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Authors: Lina Wu, Ye Li, Jia Liu

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We are interested in solving Liouville-type problems to explore constancy properties for maps or differential forms on Riemannian manifolds. Geometric structures on manifolds, the existence of constancy properties for maps or differential forms, and energy growth for maps or differential forms are intertwined. In this article, we concentrate on discovery of solutions to Liouville-type problems where manifolds are Euclidean spaces (i.e. flat Riemannian manifolds) and maps become real-valued functions. Liouville-type results of vanishing properties for functions are obtained. The original work in our research findings is to extend the q-energy for a function from finite in L^q space to infinite in non-L^q space by applying p-balanced technique where q = p = 2. Calculation skills such as Hölder's Inequality and Tests for Series have been used to evaluate limits and integrations for function energy. Calculation ideas and computational techniques for solving Liouville-type problems shown in this article, which are utilized in Euclidean spaces, can be universalized as a successful algorithm, which works for both maps and differential forms on Riemannian manifolds. This innovative algorithm has a far-reaching impact on research work of solving Liouville-type problems in the general settings involved with infinite energy. The p-balanced technique in this algorithm provides a clue to success on the road of q-energy extension from finite to infinite.

Keywords: Differential Forms, Hölder Inequality, Liouville-type problems, p-balanced growth, p-harmonic maps, q-energy growth, tests for series.

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Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: Agricultural robot, autonomous control, path-tracking control, tracked mobile robot.

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Authors: Gesine Hellwig

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Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

Keywords: Functional imaging, Tracer kinetic modeling, LTIsystem, Indicator dilution theory / convolution approach, Two-Compartment model.

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Authors: Samad Lotfollahzadeh

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Escherichia coli (E. coli) is the most isolated bacteria from blood circulation of septicemic calves. Given the prevalence of septicemia in animals and its economic importance in veterinary practice, better understanding of changes in clinical signs following disease, may contribute to early detection of disorder. The present study has been carried out to detect changes of clinical signs in induced sepsis in calves with E. coli. Colisepticemia has been induced in 10 twenty-day old healthy Holstein- Frisian calves with intravenous injection of 1.5 X 109 colony forming units (cfu) of O111:H8 strain of E. coli. Clinical signs including rectal temperature, heart rate, respiratory rate, shock, appetite, sucking reflex, feces consistency, general behavior, dehydration and standing ability were recorded in experimental calves during 24 hours after induction of colisepticemia. Blood culture was also carried out from calves four times during experiment. ANOVA with repeated measure is used to see changes of calves’ clinical signs to experimental colisepticemia, and values of P≤ 0.05 was considered statistically significant. Mean values of rectal temperature and heart rate as well as median values of respiratory rate, appetite, suckling reflex, standing ability and feces consistency of experimental calves increased significantly during study (P<0.05). In the present study median value of shock score was not significantly increased in experimental calves (P> 0.05). The results of present study showed that total score of clinical signs in calves with experimental colisepticemia increased significantly, although score of some clinical signs such as shock did not change significantly.

Keywords: Calves, Clinical signs scoring, E. coli O111:H8, Experimental colisepticemia,

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Authors: Anjan Kumar Kakati, M. Chandrasekaran, Amitava Mandal, Amit Kumar Singh

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End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.

Keywords: End milling, Surface roughness, Neural networks.

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Authors: Aseel Hatif Jassam, Hadeel Hatif Jassam

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The paper discusses the phallocentric discourse that is challenged by women in general and women of color in particular in spite of the simultaneity of oppression due to race, class, and gender in the diaspora. Therefore, the paper gives a brief account of women's experience in the light of postcolonial feminist theory. The paper also casts light on the theories of Luce Irigaray and Helen Cixous, two feminist theorists who support and advise women to have their own discourse to challenge the infectious patriarchal sentence advocated by Sigmund Freud and Harold Bloom's model of literary history. Black women authors like Buchi Emecheta as well as her alter ego Adah, a Nigerian-born girl and the protagonist of her semi-autobiographical novel, Second Class Citizen, suffer from this phallocentric and oppressive sentence and displacement as they migrate from Nigeria, a former British colony where they feel marginalized, to North London with the hope of realizing their dreams. Yet in the British diaspora, they get culturally shocked and continue to suffer from further marginalization due to class and race and are insulted and inferiorized ironically by their patriarchal husbands who try to put an end to their dreams of authorship. With the phallocentric belief that women are not capable of self-representation in the background of their mindsets, the violent Sylvester Onwordi and Francis Obi, the husbands of both Emecheta and Adah respectively have practiced oppression on them by burning their own authoritative voices, represented by the novels they write while they are struggling with their economically atrocious living experiences in the British diaspora.

Keywords: Authorship, British diaspora, discourse, phallocentric, patriarchy.

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Authors: Beatriz dos Anjos Furtado, Marina Barreiros Lamim, Camila Avozani Zago, Julianne Alvim Milward-de-Azevedo, Luís Cláudio Meirelles de Medeiros

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The intense process of economic acceleration, expansion of industrial activities and capitalism, combined with population growth, while promoting the development, bring environmental consequences and dynamics of locations. It can be seen that society is seeking to break with old paradigms of capitalist society, seeking to reconcile growth with sustainable development, with a change of mentality of the stakeholders of the production process (shareholders, employees, suppliers, customers, governments, and neighbors, groups citizens and the public in general). In this context, this research aims to map the stakeholders interested in environmental management in industries located in the city of Três Rios/RJ. The city of Três Rios is located in South-Central region of the state of Rio de Janeiro - Brazil. Methodological resources used refer to descriptive and field research, whose nature is qualitative and quantitative. It is also of multicases studies in the study area, and the data collection occurred by means of semi-structured questionnaires and interviews with employees related to the environmental area of the industries located in Três Rios and registered at the Federation of Industries the State of Rio de Janeiro - FIRJAN in the version of 2013 and active in federal revenue. Through this research it observed, among other things, the stakeholders involved in the environmental management process of “Três Rios” industry respondents, and those responding to the demands of environmental management.

Keywords: Environmental management, environmental practices, industry, stakeholders.

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Authors: Mohammed Sani Abdulai

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Government budgets are the primary instruments for formulating and implementing a country’s fiscal policy objectives, development priorities, and the overall socio-economic aspirations of its people. Thus, in this paper, the author examined the Government of Ghana’s budgets with respect to their functions, coverage, classifications, and integration with the country’s chart of accounts. The author did so by amalgamating the research findings of extant literature with (a) the operational and procedural guidelines underpinning the formulation and execution of the government’s budgets; (b) the recommendations made by various development partners and thinktanks on reforming the country’s budgeting processes and procedures; and (c) the lessons Ghana could learn from the budget reform efforts of other countries. By way of research findings, the paper showed that the Government of Ghana’s budgets in terms of function are both eclectic and multidimensional. On coverage, the paper showed that the country’s budgets duly cover the revenues and expenditures of the general government (i.e., both the central and sub-national governments). Finally, on classifications, the paper noted with delight the Government of Ghana’s effort in providing classificatory codes to both its national development agenda and such international development goals as the AU’s Agenda 2063 and the UN’s Sustainable Development Goals. However, the paper found some significant lapses that require a complete overhaul and structuring on the integrations of its budget classifications with its chart of accounts. Thus, the paper concluded with a detailed examination of the challenges confronting the country’s current chart of accounts and recommendations for addressing them.

Keywords: Budget, budgetary transactions, budgetary governance, Chart of Accounts, classification, composition, coverage, Public Financial Management.

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Authors: Seyedfateh Moradi, Abas Ali Rahbar

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The present study focuses on investigating group psychoanalysis in the Middle East. The study uses a descriptive-analytic method and library resources have been used to collect the data. Additionally, the researcher’s observations of people’s everyday behavior have played an important role in the production and analysis of the study. Group psychoanalysis in the Middle East can be conducted through people’s daily behaviors, proverbs, poetry, mythology, etc., and some of the general characteristics of people in the Middle East include: xenophobia, revivalism, fatalism, nostalgic, wills and so on. Members of the group have often failed to achieve Libido wills and it is very important in unifying and reproduction violence. Therefore, if libidinal wills are irrationally fixed, it will be important in forming fundamentalist and racist groups, a situation that is dominant among many groups in the Middle East. Adversities, from early childhood and afterwards, in the subjects have always been influential in the political behavior of group members, and it manifests itself as counter-projections. Consequently, it affects the foreign policy of the governments. On the other hand, two kinds of subjects are identifiable in the Middle East, one; classical subject that is related to nostalgia and mythology and, two; modern subjects which is self-alienated. As a result, both subjects are seeking identity and self-expression in public in relation to forming groups. Therefore, collective unconscious in the Middle East shows itself as extreme boundaries and leads to forming groups characterized with violence. Psychoanalysis shows important aspects to identify many developments in the Middle East; totally analysis of Freud, Carl Jung and Reich about groups can be applied in the present Middle East.

Keywords: Politics, political psychoanalysis, group, Middle East.

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Authors: Hock Chuan, Lim

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This paper presents an approach for identifying interactive effects using Network Science (NS) supported by Social Network Analysis (SNA) techniques. Based on general observations that learning processes and behaviors are shaped by the social relationships and influenced by learning environment, the central idea was to understand both the human and non-human interactive effects for a blended learning mode of delivery of computer science modules. Important findings include (a) the importance of non-human nodes to influence the centrality and transfer; (b) the degree of non-human and human connectivity impacts learning. This project reveals that the NS pattern and connectivity as measured by node relationships offer alternative approach for hypothesis generation and design of qualitative data collection. An iterative process further reinforces the analysis, whereas the experimental simulation option itself is an interesting alternative option, a hybrid combination of both experimental simulation and qualitative data collection presents itself as a promising and viable means to study complex scenario such as blended learning delivery mode. The primary value of this paper lies in the design of the approach for studying interactive effects of human (social nodes) and non-human (learning/study environment, Information and Communication Technologies (ICT) infrastructures nodes) components. In conclusion, this project adds to the understanding and the use of SNA to model and study interactive effects in blended social learning.

Keywords: Blended learning, network science, social learning, social network analysis, study environment.

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Authors: Andressa S. T. Gomes, Luiza A. Souza, Luciana H. Yamane, Renato R. Siman

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The segregation of waste of electrical and electronic equipment (WEEE) in the generating source, its characterization (quali-quantitative) and identification of origin, besides being integral parts of classification reports, are crucial steps to the success of its integrated management. The aim of this paper was to count WEEE generation at the Federal University of Espírito Santo (UFES), Brazil, as well as to define sources, temporary storage sites, main transportations routes and destinations, the most generated WEEE and its recycling potential. Quantification of WEEE generated at the University in the years between 2010 and 2015 was performed using data analysis provided by UFES’s sector of assets management. EEE and WEEE flow in the campuses information were obtained through questionnaires applied to the University workers. It was recorded 6028 WEEEs units of data processing equipment disposed by the university between 2010 and 2015. Among these waste, the most generated were CRT screens, desktops, keyboards and printers. Furthermore, it was observed that these WEEEs are temporarily stored in inappropriate places at the University campuses. In general, these WEEE units are donated to NGOs of the city, or sold through auctions (2010 and 2013). As for recycling potential, from the primary processing and further sale of printed circuit boards (PCB) from the computers, the amount collected could reach U$ 27,839.23. The results highlight the importance of a WEEE management policy at the University.

Keywords: Solid waste, waste of electric and electronic equipment, waste management, institutional generation of solid waste.

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Authors: Vladyslav Povoroznyuk, Larysa Martynyuk, Iryna Syzonenko, Liliya Martynyuk

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Osteoporosis is one of the important problems in postmenopausal women due to an increased risk of sudden and unexpected fractures. This study is aimed to determine the connection between bone mineral density (BMD) and trabecular bone score (TBS) in Ukrainian women suffering from metabolic syndrome. Participating in the study, 566 menopausal women aged 50-79 year-old were examined and divided into two groups: Group A included 336 women with no obesity (BMI ≤ 29.9 kg/m²), and Group B – 230 women with metabolic syndrome (diagnosis according to IDF criteria, 2005). Dual-energy X-ray absorptiometry was used for measuring of lumbar spine (L1-L4), femoral neck, total body and forearm BMD and bone quality indexes (last according to Med-Imaps installation). Data were analyzed using Statistical Package 6.0. A significant increase of lumbar spine (L1-L4), femoral neck, total body and ultradistal radius BMD was found in women with metabolic syndrome compared to those without obesity (p < 0.001) both in their totality and in groups of 50-59 years, 60-69 years, and 70-79 years. TBS was significantly higher in non-obese women compared to metabolic syndrome patients of 50-59 years and in the general sample (p < 0.05). Analysis showed significant positive correlation between body mass index (BMI) and BMD at all levels. Significant negative correlation between BMI and TBS (L1-L4) was established. Despite the fact that BMD indexes were significantly higher in women with metabolic syndrome, the frequency of vertebral and non-vertebral fractures did not differ significantly in the groups of patients.

Keywords: Bone mineral density, trabecular bone score, metabolic syndrome, fracture.

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Authors: Sarunyoo Songkro, Naranut Rajatasereekul, Nipapat Cheewasrirungrueng

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The aim of the present study was to evaluate the mucoadhesion and the release of nicotinamide gel formulations using in vitro methods. An agar plate technique was used to investigate the adhesiveness of the gels whereas a diffusion apparatus was employed to determine the release of nicotinamide from the gels. In this respect, 10% w/w nicotinamide gels containing bioadhesive polymers: Carbopol 934P (0.5-2% w/w), hydroxypropylmethyl cellulose (HPMC) (4-10% w/w), sodium carboxymethyl cellulose (SCMC) (4-6% w/w) and methylcellulose 4000 (MC) (3-5% w/w) were prepared. The gel formulations had pH values in the range of 7.14 - 8.17, which were considered appropriate to oral mucosa application. In general, the rank order of pH values appeared to be SCMC > MC4000 > HPMC > Carbopol 934P. Types and concentrations of polymers used somewhat affected the adhesiveness. It was found that anionic polymers (Carbopol 934 and SCMC) adhered more firmly to the agar plate than the neutral polymers (HPMC and MC 4000). The formulation containing 0.5% Carbopol 934P (F1) showed the highest release rate. With the exception of the formulation F1, the neutral polymers tended to give higher relate rates than the anionic polymers. For oral tissue treatment, the optimum has to be balanced between the residence time (adhesiveness) of the formulations and the release rate of the drug. The formulations containing the anionic polymers: Carbopol 934P or SCMC possessed suitable physical properties (appearance, pH and viscosity). In addition, for anionic polymer formulations, justifiable mucoadhesive properties and reasonable release rates of nicotinamide were achieved. Accordingly, these gel formulations may be applied for the treatment of oral mucosal lesions.

Keywords: Nicotinamide, bioadhesive polymer, mucoadhesiveness, release rate, gel.

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Authors: A.K. Tangirala, S. Babji

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In the last few years, three multivariate spectral analysis techniques namely, Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Non-negative Matrix Factorization (NMF) have emerged as effective tools for oscillation detection and isolation. While the first method is used in determining the number of oscillatory sources, the latter two methods are used to identify source signatures by formulating the detection problem as a source identification problem in the spectral domain. In this paper, we present a critical drawback of the underlying linear (mixing) model which strongly limits the ability of the associated source separation methods to determine the number of sources and/or identify the physical source signatures. It is shown that the assumed mixing model is only valid if each unit of the process gives equal weighting (all-pass filter) to all oscillatory components in its inputs. This is in contrast to the fact that each unit, in general, acts as a filter with non-uniform frequency response. Thus, the model can only facilitate correct identification of a source with a single frequency component, which is again unrealistic. To overcome this deficiency, an iterative post-processing algorithm that correctly identifies the physical source(s) is developed. An additional issue with the existing methods is that they lack a procedure to pre-screen non-oscillatory/noisy measurements which obscure the identification of oscillatory sources. In this regard, a pre-screening procedure is prescribed based on the notion of sparseness index to eliminate the noisy and non-oscillatory measurements from the data set used for analysis.

Keywords: non-negative matrix factorization, PCA, source separation, plant-wide diagnosis

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Authors: Lucy Ampaw-Asiedu, Terri R. Norton

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In the wake of recent disasters happening around the world such as earthquake in Italy (January, 2017); hurricanes in the United States (US) (September 2016 and September 2017); and compounding disasters in Haiti (September 2010 and September 2016); to our best knowledge, never has the world seen the need to work on preemptive rather than reactionary measures to salvage this situation than now. Tornadoes are natural hazards that mostly affect mid-western and central states in the US. Tornadoes, like all natural hazards such as hurricanes, earthquakes, floods and others, are very destructive and result in massive destruction to homes, cause billions of dollars in damage and claims many lives. Healthcare facilities in general are vulnerable to disasters, and therefore, the safety of patients, health workers and those who come in to seek shelter should be a priority. The focus of this study is to assess disaster management measures instituted by healthcare facilities. Thus, the sole aim of the study is to examine the vulnerabilities and the design of safe spaces in healthcare facilities in Central US. Objectives that guide the study are to primarily identify the impacts of tornadoes in hospitals and to assess the structural design or specifications of safe spaces. St. John’s Regional Medical Center, now Mercy Hospital in Joplin, is used as a case study. Preliminary results show that the lateral base shear of the proposed design to be 684.24 ton (1508.49kip) for the safe space. Findings from this work will be used to make recommendations about the design of safe spaces for health care facilities in Central US.

Keywords: Disaster management, safe spaces, structural design, tornado, vulnerability.

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Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

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Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: Climate, reanalysis, renewable energy, solar radiation.

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: Diesel engine, machine learning, NOx emission, semi-empirical.

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Authors: Seyed Saeid Tabaee, Omid Bahar

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Nowadays, energy dissipation devices are commonly used in structures. High rate of energy absorption during earthquakes is the benefit of using such devices, which results in damage reduction of structural elements, specifically columns. The hysteretic damping capacity of energy dissipation devices is the key point that it may adversely make analysis and design process complicated. This effect may be generally represented by Equivalent Viscous Damping (EVD). The equivalent viscous damping might be obtained from the expected hysteretic behavior regarding to the design or maximum considered displacement of a structure. In this paper, the hysteretic damping coefficient of a steel Moment Resisting Frame (MRF), which its performance is enhanced by a Buckling Restrained Brace (BRB) system has been evaluated. Having foresight of damping fraction between BRB and MRF is inevitable for seismic design procedures like Direct Displacement-Based Design (DDBD) method. This paper presents an approach to calculate the damping fraction for such systems by carrying out the dynamic nonlinear time history analysis (NTHA) under harmonic loading, which is tuned to the natural system frequency. Two MRF structures, one equipped with BRB and the other without BRB are simultaneously studied. Extensive analysis shows that proportion of each system damping fraction may be calculated by its shear story portion. In this way, contribution of each BRB in the floors and their general contribution in the structural performance may be clearly recognized, in advance.

Keywords: Buckling restrained brace, Direct displacement based design, Dual systems, Hysteretic damping, Moment resisting frames.

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Authors: Ahmed El Azab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

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Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting the fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, and then the determined factors are applied using different classification techniques. A comparison of the results of these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent researches in the same area; this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts; moreover, the study can be applied on different social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: Fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques.

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Authors: Jae-Yong Lee, Gyu-Hyun Bae, Yun-Soo Chung, Dae-Sub Kim, Jae-Sung Bae

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In general, fabric is heat-treated using a stenter machine in order to dry and fix its shape. It is important to shape before the heat treatment because it is difficult to revert back once the fabric is formed. To produce the product of right shape, camera type weft straightener has been applied recently to capture and process fabric images quickly. It is more powerful in determining the final textile quality rather than photo-sensor. Positioning in front of a stenter machine, weft straightener helps to spread fabric evenly and control the angle between warp and weft constantly as right angle by handling skew and bow rollers. To process this tricky procedure, the structural analysis should be carried out in advance, based on which, its control technology can be drawn. A structural analysis is to figure out the specific contact/slippage characteristics between fabric and roller. We already examined the applicability of camera type weft straightener to plain weave fabric and found its possibility and the specific working condition of machine and rollers. In this research, we aimed to explore another applicability of camera type weft straightener. Namely, we tried to figure out camera type weft straightener can be used for fabrics. To find out the optimum condition, we increased the number of rollers. The analysis is done by ANSYS software using Finite Element Analysis method. The control function is demonstrated by experiment. In conclusion, the structural analysis of weft straightener is done to identify a specific characteristic between roller and fabrics. The control of skew and bow roller is done to decrease the error of the angle between warp and weft. Finally, it is proved that camera type straightener can also be used for the special fabrics.

Keywords: Camera type weft straightener, structure analysis, control, skew and bow roller.

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Authors: Sama’ila Idi Ningi, Abubakar Yusuf Dutse

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The banking sector poses a lot of problems in Nigeria in general and the non-oil export sector in particular. The banks' lack effectiveness in handling small, medium or long-term credit risk (lack of training of loan officers, lack of information on borrowers and absence of a reliable credit registry) results in non-oil exporters being burdened with high requirements, such as up to three years of financial statements, enough collateral to cover both the loan principal and interest (including a cash deposit that may be up to 30% of the loans' net present value), and to provide every detail of the international trade transaction in question. The stated problems triggered this research. Consequently, information on bank financing of non-oil exports was collected from 100 respondents from the 20 Deposit Money Banks (DMBs) in Nigeria. The data was analysed by the use of descriptive statistics correlation and regression. It is found that, Nigerian banks are participants in the financing of non-oil exports. Despite their participation, the rate of interest for credit extended to non-oil export is usually high, ranging between 15-20%. Small and medium sized non-oil export businesses lack the credit history for banks to judge them as reputable. Banks also consider the non-oil export sector very risky for investment. The banks actually do grant less credit than the exporters may require and therefore are not properly funded by banks. Banks grant very low volume of foreign currency loan in addition to, unfavorable exchange rate at which Naira is exchanged to the Dollar and other currencies in the country. This makes importation of inputs costly and negatively impacted on the non-oil export performance in Nigeria.

Keywords: Supply Side Factors, Bank Financing, Non-Oil Exports.

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: Diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion equation, trends functions, bi-parameters Weibull density function.

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: Artificial intelligence, depression detection, facial emotion recognition, natural language processing, mental disorder.

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Authors: S. Fore, L. Zuze

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Frequent machine breakdowns, low plant availability and increased overtime are a great threat to a manufacturing plant as they increase operating costs of an industry. The main aim of this study was to improve Overall Equipment Effectiveness (OEE) at a manufacturing company through the implementation of innovative maintenance strategies. A case study approach was used. The paper focuses on improving the maintenance in a manufacturing set up using an innovative maintenance regime mix to improve overall equipment effectiveness. Interviews, reviewing documentation and historical records, direct and participatory observation were used as data collection methods during the research. Usually production is based on the total kilowatt of motors produced per day. The target kilowatt at 91% availability is 75 Kilowatts a day. Reduced demand and lack of raw materials particularly imported items are adversely affecting the manufacturing operations. The company had to reset its targets from the usual figure of 250 Kilowatt per day to mere 75 per day due to lower availability of machines as result of breakdowns as well as lack of raw materials. The price reductions and uncertainties as well as general machine breakdowns further lowered production. Some recommendations were given. For instance, employee empowerment in the company will enhance responsibility and authority to improve and totally eliminate the six big losses. If the maintenance department is to realise its proper function in a progressive, innovative industrial society, then its personnel must be continuously trained to meet current needs as well as future requirements. To make the maintenance planning system effective, it is essential to keep track of all the corrective maintenance jobs and preventive maintenance inspections. For large processing plants these cannot be handled manually. It was therefore recommended that the company implement (Computerised Maintenance Management System) CMMS.

Keywords: Maintenance, Manufacturing, Overall Equipment Effectiveness

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Authors: Nourhan Elshenawi

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Net Neutrality (NN) is the principle of treating all online data the same without any prioritization of some over others. A research gap in current scholarship about “violations of NN” and the subsequent ethical concerns paves the way for the following research question: To what extent violations of NN entail ethical concerns and implications for Internet stakeholders? To answer this question, NR is examined using the two major action-based ethical theories, Kantian and Utilitarian, across the relevant Internet stakeholders. First some necessary IT background is provided that shapes how the Internet works and who the key stakeholders are. Following the IT background, the relationship between the stakeholders, users, Internet Service Providers (ISPs) and content providers is discussed and illustrated. Then some violations of NN that are currently occurring is covered, without attracting any attention from the general public from an ethical perspective, as a new term Net Regularity (NR). Afterwards, the current scholarship on NN and its violations are discussed, that are mainly from an economic and sociopolitical perspectives to highlight the lack of ethical discussions on the issue. Before moving on to the ethical analysis however, websites are presented as digital entities that are affected by NR and their happiness is measured using functionalism. The analysis concludes that NR is prone to an unethical treatment of Internet stakeholders in the perspective of both theories. Finally, the current Digital Divide in the world is presented to be able to better illustrate the implications of NR. The implications present the new Internet divide that will take place between individuals within society. Through answering the research question using ethical analysis, it attempts to shed some light on the issue of NR and what kind of society it would lead to. NR would not just lead to a divided society, but divided individuals that are separated by something greater than distance, the Internet.

Keywords: Digital divide, digital entities, digital ontology, net neutrality, internet ethics, internet law, internet service providers, websites as beings.

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Authors: Mohamed Ghorab

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Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: Distributed energy resources, network energy system, optimization, microgeneration system.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: Shorena Pharjiani

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Present empirical paper investigates the relationship between FDI and economic growth by 10 selected industries in 10 Central and Eastern European countries from the period 1995 to 2012. Different estimation approaches were used to explore the connection between FDI and economic growth, for example OLS, RE, FE with and without time dummies. Obtained empirical results leads to some main consequences: First, the Central and East European countries (CEEC) attracted foreign direct investment, which raised the productivity of industries they entered in. It should be concluded that the linkage between FDI and output growth by industries is positive and significant enough to suggest that foreign firm’s participation enhanced the productivity of the industries they occupied. There had been an endogeneity problem in the regression and fixed effects estimation approach was used which partially corrected the regression analysis in order to make the results less biased. Second, it should be stressed that the results show that time has an important role in making FDI operational for enhancing output growth by industries via total factor productivity. Third, R&D positively affected economic growth and at the same time, it should take some time for research and development to influence economic growth. Fourth, the general trends masked crucial differences at the country level: over the last 20 years, the analysis of the tables and figures at the country level show that the main recipients of FDI of the 11 Central and Eastern European countries were Hungary, Poland and the Czech Republic. The main reason was that these countries had more open door policies for attracting the FDI. Fifth, according to the graphical analysis, while Hungary had the highest FDI inflow in this region, it was not reflected in the GDP growth as much as in other Central and Eastern European countries.

Keywords: Central and East European countries (CEEC), economic growth, FDI, panel data.

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Authors: T. Qasim, B. El Masoud, D. Ailabouni

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This in vitro study focused on investigating the fatigue resistance of veneered zirconia molar crowns with different veneering ceramic thicknesses, simulating the relative wear depths under simulated cyclic loading. A mandibular first molar was prepared and then scanned using computer-aided design/computer-aided manufacturing (CAD/CAM) technology to fabricate 32 zirconia copings of uniform 0.5 mm thickness. The manufactured copings then veneered with 1.5 mm, 1.0 mm, 0.5 mm, and 0.0 mm representing 0%, 33%, 66%, and 100% relative wear of a normal ceramic thickness of 1.5 mm. All samples were thermally aged to 6000 thermo-cycles for 2 minutes with distilled water between 5 ˚C and 55 ˚C. The samples subjected to cyclic fatigue and fracture testing using SD Mechatronik chewing simulator. These samples are loaded up to 1.25x10⁶ cycles or until they fail. During fatigue, testing, extensive cracks were observed in samples with 0.5 mm veneering layer thickness. Veneering layer thickness 1.5-mm group and 1.0-mm group were not different in terms of resisting loads necessary to cause an initial crack or final failure. All ceramic zirconia-based crown restorations with varying occlusal veneering layer thicknesses appeared to be fatigue resistant. Fracture load measurement for all tested groups before and after fatigue loading exceeded the clinical chewing forces in the posterior region. In general, the fracture loads increased after fatigue loading and with the increase in the thickness of the occlusal layering ceramic.

Keywords: All ceramic, dental crowns, relative wear, chewing simulator, cyclic loading, thermally ageing.

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Authors: Wenbo Wang, Yi-fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state of the art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study presents a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive and authoritative data; 2) developing a search function to automatically select relevant, new and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that: 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graph in Wikidata to dynamically augment the representations of claims and references without introducing too much noises; II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: Fact checking, claim verification, Deep Learning, Natural Language Processing.

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