenna is required to be small mass and have a deployment function. After being orbited, the antenna can be deployed by expanding and be stabilized. However, few types of structures can be used to construct large cylindrical shell structures in existing structures, which greatly limits the development and application of such antennas. Aiming at high structural efficiency, the geometrical characteristics of parabolic cylinders and mechanism topological mapping law to the expandable truss are studied, and the basic configuration of deployable truss with cylindrical shell is structured. Then a modular truss parabolic cylindrical antenna is designed in this paper. The antenna has the characteristics of stable structure, high precision of reflecting surface formation, controllable motion process, high storage rate, and lightweight, etc. On the basis of the overall configuration comprehensive theory and optimization method, the structural stiffness of the modular truss parabolic cylindrical antenna is improved. And the bearing density and impact resistance of support structure are improved based on the internal tension optimal distribution method of reflector forming. Finally, a truss-type cylindrical deployable support structure with high constriction-deployment ratio, high stiffness, controllable deployment, and low mass is successfully developed, laying the foundation for the application of large-diameter parabolic cylindrical antennas in satellite antennas.

Keywords: linear array feed antenna, truss type, parabolic cylindrical antenna, spaceborne antenna

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Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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Authors: Yuliang Liu, Thomas Lavallee, Mary Weishaar, Gretchen Fricke, Huaibo Xin

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The longitudinal study was designed to investigate the impacts of the International Training Program in Pedagogy (ITPP) at a midwestern institution in the United States on the visiting scholars from China from 2012-18. The study used the survey research method and involved 48 visiting scholars from Northwest Normal University in China in those eight ITPP cohorts. The results of both quantitative and qualitative data were critically examined and indicated both types of data sources revealed similar findings. It was found that the ITPP has significantly affected all scholars' instruction in China. International implications resulted from the study.

Keywords: international training program in pedagogy, visiting scholars, survey research method, International implications

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Authors: Tanja Salary

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This paper discusses a study conducted in a juvenile justice facility regarding medication errors. It includes an introduction to data collected about medication errors in a juvenile justice facility from 2011 - 2019 and explores contributing factors that relate to those errors. The data was obtained from electronic incident records of medication errors that were documented from the years 2011 through 2019. In addition, the presentation reviews both current and historical research of empirical data about patient safety standards and quality care comparing traditional health care facilities to juvenile justice residential facilities and acknowledges a gap in research. The theoretical/conceptual framework for the research study was Bandura and Adams’s self-efficacy theory of behavioral change and Mark Friedman’s results-based accountability theory. Despite the lack of evidence in previous studies addressing medication errors in juvenile justice facilities, this presenter will share information that adds to the body of knowledge, including the potential relationship of medication errors and contributing factors of race and age. Implications for future research include the effect that education and training will have on the communication among juvenile justice staff, including nurses, who administer medications to juveniles to ensure adherence to patient safety standards. There are several opportunities for future research concerning other characteristics about factors that may affect medication administration errors within the residential juvenile justice facility.

Keywords: Juvenile justice, medication errors, juveniles, error reduction strategies

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgiana Duarte

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This study explored early adolescents’ anxious and depressed syndromes in Northeast China. Specifically, the study examined anxious and depressed behaviors and the relationship to education environments. The purpose is to examine how the elements of educational environments and the early adolescents’ behaviors as independent variables influence and possibly predict the early adolescents’ anxious/depressed problems. Achenbach System of Empirically Based Assessment (ASEBA), was the instrument, used in collection of data. A stratified sampling method was utilized to collect data from 2532 participants in seven schools. The results indicated that several background variables influenced anxious/depressed problem. Specifically, age, grade, sports activities and hobbies had a relationship with the anxious/depressed variable.

Keywords: anxious/depressed problems, CBCL, empirically-based assessment, internalizing problems

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Authors: Ramzi Bekri Umer

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Aim: This study attempts to investigate the causes and difficulties with women’s incarceration as well as threat for their reintegration after release from prison with emphasis on the correctional facility of Haramaya city. Method and Methodology: Both quantitative and qualitative research methods were employed in this study; key informant interviews and participant observation were utilized to gather qualitative data, while crosssectional and descriptive research designs were used to gather quantitative data. Findings: This study shows that the women's incarceration was caused by their family histories, genderbased violence, illiteracy, and socioeconomic issues. The principal charges made against the female culprits were theft, vandalism, murder, and moral perversion. A poor quality of life in prison, concerns about family dissolution, emotional instability, financial difficulties, and a lack of spirituality were the main causes of unhappiness for the women behind bars, while social stigma, mistrust, and retaliation fears were the main obstacles to the women's ability to reintegrate into their families and communities. Theoretical Importance: This study involves incarcerated women at correctional center of Haramaya who committed various types of crimes. The local government sectors and non-governmental organization will gain from the study in order to create workable plans to reduce women's criminality and the growing number of female lawbreakers. Local communities and other governmental and nongovernmental partners will be able to support gender equality initiatives that seek to eradicate gender-based violence and discrimination, which worsen the criminality of women. Data Collection and Analysis Procedures: The quantitative and qualitative data were collected prospectively from a sample of 100 women prisoners. Quantitative data were analyzed using descriptive statistics, whereas, thematic analysis, were used for qualitative data. Question Answered: 1. What are the main causes women’s imprisonment in Haramaya city correctional facility. 2. What are the main obstacles of the women's ability to reintegrate into their families and communities after released from incarceration. Conclusion: The study concludes that incarcerated women experience a tremendous impact on their daily life. It highlights the importance of addressing factors such as family backgrounds, gender-based violence, illiteracy and socio-economic problem to decrease the number of women imprisonment. Detention environment, fear for family breakup, financial hardship and deprivation of spiritual life are the major sources of distress among the incarcerated women.

Keywords: Ethiopia, women prisoner, incarceration, reintegration

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Authors: Muluken Biadgelegn Wollele, Mebratu Assaye Mengistu

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Nanotechnology has created new opportunities for improving industrial efficiency and performance. One of the proposed approaches to improving the effectiveness of temperature exchangers is the use of nanofluids to improve heat transfer performance. The thermal conductivity of nanoparticles, as well as their size, diameter, and volume concentration, all played a role in influencing the rate of heat transfer. Nanofluids are commonly used in automobiles, energy storage, electronic component cooling, solar absorbers, and nuclear reactors. Convective heat transfer must be improved when designing thermal systems in order to reduce heat exchanger size, weight, and cost. Using roughened surfaces to promote heat transfer has been tried several times. Thus, both active and passive heat transfer methods show potential in terms of heat transfer improvement. There will be an added advantage of enhanced heat transfer due to the two methods adopted; however, pressure drop must be considered during flow. Thus, the current research aims to increase heat transfer by adding a twisted tap insert in a plain tube using a working fluid hybrid nanofluid (Al₂O₃-Cu) with a base fluid of water. A circular duct with inserts, a tube length of 3 meters, a hydraulic diameter of 0.01 meters, and tube walls with a constant heat flux of 20 kW/m² and a twist ratio of 125 was used to investigate Al₂O₃-Cu/H₂O hybrid nanofluid with inserts. The temperature distribution is better than with conventional tube designs due to stronger tangential contact and swirls in the twisted tape. The Nusselt number values of plain twisted tape tubes are 1.5–2.0 percent higher than those of plain tubes. When twisted tape is used instead of plain tube, performance evaluation criteria improve by 1.01 times. A heat exchanger that is useful for a number of heat exchanger applications can be built utilizing a mixed flow of analysis that incorporates passive and active methodologies.

Keywords: nanofluids, active method, passive method, Nusselt number, performance evaluation criteria

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Authors: Caroline E. Mendes, Alberto C. Badino

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Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while  was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching  of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.

Keywords: bubble column, internal loop airlift, gas hold-up, kLa

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Sarchil H. Qader, Andrew Harfoot, Mathias Kuepie, Sabrina Juran, Attila Lazar, Andrew J. Tatem

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The need for high-quality, reliable, and timely population data, including demographic information, to support the achievement of the sustainable development goals (SDGs) in all countries was recognized by the United Nations' 2030 Agenda for sustainable development. However, many low and middle-income countries lack reliable and recent census data. To achieve reliable and accurate census and survey outputs, up-to-date census enumeration areas and digital national sampling frames are critical. Census enumeration areas (EAs) are the smallest geographic units for collection, disseminating, and analyzing census data and are often used as a national sampling frame to serve various socio-economic surveys. Even for countries that are wealthy and stable, creating and updating EAs is a difficult yet crucial step in preparing for a national census. Such a process is commonly done manually, either by digitizing small geographic units on high-resolution satellite imagery or walking the boundaries of units, both of which are extremely expensive. We have developed a user-friendly tool that could be employed to generate draft EA boundaries automatically. The tool is based on high-resolution gridded population and settlement datasets, GPS household locations, building footprints and uses publicly available natural, man-made and administrative boundaries. Initial outputs were produced in Burkina Faso, Paraguay, Somalia, Togo, Niger, Guinea, and Zimbabwe. The results indicate that the EAs are in line with international standards, including boundaries that are easily identifiable and follow ground features, have no overlaps, are compact and free of pockets and disjoints, and the boundaries are nested within administrative boundaries.

Keywords: enumeration areas, national sampling frame, gridded population data, preEA tool

Procedia PDF Downloads 133