Search results for: monitoring networks

Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker

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Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.

Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia

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Authors: Naveen Kumar B. T., Anuj Tyagi, Prabjeet Singh, Shanthanagouda A. H., Sumeet Rai

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Inland saline water resources are gaining the importance in expanding the aquaculture activities to mitigate the nutritional and food security issues of the world. For profitable and sustainable aquaculture practices, scientific farming, biosecurity measure, and best fish health management should be the integral part of developmental activities. Keeping in line with global awareness and trends, the Indian government has taken an innovative step to conduct disease surveillance and awareness programme for aquatic disease through network project. This ‘National Surveillance Programme for Aquatic Animal Diseases (NSPAAD)’ is being implemented in collaboration of national institutes and state agriculture universities with funding support from National Fisheries Development Board (NFDB), Govt. of India. Guru Angad Dev Veterinary and Animal Sciences University (GADVASU), Ludhiana, an NSPAAD collaborator, has been actively engaged in disease surveillance in the Indian state of Punjab. Shrimp farming in inland saline areas of Punjab is expanding at a tremendous pace under the guidance of GADVASU along with the support of State Fisheries Department. Under this national disease surveillance programme, we reported Enterocytozoon hepatopenaei (EHP) infection in the Litopenaeus vannamei cultured in the inland saline waters. Polymerase chain reaction (PCR) based diagnosis was carried out using the OIE (World Organisation for Animal Health) protocol. It was observed that out of 20 shrimp farms, two farms were 1st step PCR positive and two more farms were nested PCR positive. All the EHP positive ponds had shown the white faeces along with mortalities at very low rate. Therefore, implementation of biosecurity and continuous surveillance and monitoring program for finfish and shellfish aquaculture are in need of the hour to prevent and control the large-scale disease outbreaks and subsequent economic losses.

Keywords: disease, EHP, inland saline water, shrimp culture

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Authors: Jia-Jane Shuai

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Purpose of this research aims to improve understanding of the nature of online religion by examining the religious social websites. What motivates individual users to use the online religious social websites, and which factors affect those motivations. We survey various online religious social websites provided by different religions, especially the Taiwanese folk religion. Based on the theory of the Content Analysis and Social Network Analysis, religious social websites and religious web activities are examined. This research examined the folk religion websites’ presentation and contents that promote the religious use of the Internet in Taiwan. The difference among different religions and religious websites also be compared. First, this study used keywords to examine what types of messages gained the most clicks of “Like”, “Share” and comments on Facebook. Dividing the messages into four media types, namely, text, link, video, and photo, reveal which category receive more likes and comments than the others. Meanwhile, this study analyzed the five dialogic principles of religious websites accessed from mobile phones and also assessed their mobile readiness. Using the five principles of dialogic theory as a basis, do a general survey on the websites with elements of online religion. Second, the project analyzed the characteristics of Taiwanese participants for online religious activities. Grounded by social network analysis and text mining, this study comparatively explores the network structure, interaction pattern, and geographic distribution of users involved in communication networks of the folk religion in social websites and mobile sites. We studied the linkage preference of different religious groups. The difference among different religions and religious websites also be compared. We examined the reasons for the success of these websites, as well as reasons why young users accept new religious media. The outcome of the research will be useful for online religious service providers and non-profit organizations to manage social websites and internet marketing.

Keywords: content analysis, online religion, social network analysis, social websites

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Andres Gonzalez, Adam Boies, Jacob Swanson, David Kittelson

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The concern of the indoor air quality (IAQ) has been increasing due to its risk to human health. The smoking, sweeping, and stove and stovetop use are the activities that have a major contribution to the indoor air pollution. Outdoor air pollution also affects IAQ. The most important factors over IAQ from cooking activities are the materials, fuels, foods, and ventilation. The low-cost, mobile air quality monitoring (LCMAQM) sensors, is reachable technology to assess the IAQ. This is because of the lower cost of LCMAQM compared to conventional instruments. The IAQ was assessed, using LCMAQM, during cooking activities in a University of Minnesota graduate-housing evaluating different ventilation systems. The gases measured are carbon monoxide (CO) and carbon dioxide (CO₂). The particles measured are particle matter (PM) _2.5 micrometer (µm) and lung deposited surface area (LDSA). The measurements are being conducted during April 2019 in Como Student Community Cooperative (CSCC) that is a graduate housing at the University of Minnesota. The measurements are conducted using an electric stove for cooking. The amount and type of food and oil using for cooking are the same for each measurement. There are six measurements: two experiments measure air quality without any ventilation, two using an extractor as mechanical ventilation, and two using the extractor and windows open as mechanical and natural ventilation. 3The results of experiments show that natural ventilation is most efficient system to control particles and CO₂. The natural ventilation reduces the concentration in 79% for LDSA and 55% for PM_2.5, compared to the no ventilation. In the same way, CO₂ reduces its concentration in 35%. A well-mixed vessel model was implemented to assess particle the formation and decay rates. Removal rates by the extractor were significantly higher for LDSA, which is dominated by smaller particles, than for PM_2.5, but in both cases much lower compared to the natural ventilation. There was significant day to day variation in particle concentrations under nominally identical conditions. This may be related to the fat content of the food. Further research is needed to assess the impact of the fat in food on particle generations.

Keywords: cooking, indoor air quality, low-cost sensor, ventilation

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Authors: Sarre Nzaba, Bulelwa Ntsendwana, Bekkie Mamba, Alex Kuvarega

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The discharge of azo dyes such as Brilliant black (BB) into the water bodies has carcinogenic and mutagenic effects on humankind and the ecosystem. Conventional water treatment techniques fail to degrade these dyes completely thereby posing more problems. Advanced oxidation processes (AOPs) are promising technologies in solving the problem. Anatase type nitrogen-platinum (N, Pt) co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine terminated polyamidoamine generation 1 (PG1) as a template and source of nitrogen. The resultant photocatalysts were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X‐ray photoelectron spectroscopy (XPS), UV‐Vis diffuse reflectance spectroscopy, photoluminescence spectroscopy (PL), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy (RS), thermal gravimetric analysis (TGA). The results showed that the calcination atmosphere played an important role in the morphology, crystal structure, spectral absorption, oxygen vacancy concentration, and visible light photocatalytic performance of the catalysts. Anatase phase particles ranging between 9- 20 nm were also confirmed by TEM, SEM, and analysis. The origin of the visible light photocatalytic activity was attributed to both the elemental N and Pd dopants and the existence of oxygen vacancies. Co-doping imparted a shift in the visible region of the solar spectrum. The visible light photocatalytic activity of the samples was investigated by monitoring the photocatalytic degradation of brilliant black dye. Co-doped TiO₂ showed greater photocatalytic brilliant black degradation efficiency compared to singly doped N-TiO₂ or Pd-TiO₂ under visible light irradiation. The highest reaction rate constant of 3.132 x 10-2 min⁻¹ was observed for N, Pd co-doped TiO₂ (2% Pd). The results demonstrated that the N, Pd co-doped TiO₂ (2% Pd) sample could completely degrade the dye in 3 h, while the commercial TiO₂ showed the lowest dye degradation efficiency (52.66%).

Keywords: brilliant black, Co-doped TiO₂, polyamidoamine generation 1 (PAMAM G1), photodegradation

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Authors: Choonsik Lee, Les Folio

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Pregnant patients may undergo CT in emergencies unrelated with pregnancy, and potential risk to the developing fetus is of concern. It is critical to accurately estimate fetal organ doses in CT scans. We developed a fetal organ dose calculation tool using pregnancy-specific computational phantoms combined with Monte Carlo radiation transport techniques. We adopted a series of pregnancy computational phantoms developed at the University of Florida at the gestational ages of 8, 10, 15, 20, 25, 30, 35, and 38 weeks (Maynard et al. 2011). More than 30 organs and tissues and 20 skeletal sites are defined in each fetus model. We calculated fetal organ dose-normalized by CTDIvol to derive organ dose conversion coefficients (mGy/mGy) for the eight fetuses for consequential slice locations ranging from the top to the bottom of the pregnancy phantoms with 1 cm slice thickness. Organ dose from helical scans was approximated by the summation of doses from multiple axial slices included in the given scan range of interest. We then compared dose conversion coefficients for major fetal organs in the abdominal-pelvis CT scan of pregnancy phantoms with the uterine dose of a non-pregnant adult female computational phantom. A comprehensive library of organ conversion coefficients was established for the eight developing fetuses undergoing CT. They were implemented into an in-house graphical user interface-based computer program for convenient estimation of fetal organ doses by inputting CT technical parameters as well as the age of the fetus. We found that the esophagus received the least dose, whereas the kidneys received the greatest dose in all fetuses in AP scans of the pregnancy phantoms. We also found that when the uterine dose of a non-pregnant adult female phantom is used as a surrogate for fetal organ doses, root-mean-square-error ranged from 0.08 mGy (8 weeks) to 0.38 mGy (38 weeks). The uterine dose was up to 1.7-fold greater than the esophagus dose of the 38-week fetus model. The calculation tool should be useful in cases requiring fetal organ dose in emergency CT scans as well as patient dose monitoring.

Keywords: computed tomography, fetal dose, pregnant women, radiation dose

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Authors: Khanyisile Mnguni, Muthukrishnavellaisamy Kumarasamy, Jeff C. Smithers

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Umgeni Water is a water board that supplies most parts of KwaZulu Natal with bulk portable water. Currently, Umgeni Water is running its distribution system based on required reservoir levels and demands and does not consider the energy cost at different times of the day, number of pump switches, and background leakages. Including these constraints can reduce operational cost, energy usage, leakages, and increase performance. Optimising pump schedules can reduce energy usage and costs while adhering to hydraulic and operational constraints. Umgeni Water has installed an online hydraulic software, WaterNet Advisor, that allows running different operational scenarios prior to implementation in order to optimise the distribution system. This study will investigate operation scenarios using optimisation techniques and WaterNet Advisor for a local water distribution system. Based on studies reported in the literature, introducing pump scheduling optimisation can reduce energy usage by approximately 30% without any change in infrastructure. Including tariff structures in an optimisation problem can reduce pumping costs by 15%, while including leakages decreases cost by 10%, and pressure drop in the system can be up to 12 m. Genetical optimisation algorithms are widely used due to their ability to solve nonlinear, non-convex, and mixed-integer problems. Other methods such as branch and bound linear programming have also been successfully used. A suitable optimisation method will be chosen based on its efficiency. The objective of the study is to reduce energy usage, operational cost, and leakages, and the feasibility of optimal solution will be checked using the Waternet Advisor. This study will provide an overview of the optimisation of hydraulic networks and progress made to date in multi-objective optimisation for a selected sub-system operated by Umgeni Water.

Keywords: energy usage, pump scheduling, WaterNet Advisor, leakages

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Authors: Antonia Harold-Barry, Eugene Dempsey

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Background: The objective is to examine the survival and outcome of infants born under 26 weeks gestation in an Irish tertiary maternity hospital from 2007-2016 and to describe the survival and neurodevelopmental outcomes of these extremely preterm infants. Method: The population is 132 infants born at 23, 24, and 25 weeks in Cork University Maternity Hospital from 2007 to 2016. Ethical approval was granted by the Cork Clinical Research Ethics Committee. Patient details were obtained from the Vermont Oxford and Badger Networks. Survival rates and Bayley scores were calculated to assess neurodevelopmental outcomes. Statistical analysis with SPSS included frequencies, distributions, and comparisons between data from 2007-2011 and 2012-2016. Results: Overall survival rate was 63%. Of the surviving babies, 61% had Bayley scores calculated. Survival stood at 39% for delivery at 23 weeks, 50% at 24 weeks, and 83% at 25 weeks. The 2012 to 2016 cohort has shown further increases in survival, with 50% of babies at 23 weeks, 58% at 24 weeks, and 89% at 25 weeks. Corresponding figures for 2007-2011 are 20%, 39%, and 75%. Gestational age and incidence of periventricular leukomalacia were statistically significant, with a p-value of 0.022. Gestational age and delivery room deaths had a p-value of 0.025, as did gestational age and birth weight. A comparison of the two cohorts (2007-2011 and 2012-2016) with the administration of antenatal steroids showed a statistically significant p-value of 0.044. Conclusion: There is less morbidity and mortality in infants born at 25 than at 23 or 24 weeks. Survival of extremely premature infants has increased significantly over the past ten years. Survival rates with normal neurodevelopmental outcomes are comparable with international standards and reflect positive changes in attitude and practices in neonatal intensive care. This study will inform parents about the potential outcomes of extreme prematurity and policy regarding the management of extreme prematurity.

Keywords: extreme of viability, neurodevelopmental outcome, periventricular leukomalacia, prematurity

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Authors: Mekonen Hailu, Gashaw Tesfaye, Adamneh Dagne, Hiwot Teshome

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Lake Hawassa is one of the most important lakes for Ethiopian fishery. It serves as a source of food and nutrition, income and livelihood for many inhabitants. However, the fishery in Lake Hawassa shows a declining trend, especially for the most valuable species, such as the Nile tilapia (Oreochromis niloticus L.), indicating that the existing management systems are either not fully enforced or inadequate. The aim of this study was therefore to develop management policy options for the sustainable utilization and management of fishery resources in Lake Hawassa. A blend of primary and secondary data was used for the study. Primary data were collected using Participatory Rural Appraisal (PRA) techniques such as focus group discussions with members of fishing co-operatives, co-operative leaders and key informant discussion to understand the current state of the fisheries resources. Then literatures were reviewed to obtain secondary data and develop alternative management policy options. It has been realized that Lake Hawassa is not very species-rich in terms of fish diversity. It contains only six species belonging to four families, of which only three are commercially important, including the Nile tilapia (90 % of catches), the African catfish Clarias gariepinus B. (7 % of catches) and the African large barb Labeobarbus intermedius R. (only 3 % of catches). The production has been declining since 2007. The top six challenges that could be responsible for this decline, identified by about two-thirds of respondents and supported by the literature review, are directly linked to fisheries and fisheries management, with overfishing, irregular monitoring, control, and surveillance (MCS) system and the lack of a fishing licensing system ranking first, second and third respectively. It is, therefore, important to address these and other problems identified in the study. Of the management options analyzed, we suggest adapting the management approach to sustain the fishery in Lake Hawaasa and its socio-economic benefits. We also present important conditions for successfully implementing co-management in this and other lakes in Ethiopia.

Keywords: comanagement, community-based management, fishery, overfishing, participatory approach, top-down management

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Authors: R. S. Komartin, B. Balanuca, R. Stan

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the last decades, studies about the use of polymeric materials of plant origin, considering environmental concerns, have captured the interest of researchers because these represent an alternative to petroleum-derived materials. Vegetable oils are one of the preferred alternatives for petroleum-based raw materials having long aliphatic chains similar to hydrocarbons which means that can be processed using conventional chemistry. Epoxidized vegetable oils (EVO) are among the most interesting products derived from oil both for their high reactivity (epoxy group) and for the potential to react with compounds from various classes. As in the case of epoxy resins starting from petrochemical raw materials, those obtained from EVO can be crosslinked with different agents to build polymeric networks and can also be reinforced with various additives to improve their thermal and mechanical performances. Among the multitude of known EVO, the most common in industrial practice are epoxidized linseed oils (ELO) and epoxidized soybean oils (ESO), the first with an iodine index over 180, the second having a lower iodine index but being cheaper. On the other hand, lignin (Ln) is the second natural organic material as a spread, whose use has long been hampered because of the high costs associated with its isolation and purification. In this context, our goal was to obtain new composite materials with satisfactory intermediate properties in terms of stiffness and elasticity using the characteristics of ELO and Ln and choosing the proper curing procedure. In the present study linseed oil (LO) epoxidation was performed using peracetic acid generated in situ. The obtained bio-based epoxy resin derived from linseed oil was used further to produce the new composites byloading Ln in various mass ratios. The resulted ELO-Ln blends were subjected to a dual-curing protocol, namely photochemical and thermal. The new ELO-Ln composites were investigated by FTIR spectrometry, thermal stability, water affinity, and morphology. The positive effect of lignin regarding the thermal stability of the composites could be proved. The results highlight again the still largely unexplored potential of lignin in industrial applications.

Keywords: composite materials, dual curing, epoxidized linseed oil, lignin

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Authors: Foteini Zagklavara, Peter Jimack, Nikil Kapur, Ozz Querin, Harvey Thompson

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The invention and development of the Polymerase Chain Reaction (PCR) technology have revolutionised molecular biology and molecular diagnostics. There is an urgent need to optimise their performance of those devices while reducing the total construction and operation costs. The present study proposes a CFD-enabled optimisation methodology for continuous flow (CF) PCR devices with serpentine-channel structure, which enables the trade-offs between competing objectives of DNA amplification efficiency and pressure drop to be explored. This is achieved by using a surrogate-enabled optimisation approach accounting for the geometrical features of a CF μPCR device by performing a series of simulations at a relatively small number of Design of Experiments (DoE) points, with the use of COMSOL Multiphysics 5.4. The values of the objectives are extracted from the CFD solutions, and response surfaces created using the polyharmonic splines and neural networks. After creating the respective response surfaces, genetic algorithm, and a multi-level coordinate search optimisation function are used to locate the optimum design parameters. Both optimisation methods produced similar results for both the neural network and the polyharmonic spline response surfaces. The results indicate that there is the possibility of improving the DNA efficiency by ∼2% in one PCR cycle when doubling the width of the microchannel to 400 μm while maintaining the height at the value of the original design (50μm). Moreover, the increase in the width of the serpentine microchannel is combined with a decrease in its total length in order to obtain the same residence times in all the simulations, resulting in a smaller total substrate volume (32.94% decrease). A multi-objective optimisation is also performed with the use of a Pareto Front plot. Such knowledge will enable designers to maximise the amount of DNA amplified or to minimise the time taken throughout thermal cycling in such devices.

Keywords: PCR, optimisation, microfluidics, COMSOL

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Authors: Sreto Boljevic

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In the absence of considerable investment in electricity generation, transmission and distribution network (DN) capacity, the demand for electrical energy will quickly strain the capacity of the existing electrical power network. With anticipated growth and proliferation of Electric vehicles (EVs) and Heat pump (HPs) identified the likelihood that the additional load from EV changing and the HPs operation will require capital investment in the DN. While an area-wide implementation of EVs and HPs will contribute to the decarbonization of the energy system, they represent new challenges for the existing low-voltage (LV) network. Distributed energy resources (DER), operating both as part of the DN and in the off-network mode, have been offered as a means to meet growing electricity demand while maintaining and ever-improving DN reliability, resiliency and power quality. DN planning has traditionally been done by forecasting future growth in demand and estimating peak load that the network should meet. However, new problems are arising. These problems are associated with a high degree of proliferation of EVs and HPs as load imposes on DN. In addition to that, the promotion of electricity generation from renewable energy sources (RES). High distributed generation (DG) penetration and a large increase in load proliferation at low-voltage DNs may have numerous impacts on DNs that create issues that include energy losses, voltage control, fault levels, reliability, resiliency and power quality. To mitigate negative impacts and at a same time enhance positive impacts regarding the new operational state of DN, CHP system integration can be seen as best action to postpone/reduce capital investment needed to facilitate promotion and maximize benefits of EVs, HPs and RES integration in low-voltage DN. The aim of this paper is to generate an algorithm by using an analytical approach. Algorithm implementation will provide a way for optimal placement of the CHP system in the DN in order to maximize the integration of RES and increase in proliferation of EVs and HPs.

Keywords: combined heat & power (CHP), distribution networks, EVs, HPs, RES

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Authors: Rana Tabassum, Ravi Kant, Banshi D. Gupta

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Malic acid is an extensively distributed organic acid in numerous horticultural products in minute amounts which significantly contributes towards taste determination by balancing sugar and acid fractions. An enhanced concentration of malic acid is utilized as an indicator of fruit maturity. In addition, malic acid is also a crucial constituent of several cosmetics and pharmaceutical products. An efficient detection and quantification protocol for malic acid is thus highly demanded. In this study, we report a novel detection scheme for malic acid by synergistically collaborating fiber optic surface plasmon resonance (FOSPR) and distinctive features of nanomaterials favorable for sensing applications. The design blueprint involves the deposition of an assembly of malate dehydrogenase enzyme entrapped in ZnO nanowires forming the sensing route over silver coated central unclad core region of an optical fiber. The formation and subsequent decomposition of the enzyme-analyte complex on exposure of the sensing layer to malic acid solutions of diverse concentration results in modification of the dielectric function of the sensing layer which is manifested in terms of shift in resonance wavelength. Optimization of experimental variables such as enzyme concentration entrapped in ZnO nanowires, dip time of probe for deposition of sensing layer and working pH range of the sensing probe have been accomplished through SPR measurements. The optimized sensing probe displays high sensitivity, broad working range and a minimum limit of detection value and has been successfully tested for malic acid determination in real samples of fruit juices. The current work presents a novel perspective towards malic acid determination as the unique and cooperative combination of FOSPR and nanomaterials provides myriad advantages such as enhanced sensitivity, specificity, compactness together with the possibility of online monitoring and remote sensing.

Keywords: surface plasmon resonance, optical fiber, sensor, malic acid

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Dounya Barrit, Ming-Chun Tang, Hoang Dang, Kai Wang, Detlef-M. Smilgies, Aram Amassian

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Several deposition methods have been developed for perovskite film preparation. The one-step spin-coating process has emerged as a more popular option thanks to its ability to produce films of different compositions, including mixed cation and mixed halide perovskites, which can stabilize the perovskite phase and produce phases with desired band gap. The two-step method, however, is not understood in great detail. There is a significant need and opportunity to adopt the two-step process toward mixed cation and mixed halide perovskites, but this requires deeper understanding of the two-step conversion process, for instance when using different cations and mixtures thereof, to produce high-quality perovskite films with uniform composition. In this work, we demonstrate using in situ investigations that the conversion of PbI₂ to perovskite is largely dictated by the state of the PbI₂ precursor film in terms of its solvated state. Using time-resolved grazing incidence wide-angle X-Ray scattering (GIWAXS) measurements during spin coating of PbI₂ from a DMF (Dimethylformamide) solution we show the film formation to be a sol-gel process involving three PbI₂-DMF solvate complexes: disordered precursor (P₀), ordered precursor (P₁, P₂) prior to PbI₂ formation at room temperature after 5 minutes. The ordered solvates are highly metastable and eventually disappear, but we show that performing conversion from P₀, P₁, P₂ or PbI₂ can lead to very different conversion behaviors and outcomes. We compare conversion behaviors by using MAI (Methylammonium iodide), FAI (Formamidinium Iodide) and mixtures of these cations, and show that conversion can occur spontaneously and quite rapidly at room temperature without requiring further thermal annealing. We confirm this by demonstrating improvements in the morphology and microstructure of the resulting perovskite films, using techniques such as in situ quartz crystal microbalance with dissipation monitoring, SEM and XRD.

Keywords: in situ GIWAXS, lead iodide, mixed cation, perovskite solar cell, sol-gel process, solvate phase

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Authors: Torben Hansen

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While trust has long been regarded as one of the most critical variables for developing and maintaining well-functioning financial customer-seller relationships it can be suggested that trust not only relates to customer trust in individual companies (narrow-scope trust). Trust also relates to the broader business context in which consumers may carry out their financial behaviour (broad-scope trust). However, despite the well-recognized significance of trust in marketing research, only few studies have investigated the role of broad-scope trust in consumer financial behaviour. Moreover, as one of its many serious outcomes, the global financial crisis has elevated the need for an improved understanding of the role of broad-scope trust in consumer financial services markets. Only a minority of US and European consumers are currently confident in financial companies and ‘financial stability’ and ‘trust’ are now among the top reasons for choosing a bank. This research seeks to address this shortcoming in the marketing literature by investigating direct and moderating effects of broad-scope trust on consumer financial behaviour. Specifically, we take an ability-effort approach to consumer financial behaviour. The ability-effort approach holds the basic premise that the quality of consumer actions is influenced by ability factors, for example consumer knowledge and cognitive effort. Our study is based on two surveys. Survey 1 comprises 1,155 bank consumers, whereas survey 2 comprises 764 pension consumers. The results indicate that broad-scope trust negatively moderates relationships between knowledge and financial healthiness and between cognitive effort and financial healthiness. In addition, it is demonstrated that broad-scope trust negatively influences cognitive effort. Specifically, the results suggest that broad-scope trust contributes to the financial well-being of consumers with limited financial knowledge and processing capabilities. Since financial companies are dependent on customers to pay their loans and bills they have a greater interest in developing relations with consumers with a healthy financial behaviour than with the opposite. Hence, financial managers should be engaged with monitoring and influencing broad-scope trust. To conclude, by taking into account the contextual effect of broad-scope trust, the present study adds to our understanding of knowledge-effort-behaviour relationship in consumer financial markets.

Keywords: cognitive effort, customer-seller relationships, financial healthiness, knowledge, trust

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Authors: Chiling Chen, Chiaoying Chou, Siyang Wu

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Taiwan locates at the west of Pacific Ocean and intersects between continental and marine climate. Typhoons frequently strike Taiwan and come with meteorological disasters, i.e., heavy flooding, landslides, loss of life and properties, etc. Global climate change brings more extremely meteorological disasters. So, develop techniques to improve disaster prevention and mitigation is needed, to improve rescue processes and rehabilitations is important as well. In this study, UAVs (Unmanned Aerial Vehicles) are applied to take instant images for improving the disaster investigation and rescue processes. Paddy rice fields in the central Taiwan are the study area. There have been attacked by heavy rain during the monsoon season in June 2016. UAV images provide the high ground resolution (3.5cm) with 3D Point Clouds to develop image discrimination techniques and digital surface model (DSM) on rice lodging. Firstly, image supervised classification with Maximum Likelihood Method (MLD) is used to delineate the area of rice lodging. Secondly, 3D point clouds generated by Pix4D Mapper are used to develop DSM for classifying the lodging levels of paddy rice. As results, discriminate accuracy of rice lodging is 85% by image supervised classification, and the classification accuracy of lodging level is 87% by DSM. Therefore, UAVs not only provide instant images of agricultural damage after the meteorological disaster, but the image discriminations on rice lodging also reach acceptable accuracy (>85%). In the future, technologies of UAVs and image discrimination will be applied to different crop fields. The results of image discrimination will be overlapped with administrative boundaries of paddy rice, to establish GIS-based assist system on agricultural damage discrimination. Therefore, the time and labor would be greatly reduced on damage detection and monitoring.

Keywords: Monsoon, supervised classification, Pix4D, 3D point clouds, discriminate accuracy

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Authors: Kyoungwoon Kim, Cuong Huynh, Cam Nguyen

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Exploding demands for more data, faster data transmission speed, less interference, more users, more wireless devices, and better reliable service-far exceeding those provided in the current mobile communications networks in the RF spectrum below 6 GHz-has led the wireless communication industry to focus on higher, previously unallocated spectrums. High frequencies in RF spectrum near (around 28 GHz) or within the millimeter-wave regime is the logical solution to meet these demands. This high-frequency RF spectrum is of increasingly important for wireless communications due to its large available bandwidths that facilitate various applications requiring large-data high-speed transmissions, reaching up to multi-gigabit per second, of vast information. It also resolves the traffic congestion problems of signals from many wireless devices operating in the current RF spectrum (below 6 GHz), hence handling more traffic. Consequently, the wireless communication industries are moving towards 5G (fifth generation) for next-generation communications such as mobile phones, autonomous vehicles, virtual reality, and the Internet of Things (IoT). The U.S. Federal Communications Commission (FCC) proved on 14th July 2016 three frequency bands for 5G around 28, 37 and 39 GHz. We present some silicon-based RFIC power amplifiers (PA) for possible implementation for 5G wireless communications around 28, 37 and 39 GHz. The 16.5-28 GHz PA exhibits measured gain of more than 34.5 dB and very flat output power of 19.4±1.2 dBm across 16.5-28 GHz. The 25.5/37-GHz PA exhibits gain of 21.4 and 17 dB, and maximum output power of 16 and 13 dBm at 25.5 and 37 GHz, respectively, in the single-band mode. In the dual-band mode, the maximum output power is 13 and 9.5 dBm at 25.5 and 37 GHz, respectively. The 10-19/23-29/33-40 GHz PA has maximum output powers of 15, 13.3, and 13.8 dBm at 15, 25, and 35 GHz, respectively, in the single-band mode. When this PA is operated in dual-band mode, it has maximum output powers of 11.4/8.2 dBm at 15/25 GHz, 13.3/3 dBm at 15/35 GHz, and 8.7/6.7 dBm at 25/35 GHz. In the tri-band mode, it exhibits 8.8/5.4/3.8 dBm maximum output power at 15/25/35 GHz. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors

Keywords: Microwaves, Millimeter waves, Power Amplifier, Wireless communications

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Sonya Barzgar, J. Patrick, A. Hettiaratchi

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Methane (CH4) is reputed as the second largest contributor to greenhouse effect with a global warming potential (GWP) of 34 related to carbon dioxide (CO2) over the 100-year horizon, so there is a growing interest in reducing the emissions of this gas. Methane biofiltration (MBF) is a cost effective technology for reducing low volume point source emissions of methane. In this technique, microbial oxidation of methane is carried out by methane-oxidizing bacteria (methanotrophs) which use methane as carbon and energy source. MBF uses a granular medium, such as soil or compost, to support the growth of methanotrophic bacteria responsible for converting methane to carbon dioxide (CO₂) and water (H₂O). Even though the biofiltration technique has been shown to be an efficient, practical and viable technology, the design and operational parameters, as well as the relevant microbial processes have not been investigated in depth. In particular, limited research has been done on the effects of sulphur on methane bio-oxidation. Since bacteria require a variety of nutrients for growth, to improve the performance of methane biofiltration, it is important to establish the input quantities of nutrients to be provided to the biofilter to ensure that nutrients are available to sustain the process. The study described in this paper was conducted with the aim of determining the influence of sulphur on methane elimination in a biofilter. In this study, a set of experimental measurements has been carried out to explore how the conversion of elemental sulphur could affect methane oxidation in terms of methanotrophs growth and system pH. Batch experiments with different concentrations of sulphur were performed while keeping the other parameters i.e. moisture content, methane concentration, oxygen level and also compost at their optimum level. The study revealed the tolerable limit of sulphur without any interference to the methane oxidation as well as the particular sulphur concentration leading to the greatest methane elimination capacity. Due to the sulphur oxidation, pH varies in a transient way which affects the microbial growth behavior. All methanotrophs are incapable of growth at pH values below 5.0 and thus apparently are unable to oxidize methane. Herein, the certain pH for the optimal growth of methanotrophic bacteria is obtained. Finally, monitoring methane concentration over time in the presence of sulphur is also presented for laboratory scale biofilters.

Keywords: global warming, methane biofiltration (MBF), methane oxidation, methanotrophs, pH, sulphur

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Authors: Seong Gu Hwang, Young Kyoon Oh, Joseph F. dela Cruz

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Marbling, or intramuscular fat, has been consistently identified as one of the top beef quality problems. Intramuscular adipocytes distribute throughout the perimysial connective tissue of skeletal muscle and are the major site for the deposition of intramuscular fat, which is essential for the eating quality of meat. The stromal vascular fraction of the skeletal muscle contains progenitor cells that can be enhanced to differentiate to adipocytes and increase intramuscular fat. Primary cultures of bovine intramuscular stromal vascular cells were used in this study to elucidate the effects of extracellular calcium and retinoic acid concentration on adipocyte differentiation. Cell viability assay revealed that even at different concentrations of calcium and retinoic acid, there was no significant difference on cell viability. Monitoring of the adipocyte differentiation showed that bovine intramuscular stromal vascular cells cultured in a low concentration of extracellular calcium and retinoic acid had a better degree of fat accumulation. The mRNA and protein expressions of PPARγ, C/EBPα, SREBP-1c and aP2 were analyzed and showed a significant upregulation upon the reduction in the level of extracellular calcium and retinoic acid. The upregulation of these adipogenic related genes means that the decreasing concentration of calcium and retinoic acid is able to stimulate the adipogenic differentiation of bovine intramuscular stromal vascular cells. To further elucidate the effect of calcium, the expression level of calreticulin was measured. Calreticulin which is known to be an inhibitor of PPARγ was down regulated by the decreased level of calcium and retinoic acid in the culture media. The same tendency was observed on retinoic acid receptors RARα and CRABP-II. These receptors are recognized as adipogenic inhibitors, and the downregulation of their expression allowed a better level of differentiation in bovine intramuscular stromal vascular cells. In conclusion, data show that decreasing the level of extracellular calcium and retinoic acid can significantly promote adipogenesis in intramuscular stromal vascular cells of Hanwoo beef cattle. These findings may provide new insights in enhancing intramuscular adipogenesis and marbling in beef cattle.

Keywords: calcium, calreticulin, hanwoo beef, retinoic acid

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Authors: Melake Kuflom

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European power networks involve the use of multiple overhead transmission lines to construct a highly duplicated system that delivers reliable and stable electrical energy to the distribution level. The transmission line protection applied in the existing GB transmission network are normally independent unit differential and time stepped distance protection schemes, referred to as main-1 & main-2 respectively, with overcurrent protection as a backup. The increasing penetration of renewable energy sources, commonly referred as “weak sources,” into the power network resulted in the decline of fault level. Traditionally, the fault level of the GB transmission network has been strong; hence the fault current contribution is more than sufficient to ensure the correct operation of the protection schemes. However, numerous conventional coal and nuclear generators have been or about to shut down due to the societal requirement for CO2 emission reduction, and this has resulted in a reduction in the fault level on some transmission lines, and therefore an adaptive transmission line protection is required. Generally, greater utilization of renewable energy sources generated from wind or direct solar energy results in a reduction of CO2 carbon emission and can increase the system security and reliability but reduces the fault level, which has an adverse effect on protection. Consequently, the effectiveness of conventional protection schemes under low fault levels needs to be reviewed, particularly for future GB transmission network operating scenarios. The proposed paper will evaluate the transmission line challenges under high penetration of renewable energy sources andprovides alternative viable protection solutions based on the problem observed. The paper will consider the assessment ofrenewable energy sources (RES) based on a fully rated converter technology. The DIgSILENT Power Factory software tool will be used to model the network.

Keywords: fault level, protection schemes, relay settings, relay coordination, renewable energy sources

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Authors: Mohd Zaki Hamzah, Roslan Rani, Ahmad Bazli Razali, Satiful Bahri Mamat, Abdul Hadi Ripin, Mohd Harun Esa

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Ever since 1901, forest management and silviculture practices in Malaysia have been frequently reviewed and updated to take into account changes in forest conditions, markets, timber demand/supply and technical advances that can be achieved in industrial processes, logging and forest harvesting, and currently, the forest management system practiced in Peninsular Malaysia is the Selective Management System (SMS) which was introduced in 1978. This system requires the selection of management regime (felling) based on Pre-Felling Forest Inventory (Pre-F) data to ensure economical harvesting and also ensuring adequate standing stands for subsequent rounds of felling, while maintaining ecological balance and environmental quality. SMS regulates forest harvesting through area and volume controls, with the cutting cycle 30 years. Most of the forest management units (FMU) (in Peninsular Malaysia) implementing SMS have been certified by Forest Stewardship Council (FSC) and/or Program for Endorsement of Forest Certification (PEFC), and one such FMU belongs to Kumpulan Pengurusan Kayu Kayan Terengganu (KPKKT). KPKKT, a timber management subsidiary of Golden Pharos Berhad (GPB), adopts the SMS to manage its 108,900 ha of timber concessionary areas in its role as logs’ supplier for the consumption of three subsidiaries of GPB. KPKKT is also responsible for the sustainable development and management of its concession in accordance with the Sustainable Forest Management (SFM) standards to ensure that it addresses the loss of forest cover and forest degradation, forest-based economic, social and environmental benefits, and ecologically protecting forests while mobilising financial resources for the implementation of sustainable forest management planning, harvesting, monitoring and the marketing of products. This paper will detail out the management and harvesting guidelines imposed by the controlling government agency, and harvesting processes taken by KPKKT to comply with guidelines and eventually supplying timber to the relevant subsidiaries (downstream mills under GPB).

Keywords: sustainable forest management, silviculture, reduce impact logging, forest certification

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Authors: Arif Budiman

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Any organization or company that wishes to achieve vision, mission, and goals of the organization is required to implement a performance management system or known as the Performance Management System (PMS) in every part of the whole organization. PMS is a tool to help visualize the direction and work program of the organization to achieve the goal. The challenge is PMS should not stop merely as a visualization tool to achieve the vision and mission of the organization, but PMS should also be able to create a high-performance culture that is inherent in each individual of the organization. Establishment of a culture within an organization requires the support of top leaders and also requires a system or governance that encourages every individual in the organization to be involved in any work program of the organization. Keywords of creating a high-performance culture are the formation of communication pattern involving the whole individual, either vertically or horizontally, and performed consistently and persistently by all individuals in each line of the organization. PT Pertamina (Persero) as the state-owned national energy company holds a system to internalize the culture of high performance through a system called Performance Management System Cycle (PMS Cycle). This system has 7 stages of the cycle, those are: (1) defining vision, mission and strategic plan of the company, (2) defining key performance indicator of each line and the individual (‘expectation setting conversation’), (3) defining performance target and performance agreement, (4) monitoring performance on a monthly regular basis (‘pulse check’), (5) implementing performance dialogue between leaders and staffs periodically every 3 months (‘performance dialogue’), (6) defining rewards and consequences based on the achievement of the performance of each line and the individual, and (7) calculating the final performance value achieved by each line and individual from one period of the current year. Perform PMS is a continual communication running throughout the year, that is why any three performance discussion that should be performed, include expectation setting conversations, pulse check and performance dialogue. In addition, another significant point and necessary undertaken to complete the assessment of individual performance assessment is soft competencies through 360-degree assessment by leaders, staffs, and peers.

Keywords: 360-degree assessment, expectation setting conversation, performance management system cycle, performance dialogue, pulse check

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Authors: Suneet Jagdev, Siddharth Singhal, Dhrubajyoti Bordoloi, Peesari Vamshidhar Reddy

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There is no universally accepted definition of what constitutes a Smart City. It means different things to different people. The definition varies from place to place depending on the level of development and the willingness of people to change and reform. It tries to improve the quality of resource management and service provisions for the people living in the cities. Smart city is an urban development vision to integrate multiple information and communication technology (ICT) solutions in a secure fashion to manage the assets of a city. But most of these projects are misinterpreted as being technology projects only. Due to urbanization, a lot of informal as well government funded settlements have come up during the last few decades, thus increasing the consumption of the limited resources available. The people of each city have their own definition of Smart City. In the imagination of any city dweller in India is the picture of a Smart City which contains a wish list of infrastructure and services that describe his or her level of aspiration. The research involved a comparative study of the Smart City models in India and in China. Behavioral changes experienced by the people living in the pilot/first ever smart cities have been identified and compared. This paper discussed what is the target of the quality of life for the people in India and in China and how well could that be realized with the facilities being included in these Smart City projects. Logical and comparative analyses of important data have been done, collected from government sources, government papers and research papers by various experts on the topic. Existing cities with historically grown infrastructure and administration systems will require a more moderate step-by-step approach to modernization. The models were compared using many different motivators and the data is collected from past journals, interacting with the people involved, videos and past submissions. In conclusion, we have identified how these projects could be combined with the ongoing small scale initiatives by the local people/ small group of individuals and what might be the outcome if these existing practices were implemented on a bigger scale.

Keywords: behavior change, mission monitoring, pilot smart cities, social capital

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Daria Karasalihovic Sedlar, Lucija Jukic, Ivan Smajla, Marija Macenic

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This paper analyses possible geothermal energy production from a mature oil reservoir based on exploitation of underlying aquifer thermal energy for the purpose of heating public buildings. Research was conducted based on the case study of the City of Ivanic-Grad public buildings energy demand and Ivanic oil filed that is situated in the same area. Since the City of Ivanic is one of the few cities in the EU where hydrocarbon exploitation has been taking place for decades almost entirely in urban area, decommissioning of oil wells is inevitable; therefore, the research goal was to investigate how to extend the life-time of the reservoir by exploiting geothermal brine beneath the oil reservoir in an environmental friendly manner. This kind of a project is extremely complex in all segments, from documentation preparation, implementation of technological solutions, and providing ecological measures for environmentally acceptable geothermal energy production and utilization. New mining activities that will be needed for the development of geothermal project at the observed Hydrocarbon Exploitation Field Ivanic will be carried out in order to prepare wells for increasing geothermal brine production. These operations involve the conversion of existing wells (well completion for conversion of the observation wells to production ones) along with workover activities, installation of new heat exchangers, and pipelines. Since the wells are in the urban area of the City of Ivanic-Grad in high density populated area, the inhabitants will be exposed to the different environmental impacts during preparation phase of the project. For the purpose of performing workovers, it will be necessary to secure access to wellheads of existing wells. This paper gives guidelines for describing potential impacts on environment components that could occur during geothermal production preparation on existing mature oil filed, recommends possible protection measures to mitigate these impacts, and gives recommendations for environmental monitoring.

Keywords: geothermal energy production, mature oil filed, environmental impact assessment, underlying aquifer thermal energy

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Authors: Nardjes Hamini, Mohamed Bachir Yagoubi

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Precision agriculture has revolutionized farming by enabling farmers to monitor their crops remotely in real-time. By utilizing technologies such as sensors, farmers can detect the state of growth, hydration levels, and nutritional status and even identify diseases affecting their crops. With this information, farmers can make informed decisions regarding irrigation, fertilization, and pesticide application. Automated agricultural tasks, such as plowing, seeding, planting, and harvesting, are carried out by autonomous robots and have helped reduce costs and increase production. Despite the advantages of precision agriculture, its high cost makes it inaccessible to small and medium-sized farms. To address this issue, this paper presents an open-source guidance system for an autonomous planter robot. The system is composed of a Raspberry Pi-type nanocomputer equipped with Wi-Fi, a GPS module, a gyroscope, and a power supply module. The accompanying application allows users to enter and calibrate maps with at least four coordinates, enabling the localized contour of the parcel to be captured. The application comprises several modules, such as the mission entry module, which traces the planting trajectory and points, and the action plan entry module, which creates an ordered list of pre-established tasks such as loading, following the plan, returning to the garage, and entering sleep mode. A remote control module enables users to control the robot manually, visualize its location on the map, and use a real-time camera. Wi-Fi coverage is provided by an outdoor access point, covering a 2km circle. This open-source system offers a low-cost alternative for small and medium-sized farms, enabling them to benefit from the advantages of precision agriculture.

Keywords: autonomous robot, guidance system, low-cost, medium farms, open-source system, planter robot, precision agriculture, real-time monitoring, remote control, small farms

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Authors: Beloulou Mohamed Lamine, Fedili Benamar, Meliani Walid, Chaid Dalila

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Introduction: The risk factors for the chronicization of postoperative pain are numerous and often intricately intertwined. Among these, the severity of acute postoperative pain is currently recognized as one of the most determining factors. Mastectomy and thoracotomy are described as among the most painful surgeries and the most likely to lead to chronic post-surgical pain (CPSP). Objective: To examine the aspects of acute postoperative pain potentially involved in the development of chronic pain following breast and thoracic surgery. Patients and Methods: A prospective study involving 164 patients was conducted over a six-month period. Postoperative pain (during mobilization) was assessed using a Visual Analog Scale (VAS) at various time points after surgery: Day 0, 1st, 2nd, 5th days, 1st and 6th months. Moderate to severe pain was defined as a VAS score ≥ 4. A comparative analysis (univariate analysis) of postoperative pain intensities at different evaluation phases was performed on patients with and without CPSP to identify potential associations with the risk of chronicization six months after surgery. Results: At the 6th month post-surgery, the incidence of CPSP was 43.0%. Moderate to severe acute postoperative pain (in the first five days) was observed in 64% of patients. The highest pain scores were reported among thoracic surgery patients. Comparative measures revealed a highly significant association between the presence of moderate to severe acute pain, especially lasting for ≥ 48 hours, and the occurrence of CPSP (p-value <0.0001). Likewise, the persistence of subacute pain (up to 4 to 6 weeks after surgery), especially of moderate to severe intensity, was significantly associated with the risk of chronicization at six months (p-value <0.0001). Conclusion: CPSP after breast and thoracic surgery remains a fairly common morbidity that profoundly affects the quality of life. Severe acute postoperative pain, especially if it is prolonged and/or with a slow decline in intensity, can be an important predictive factor for the risk of chronicization. Therefore, more effective and intensive management of acute postoperative pain, as well as longitudinal monitoring of its trajectory over time, should be an essential component of strategies for preventing chronic pain after surgery.

Keywords: chronic post-surgical pain, acute postoperative pain, breast and thoracic surgery, subacute postoperative pain, pain trajectory, predictive factor

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