bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Predictive Models to Estimate Corrosion in Buried Steel Structures
Authors: Arriba-Rodríguez Lorena-de , Rodríguez-Montequín Vicente , Villanueva-Balsera Joaquín , Ortega-Fernández Francisco
Published: November 2020

Corrosion is the main mechanism of the degradation of steel structures buried in the soil. Due to its aggressiveness, the material gradually loses thickness until the structure fails, which may cause serious environmental problems. The lack of a clearly established method in the design leads to the need for conservative excess thicknesses to ensure their useful life. This implies inefficient use of steel and an increase in the cost of the structure. In this paper, four quantitative and multivariate models were created to predict the loss of buried steel as a function of time. We developed a basic model, as well as a physical and an electrochemical one, based on multivariate adaptive regression spline (MARS), and a simpler model for comparative purposes based on clusters with Euclidean distance. The modeling was synthesized in a computer tool where the inputs were the characteristics of the soil and the time and the outputs were the loss of thickness of each predictive model and the description of the most similar real tests. The results showed that in all models, for relative errors of 10%, over 90% of predictions were correct. In addition, a real example of the operation of the tool was defined, where it was found that the estimates of the models allow the necessary optimization of steel to fulfill its useful life.
Linkages between Social Goal Orientation and Innovative Behavior: Examining the Mediating Role of Knowledge Sharing and Employee Engagement
Authors: Lee Kwangho , Song Hae-Deok
Published: November 2020

The purpose of this study is to identify the structural relationships among social goal orientation, knowledge sharing, employee engagement and innovative behavior on employees of an organization. This study used a data sample of office workers in Korean companies by survey. The findings are as follows. First, knowledge sharing plays a significant role in the relationship between social goal orientation type and innovative behavior. Second, employee engagement plays a mediating role between social goal orientation and innovative behavior. Third, the dual mediating effect of knowledge sharing and employee engagement is important between social goal orientation and innovative behavior. Our findings have important theoretical implications, which suggest that not only psychological motivations of individuals but also their social motivations should be considered to promote innovative behavior. Therefore, it is important to provide an appropriate knowledge sharing and employee engagement environment for employees according to their social goal orientation type rather than requiring innovative behavior.
Climate Change and Sustainability of Crop Yield in Dry Regions Food Insecurity
Authors: Shayanmehr Samira , Rastegari Henneberry Shida , Sabouhi Sabouni Mahmood , Shahnoushi Foroushani Naser
Published: November 2020

The main purpose of the study was to investigate the effects of climatic change on potato yield and yield variability in Agro-Ecological Zones (AEZs) of Iran during 2041–2070 (2050s). The Statistical Downscaling Model (SDSM) was performed in this study to downscale the outputs of the General Circulation Model (GCM) and to obtain local climate projections under climate scenarios for a future period. The Just and Pope Production function was used to investigate the impacts of climatic change on potato yield. The results showed that the effects of future climatic change on potato yield and its variability would vary among the different AEZs. Potato yield would change in the range from −11% to 36% across different AEZs during the 2050s. Yield variability is expected to vary from −29% to 6%. Much more generally, the results indicated that the major potato producing zones would experience a decrease in mean potato yield in the presence of climate change. Our findings would help policymakers and planners in designing appropriate policies to allocate the lands under potato cultivation among different zones. These results also have important implications for adopting ecological zone-specific strategies to mitigate the reduction in potato yield and meet food security.
The Unintended Consequences of COVID-19 Mitigation Measures on Mass Transit and Car Use
Authors: Labonté-LeMoyne Élise , Chen Shang-Lin , Coursaris Constantinos K. , Sénécal Sylvain , Léger Pierre-Majorique
Published: November 2020

As the world adapts to COVID-19, the transport behaviour of commuters has been greatly modified. Governments and transit authorities will need strong, well-received mitigation measures and education campaigns to maintain the historically upward trend of sustainable mass transit usage following this pandemic. This study, from a survey of 1968 Canadians in early May 2020, reveals that, following the end of stay-at-home orders, commuters intend to use their cars more and mass transit less. Driving these behavioural changes are commuters’ perceptions that mass transit use will negatively impact their health safety, peace of mind, and travel experience. The results also show that certain mitigation measures, such as more frequent cleaning and mandatory hand washing, are likely to reduce this decline, whereas e-monitoring and the use of health certificates will be detrimental to mass transit ridership through user perception. These results can help lessen the environmental impact of the public returning to work by encouraging their continued use of more environmentally friendly modes of transportation.
Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment
Authors: Cioara Tudor , Antal Marcel , (Pop) Claudia Daniela Antal , Anghel Ionut , Bertoncini Massimo , Arnone Diego , Lazzaro Marilena , Mammina Marzia , Velivassaki Terpsichori-Helen , Voulkidis Artemis , Ricordel Yoann , Sainthérant Nicolas , Oleksiak Ariel , Piatek Wojciech
Published: November 2020

In this paper, we address the management of Data Centers (DCs) by considering their optimal integration with the electrical, thermal, and IT (Information Technology) networks helping them to meet sustainability objectives and gain primary energy savings. Innovative scenarios are defined for exploiting the DCs electrical, thermal, and workload flexibility as a commodity and Information and Communication Technologies (ICT) are proposed and used as enablers for the scenarios’ implementation. The technology and scenarios were evaluated in the context of two operational DCs: a micro DC in Poznan which has on-site renewable sources and a DC in Point Saint Martin. The test cases’ results validate the possibility of using renewable energy sources (RES) for exploiting DCs’ energy flexibility and the potential of combining IT load migration with the availability of RES to increase the amount of energy flexibility by finding a trade-off between the flexibility level, IT load Quality of Service (QoS), and the RES production level. Moreover, the experiments conducted show that the DCs can successfully adapt their thermal energy profile for heat re-use as well as the combined electrical and thermal energy profiles to match specific flexibility requests.
Improving Governance of Tenure in Policy and Practice: A Conceptual Basis to Analyze Multi-Stakeholder Partnerships for Multi-Stakeholder Transformative Governance Illustrated with an Example from South Africa
Authors: Jansen Louisa J.M. , Kalas Patrick P.
Published: November 2020

Tenure governance is a complex and multi-dimensional issue that requires cross-sectoral and holistic approaches, gathering the resources, information and expert skills of a variety of actors while exploring innovative, polycentric multi-stakeholder governance arrangements to address collective action challenges. To do this, multi-stakeholder partnerships are formed where public and private partners pool their resources and competencies to address mutual goals more effectively. A coherent theoretical framework to analyze multi-stakeholder partnerships as part of multi-stakeholder governance is presented based on internal conditions and the external environment. The paper expands existing frameworks to analyze multi-stakeholder partnerships through introducing a new element the deliberative capacity, a decisive success factor for the effectiveness of multi-stakeholder partnerships for multi-stakeholder transformative governance at the national level. Moreover, the practical applicability of this expanded framework is illustrated in a real case example in South Africa. This country-driven, inclusive multi-stakeholder partnership process, which integrates a variety of actors in collective decision-making on the land reform process as part of a multi-stakeholder governance process, is used as an illustration of the above framework. Such a partnership linked to multi-stakeholder governance is the key instrument to attain agreement and recognition for the dedicated implementation and monitoring of the ‘Voluntary Guidelines on the Responsible Governance of Tenure of Land, Fisheries and Forests in the Context of National Food Security’ (VGGT). The investment made by the different stakeholders in this organically constituted partnership may add to a greater transformative potential in the VGGT implementation and monitoring process, and the probability that the situation on the ground will change sustainably given the explicit linkage to national governance arrangements.
The Magnitude and Determinants of Missed Opportunities for Childhood Vaccination in South Africa
Authors: Ndwandwe Duduzile , Nnaji Chukwudi A. , Wiysonge Charles S.
Published: November 2020

Missed opportunities for vaccination (MOV) may be among the factors responsible for suboptimal vaccination coverage in South Africa. However, the magnitude and determinants of MOV in the country are not known. Thus, this study seeks to assess the prevalence and determinants of MOV in the country. South Africa is sub-divided into nine administrative provinces. We used nationally representative data from the 2016 South African Demographic and Health Survey. We considered MOV to have occurred if a child aged 12–23 months old had not taken all scheduled basic vaccine doses despite having any of the following contacts with health services: delivery in a health facility; postnatal clinic visit; receipt of vitamin A; and any child-related treatment at a health facility. Multilevel logistic regression was used to determine factors associated with MOV. The national prevalence of MOV among children aged 12–23 months was 40.1%. Children whose mothers attended facility-based antenatal care were considerably less likely to experience MOV than those whose mothers did not attend antenatal care: odds ratio (OR) 0.41, 95% confidence interval (CI) 0.19 to 0.88. Conversely, the independent predictor of an increased MOV among children was residence in either the Gauteng province (OR 2.97, 95% CI 1.29 to 6.81) or Mpumalanga province (OR 2.32, 95%CI 1.04 to 5.18); compared to residence in the Free State province. Our findings suggest a high burden of MOV among children in South Africa and that MOV may be associated with individual and contextual factors. The findings also underscore the need for further exploration of the contextual factors contributing to MOV in South Africa.
DC-Based Vaccines for Cancer Immunotherapy
Authors: Fu Chunmei , Zhou Li , Mi Qing-Sheng , Jiang Aimin
Published: November 2020

As the sentinels of the immune system, dendritic cells (DCs) play a critical role in initiating and regulating antigen-specific immune responses. Cross-priming, a process that DCs activate CD8 T cells by cross-presenting exogenous antigens onto their MHCI (Major Histocompatibility Complex class I), plays a critical role in mediating CD8 T cell immunity as well as tolerance. Current DC vaccines have remained largely unsuccessful despite their ability to potentiate both effector and memory CD8 T cell responses. There are two major hurdles for the success of DC-based vaccines: tumor-mediated immunosuppression and the functional limitation of the commonly used monocyte-derived dendritic cells (MoDCs). Due to their resistance to tumor-mediated suppression as inert vesicles, DC-derived exosomes (DCexos) have garnered much interest as cell-free therapeutic agents. However, current DCexo clinical trials have shown limited clinical benefits and failed to generate antigen-specific T cell responses. Another exciting development is the use of naturally circulating DCs instead of in vitro cultured DCs, as clinical trials with both human blood cDC2s (type 2 conventional DCs) and plasmacytoid DCs (pDCs) have shown promising results. pDC vaccines were particularly encouraging, especially in light of promising data from a recent clinical trial using a human pDC cell line, despite pDCs being considered tolerogenic and playing a suppressive role in tumors. However, how pDCs generate anti-tumor CD8 T cell immunity remains poorly understood, thus hindering their clinical advance. Using a pDC-targeted vaccine model, we have recently reported that while pDC-targeted vaccines led to strong cross-priming and durable CD8 T cell immunity, cross-presenting pDCs required cDCs to achieve cross-priming in vivo by transferring antigens to cDCs. Antigen transfer from pDCs to bystander cDCs was mediated by pDC-derived exosomes (pDCexos), which similarly required cDCs for cross-priming of antigen-specific CD8 T cells. pDCexos thus represent a new addition in our arsenal of DC-based cancer vaccines that would potentially combine the advantage of pDCs and DCexos.
Glomerular Filtration Function Decline, Mortality, and Cardiovascular Events: Data from the Strong Heart Study
Authors: Suchy-Dicey Astrid M. , Zhang Ying , McPherson Sterling , Tuttle Katherine R. , Howard Barbara V. , Umans Jason , Buchwald Dedra S.
Published: November 2020

Background

Rapid kidney decline is associated with mortality and cardiovascular disease, even in the absence of CKD. American Indians (AI) have particularly high burden of kidney disease, cardiovascular disease, and stroke. This study aims to examine extreme loss in glomerular function in this population in association with clinical outcomes.

Methods

The Strong Heart Study, a large longitudinal cohort of adult AI participants, collected plasma creatinine at three examination visits between 1989 and 1999. Intraindividual regressions of eGFR provided linear estimates of the change in kidney function over this time. Surveillance with physician adjudication identified mortality and cardiovascular events between visit three through to 2017.

Results

Mean change in eGFR was loss 6.8 ml/min over the 10-year baseline (range: −66.0 to +28.9 ml/min). The top 1 percentile lost approximately 5.7 ml/min per year. Participants with extreme eGFR loss were more likely to have diabetes (95% versus 71%), hypertension (49% versus 33%), or longer smoking history, among smokers (19 pack-years versus 17 pack-years). CKD (eGFR <60 ml/min) was associated only with mortality, independent of slope: HR, 1.1; 95% CI, 1.0 to 1.3. However, extreme loss in eGFR (>20 ml/min over baseline period) was associated with mortality, independent of baseline eGFR: HR, 3.5; 95% CI, 2.7 to 4.4, and independently associated with composite CVD events and CHF: HR, 1.4 and 1.7; 95% CI, 1.1 to 1.9 and 1.2 to 2.6, respectively.

Conclusions

This is the first examination of decline in eGFR in association with mortality and CVD among AIs. The implications of these findings are broad: clinical evaluation may benefit from evaluating change in eGFR over time in addition to dichotomous eGFR. Also, these findings suggest there may be aspects of renal function that are not well marked by clinical CKD, but which may have particular relevance to long-term renal and vascular health.
Yeşil Yöntemle Sentezlenen Biyoaktif Nanopartiküller
Authors: ÇİFTÇİ Harun , ER ÇALIŞKAN Çiğdem , ÖZTÜRK Kübra , YAZICI Burcu
Published: November 2020

Nanoteknoloji, bilimin tüm alanlarında uygulanan umut verici teknolojilerden biri haline gelmiştir. Biyoteknolojik olarak üretilen metalik nanopartikülller (NP), biyomedikal ve fizyokimyasal alanlardaki kapsamlı uygulamaları nedeniyle bilimsel uygulama ve teknoloji platformlarında ilgi görmektedir. Son yıllarda sentetik ilaçların kullanımı sonucu meydana gelen yan etkiler ve bunların yol açtığı medikal ve ekonomik sorunlar tedavilerde bitki kullanımını tekrar popüler hale getirmiştir. Bitkilerden değişik yöntemlerle elde edilen bitki ekstraktları ile 100 nm’den daha küçük boyutta, ekolojik, toksik olmayan metal esaslı (altın, gümüş, palladyum, mangan, çinko gibi) NP’ler sentezlenebilmektedir. NP’lerin boyutları ve şekilleri değiştikçe partiküllerin fiziksel, kimyasal, biyoaktif, optik, elektriksel, katalitik ve toksisite özellikleri de değişmektedir. Yeşil sentez olarak da bilinen biyolojik sentez; yüksek basınca, yüksek sıcaklık değerlerine ve toksik kimyasallara gerek duyulmadan NP’lerin kolay ve ekolojik olarak elde edilmesinde kullanılan pratik yöntemdir. NP’lerin yeşil sentezi bakteri, mantar, maya, virüs, mikroalg ve bitki biyokütlesi/özü gibi farklı biyomateryaller kullanılarak gerçekleştirilmektedir. Metalik NP’lerin bitki aracılı biyosentezi, bitkide bulunan organik fonksiyonel gruplar içeren biyomoleküller (proteinler, vitaminler, amino asitler, enzimler, polisakkaritler, sitratlar, organik asitler gibi) aracılığıyla gerçekleşir. Medikal alanlarda NP’lerin artan uygulaması, NP’lerin biyolojik etkileşimlerinin mekanizmalarının ve potansiyel toksisitelerinin daha iyi anlaşılmasını gerekli kılmaktadır. Bu derlemede, fiziksel, kimyasal ve yeşil sentez dâhil NP’lerin sentez yolları açıklanmaktadır. Ayrıca literatürde güncel çalışmalarda verilen partikül karakterizasyonu yöntemleri ve partiküllerin antibakteriyel, antifungal ve antiviral aktivite gibi özellikleri ayrıntılı olarak tartışılmaktadır.
The Sustainable Development Goals, climate crisis and sustained injustices
Authors: Villavicencio Calzadilla Paola
Published: November 2020

In 2015, the UN adopted the 2030 Agenda and the Sustainable Development Goals (SDGs), a set of universal goals in key areas of action linked to sustainable development. The SDGs address not only highly relevant socioeconomic issues, but also pressing environmental challenges associated with the Anthropocene, such as climate change. The integration of a specific climate goal – SDG 13 – into the SDGs is paramount as climate change is a global and urgent threat compromising the realisation of all the SDGs. However, the SDGs’ focus on issues linked to the current economic growth pattern and development paradigm may prevent them from addressing the climate crisis and the inequalities and injustices associated with it. This paper attempts to establish the extent to which the SDGs promote progress towards achieving climate justice or if, on the contrary, they maintain the status-quo and continue to fuel the climate crisis while leaving millions behind.
An approach to organizing the transition of vehicle control from an automated driving system to a person
Authors: Dubovsky V. A. , Savchenko V. V.
Published: November 2020

The analysis of trends in the development of the automotive industry and well-known methods of automating vehicle control served the basis for us to propose an approach to organizing the transfer of vehicle control from an automated driving system to a person. The approach involves monitoring the vehicle performance and the systems that provide automated driving, the state of the environment and the driver's psychophysiological state, as well as road conditions on the upcoming path, predicting the place and time of transition of control to the driver, determining and regulating his/her readiness to take control if necessary. This approach is peculiar for in time of automated driving, the minimum level of the driver's readiness to operate the vehicle is constantly maintained, which is brought to optimal within a certain time before the scheduled transition to manual control. This two-level monitoring of the condition of drivers of highly automated vehicles will improve road safety both in cases of predicted and unexpected need for an emergency transition from automated to manual driving. The aim of the work is to develop a methodology for improving road safety with highly automated vehicles involved.
Computer modeling of volumetric damageability in the mine roadway neighbourhood
Authors: Sherbakov S. S. , Shemet L. A. , Nasan A. A.
Published: November 2020

The object of research is a rock massif with various cross-sectional shapes of roadway. The purpose of work: computer modeling of stress-strain state and volumetric damageability in the neighbourhood of a mine roadway. The undisturbed rock massif has an initial stress-strain state (under its own weight) before a mine roadway is formed. Therefore, to determine the stress-strain state of the rock massif with the mine roadway, we must first calculate the stress state of the rock massif without the roadway and then take it into account as a pre-stressed state for the rock massif therewith. Damageability assessment of the rock massif with a mine roadway was carried out based on the obtained distributions of stresses and strains. We calculated volumetric damageability through the model of a deformed solid body with dangerous volume. Dangerous volume is a limited area where stresses or strains exceed the predetermined threshold. Calculation of dangerous volumes and integral damageability was carried out in the finite element package ANSYS. The program was written in APDL. The ratios between the existing and limiting stresses was calculated for each finite element. The elements for which this ratio exceeds unity will form a dangerous volume for the whole model. As a result, we have an array of finite elements constituting the dangerous volume and its value. The developed method for assessing damageability in the mine roadway neighbourhood takes into account various cross-sectional shapes of the mine roadway and its depth. The relevance of studying possible destruction regions using the model of a deformed solid body with dangerous volume was substantiated.
Modeling the impacts of heavy charged particles on electrical characteristics of n-MOSFET device structure
Authors: Lovshenko I. Yu. , Stempitsky V. R. , Shandarovich V. T.
Published: November 2020

The use of microelectronic products in outer space is possible if protection is provided against special external influencing factors, including radiation effect. For digital integrated circuits manufactured using submicron CMOS processes, the greatest influence is exerted by radiation effects caused by exposure to a heavy charged particle. The use of special design tools in the development of dual-purpose microcircuits, with increased resistance to the impact of heavy charged particles, prevents single events from occurring. Thus, the use of modern software products for device and technological modeling in microelectronics when developing the element base of radiation-resistant microcircuits for space purposes will cut the time to develop new products and make it possible to modernize (improve performance) already existing device and circuitry solutions. The paper delivers the results of modeling the impacts of heavy charged particles with a magnitude of linear energy transfer equal to 1.81, 10.1, 18.8, 55.0 MeV·cm2/mg, corresponding to nitrogen ions 15N+4 with an energy E = 1,87 MeV; argon 40Ar+12 with an energy E = 372 MeV; ferrum 56Fe+15 with an energy E = 523 MeV; xenon 131Xe+35 with an energy E = 1217 MeV, on electrical characteristics of n-MOSFET device structure. The dependences of the maximum drain current IС on the motion trajectory of a heavy charged particle and the ambient temperature are shown.
Theoretical study of spreading resistance using anisotropic conductivity parameters for graphene: a comparative study against conventional isotropic conductors
Authors: Seki Kazuhiko , Kubo Toshitaka , Ye Nan , Shimizu Tetsuo
Published: November 2020

Graphene can lower spreading resistance owing to its anisotropic electrical resistivity. Although graphene is beneficial for collecting in-plane spreading currents, its low out-of-plane conductivity is a disadvantage. We theoretically study the spreading resistance of single- and multi-layer graphene films coated over a metal substrate. The effect of layer thickness and substrate conductivity on the spreading resistance of graphene is interpreted using electric field and equipotential lines. The results are compared to those obtained using conventional isotropic conducting films. We discuss the scenarios where graphene-coated layers are more beneficial than those coated using conventional materials. We also discuss the sensitivity in detecting the layer thickness of graphene by measuring spreading resistance.
Using Platforms and Platform Law to Overcome Risks Caused by Digitalization Processes
Authors: Altoukhov A. V. , Kashkin S. Yu. , Kuz’mina M. V.
Published: November 2020

Fundamental changes within a country and at the global level can have contradictory consequences for society. The more areas are affected by changes and the deeper these changes are, the more significant the necessary innovations can be. Considering the scale of digitalization and application of artificial intelligence technologies based on it, it can be concluded that we are dealing with an unprecedented phenomenon that needs to be thoroughly assessed by different experts.

Aim. The presented study aims to assess risks associated with the implementation of platform solutions without appropriate legislative initiatives, which, in turn, should facilitate the creation of the platform law institution. Today, legal science assesses risks associated with the legislative regulation of processes and creates conditions for safe and productive interaction with new mechanisms.

Tasks. The authors examine current legislation to create conditions for protecting the rights and legitimate interests of legal entities in their interaction with cutting-edge digital solutions and for analyzing the possibility of full-scale application of digital platforms on this basis; estimate the legal risks of applying digital innovations under current conditions.

Results. Analytical work has shown that platform solutions are a new technological unit that cannot be fully regulated by existing legal norms due to its technological features. The lack of personalized legal regulation of platforms not only infringes the rights of citizens providing various public and other services using digital technologies, but also creates conditions for the aggravation of the crime situation and the development of new types of crime.

Conclusions. The main risks of mass digitalization are considered. The technological features of innovations make it necessary to develop a branch of law that would regulate public relations during interaction with platform solutions and other information technologies. The authors propose a new complex mechanism of legal regulation — platform law, which will make using platforms completely safe and efficient in all sectors of society.
Assessment of Safety Risk for Signalized and Un signalized Intersection in a Road Network
Authors:   Phd. Scholar, Department of Civil Engineering, Maulana Azad National Institute of Technology, Bhopal (M.P), India., Pandey Daya Shankar
Published: November 2020

The spectacular increase of number of motor vehicles on the road is mainly attributed ingeneration of traffic problems like accidents, congestions, delays etc., especially in the urban premises of developing countries. This paper examines the traffic problems and sustainable improvement of road intersection at Bhopal, India. The special and temporal constitutions of the vehicle as well as pedestrian traffic at the intersections were examined and the characteristics of the junction indoctrinating the delay problems are identified. Data regarding the traffic volume, land use and pedestrian movement activities are collected through surveys, expert opinion and literature . Analysis of the collected data revealed that the improper planning of the junctions, lack of traffic signals and unauthorised parking are the major factors contributing to the traffic congestions. Various Using data collected from surveys, traffic frequency and severity standards for signalized and Un signalized have been established. The methodologies are developed incorporating the relative importance of different severity of different safety indices at intersection. The relative importance (weights) of very low, low, medium and high severity condition is developed using data collection and expert opinions experience people which have knowledge in development/safety development at intersection were obtained by conducting a survey.
Evaluation of Road Safety for Roundabout and Signalized Intersection
Authors:   Phd. Scholar, Department of Civil Engineering, Maulana Azad National Institute of Technology, Bhopal (M.P), India, Pandey Daya Shankar , Agarwal Dr. P.K. ,   Professor, Department of Civil Engineering, Maulana Azad National Institute of Technology, Bhopal (M.P), India
Published: November 2020

Traditional intersections have always caused accidents. There are numerous geometric intersection designs that best fit each situation. This study performed an operational and safety comparison with different intersection like signalized, unsignalized and roundabout to decrease the overall travel delay & collision at intersection and increase the safety using case study. This dissertation describes the application of the traffic conflict technique to estimate, traffic safety at intersections. Using data collected from surveys, traffic frequency and severity standards for signalized and roundabout have been established. The methodologies are developed incorporating the relative importance of different severity of different safety indices at intersection. The relative importance (weights) of very low, low, medium and high severity condition is developed using data collection and expert opinions experience people which have knowledge in development/safety development at intersection were obtained by conducting a survey. A questionnaire was prepared to obtain the relative importance of different severity of different parameter performance. The weights are developed in such a way that their values lie between 0 and 1. In proposed work design safety parameter for intersection for enhancement of safety at intersections and all safety design is implemented on MATLAB and analysis of the geometrical design for vehicle system in the intersection by MATLAB, analyses, the status of confliction and desired value obtained by comparison of actual value with available geometric designs and to enhance the safety at intersection and explores methods to solve the problem of collision at intersections. In this paper evaluate safety parameter of roundabout.
Biosurfactan Injection of U-Champ on Heavy Oil Sample in Laboratory for Preliminary to Pilot Project
Authors:   Petroleum Engineering, UPN “Veteran” Yogyakarta, Yogyakarta, Indonesia., Budiharjo S. Harry , Pamungkas Joko ,   Petroleum Engineering, UPN “Veteran” Yogyakarta, Yogyakarta, Indonesia., Widyaningsih Indah ,   Petroleum Engineering, UPN “Veteran” Yogyakarta, Yogyakarta, Indonesia., Wahyuningsih Triyana ,   Petroleum Engineering, UPN “Veteran” Yogyakarta, Yogyakarta, Indonesia.
Published: November 2020

Biosurfactants “U-Champ” is made by microorganisms, it could be changes the fluid characteristics which are, viscosity and Interfacial tension (IFT). In this study, will be presented the effect of Biosurfactan “U-Champ” injection into the heavy oil sample on laboratory experiment. Viscosity and IFT measurement was carried out in this experiment to analyze the characteristic changes. Coreflooding experiment also occur to measure the incremental of oil recovery. We used some of concetration of Biousrfactant “U-Champ” (1%;2,5%;5%;10%). In this experiment, we found 5% concetration of Biosurfactant “U-Champ” as the CMC value. The result of observation indicates the reduction of viscosity from 5.57 cp to 1.76 cp at 30oC, and from 1 cp to 0.95 cp at 80oC, and reduced the IFT value from 10.05 mN/m to 3.81 mN/m. Based on the result, Coreflooding experiment was occur to measure the incremental of oil recovery and obtained the increasing of recovery factor from 37,5% after waterflooding process to 81,25%. Finally, this studies feasible to continue in pilot project.
Internet-of-Things IoT based Smart Farming Towards Making the Precision Farming in Agriculture
Authors:   Received Master of Technology in Computer Science and Web Technologies from JNTU Hyderabad, India., Laxmaiah Dr. Bagam , Ramji Banothu ,   working Associate Professor in the department of Computer Science and Engineering, CMR Technical Campus, Hyderabad, India., Mahesh Kotha ,   Associate Professor in the department of Computer Science and Engineering, in CMR Technical Campus, Hyderabad, India.
Published: November 2020

Internet of Things (IoT) technology, has been changed every area of human life by making everything. Well-Developed and bright IOT communicates that a network of things or people which make a self-building network. Smart farming food excellently and supportable for the public. High quality farming-based is one of the most important arena systems of increasing food excellently and supportable for the public. High quality farming is one of the well-known applications of IoT in the agriculture are and plentiful establishments are taking advantage of this procedure around the world. One more type of IoT invention in farming and one more element of high-quality farming is harvest management devices. And weather positions, they should be placed in the field to collect data designed only for happening and only with in crop farming, from temperature and rainfall to leaf water and complete crop health. The use of farming-based drones in smart farming. Also called as UAVs (unmanned air vehicles), drones are drones are well prepared than airplanes and satellites to collect farming-based data. With the increasing approval of the Internet of Things (IoT), connected devise have got into every trait of our life from health, home automation, self-pushed and planning required to move people and supplies to where they’re needed, smart cities and industrial IoT.
Quality Improvements of Camera Captured Pictures using Blind and Non-blind Deconvolution Algorithms
Authors:   Department of Electronics and Telecommunication, VPKBIET, Baramati, Pune, India., Patil Pallavi U. , Lande Dr. Sudhir B. ,   Department of Electronics and Telecommunication, VPKBIET, Baramati, Pune, India., Nagalkar Dr. Vinay J. ,   Department of Electronics and Telecommunication, VPKBIET, Baramati, Pune, India., Nikam Sonal B. ,   Department of Electronics and Telecommunication, VPKBIET, Baramati, Pune, India.
Published: November 2020

Camera captured image is a set of three-dimensional picture frame. This picture frame is a set of different characteristics and parameters. Captured picture suffers from image blurring parameters. These blurring parameters are created by camera misfocus, motion, atmospheric causes, camera sensor noise etc. Thus, captured picture is represents the blurry image format due to lot of interferences occurs in the surrounding background and picture captured device. Hence, some information is corrupted i.e. degradation occurs in the camera captured picture. Therefore, it needs to reconstruct the original picture using image restoration process. Restoration operation includes different image deblurring algorithms such as Non-blind deconvolution and Blind deconvolution algorithms. Non-blind deconvolution algorithms are more effective when blurring parameters of captured picture is known but Blind deconvolution algorithm recover the blurry image without prior knowledge about blurring parameters.
An Efficient Ensemble Classifier for Heart Disease Diagnosis and early Prediction
Authors:   Computer Science and Applications, St.Peter’s Institute of Higher Education and Research, Avadi, Chennai, Tamil Nadu, India., Brindha S. , Ajisha T. ,   Computer Science and Applications, St.Peter’s Institute of Higher Education and Research, Avadi, Chennai, Tamil Nadu, India.
Published: November 2020

Heart Disease is one of the most significant causes of mortality in the world today. Prediction and Diagnosis of Cardiovascular disease is considered as one of the major challenges in the Medical Field especially for Cardiologists. Artificial Intelligence and Machine learning (ML) was popularly employed for pattern prediction and it was noticed that these Intelligent Mechanisms were used in Medical Feld for better Heart Disease Pattern Prediction. Thus more researchers were focusing Machine Learning based Data Mining Classifiers for Heart Disease Pattern Prediction and Diagnosis in the healthcare Industry especially for Cardiologists. This research work identified the recently proposed Hybrid Random Forest with a Linear Model (HRFLM) Classifier for improving the classification accuracy for the cardiovascular disease patterns prediction well in advance and Diagnosis as well. However, it was noticed that for improving the performances better in terms of Accuracy, Sensitivity, Specificity, Precision, FScore and False Positive Rate FPR, needed an efficient classifier. Thus this work developed and implemented an efficient Classifier ensemble Nu-SVC Classifier and Weighted Random Forest Classifier. From the experimental results, it was noticed that the proposed Ensemble Classifier performs better as compared with that of existing Hybrid Classifier in terms of in terms of Accuracy, Sensitivity, Specificity, Precision, FScore and False Positive Rate FPR
Data mining Application of Data Reduction and Clustering Domain of Textile Database
Authors:   Assistant Professor, Department of Statistics, Madras Christian College, Chennai (Tamil Nadu), India., Salomi M. , Priya R. Lakshmi ,   Assistant Professor, Department of Statistics, Dr. Ambedkar Govt. Arts College, Chennai (Tamil Nadu), India., G Manimannan ,   Assistant Professor, Department of Mathematics, TMG College of Arts and Science, Chennai (Tamil Nadu), India., Devi N. Manjula ,   Bio Statistician, Department of Community Medicine, Karpaka Vinayakar Institute of Medical Sciences, Chengalpet, (Tamil Nadu), India.
Published: November 2020

This research paper attempts to identify the textile data structure and hidden pattern of original database with certain important parameters. The main objectives of this study are to identify the first n number of factors that explained over the study period. Initially factor analysis is performed to extract factor scores. Principal extraction is performed through Data mining package with sixteen textile fabrics parameters. Factor extraction is aimed to uncover the intrinsic pattern among the textile parameters considered and an important point of factor analysis is to extract factor scores for further investigation. Thus, factor analysis consistently resulted in three factors for the whole datasets. The amount of total variation explained is over 75 percent in factor analysis with varimax rotation. The factor loadings or factor structure matrix with unassociated rotation methods are not always easy to interpret. The nonhierarchical k-mean clustering is also used to identify meaningful cluster based on their parameter means of original database.
Economic Growth and Sustainable Development in India
Authors:   Assistant Professor, Department of Management, ICFAI University, Rajawala Road, Selaqui, Central Hope Uttarakhand, India., Choudhary Dr. Rashmi , Srivastava Pooja Prakash ,   Research Scholar, Department of Management, ICFAI University, Rajawala Road, Selaqui, Central Hope Uttarakhand, India.
Published: November 2020

This paper outlines one of the pivotal ambiance issues cladding India is that of speck contamination from the ignition of hydrocarbon deposits. This has sincere fitness outcomes and with the swift ballooning in the fiscal stability these influences are expanding. Along with it, the expansion of monetary condition is a mandatory and strategy designers are anxious about the feasibility that contamination depletion actions could lower extension remarkably. When look back over centuries, the thesis of progress has walked a long distance. It commenced with an emphasis on monetary advancement and progress, and gradually has landed to a station where explorers, authorities and academicians are searching at more comprehensive designs of livelihood than just simple progress. Imperishable evolution, gradually, has become the most significant conception at present and supplies a more understandable meaning of progress, associating up bionomical amenities and standard of living with monetary advancement. Such a prototype move in a stage of less than a centenary is no less than a innovation.
Automatic Intelligent Movie Sentiment Analysis Model Creation for Box Office Prediction using Multiview Light Semi Supervised Convolution Neural Network
Authors:   Jain University, Bangalore , India., Kulkarni Chaitra , Manuja Dr. Manoj ,   Chitkara University Rajpura, Punjab, India., Suchithra Dr. R ,   Jain University, Bangalore , India.
Published: November 2020

With the rapid growth of e-commerce, online product and service monitoring is becoming more and more established as an important source of information for both sellers and customers. Emotional surveys and comments for online review analysis are gaining more and more attention as such studies help use information from online reviews for potential economic impacts. Twitter is a widely used social networking site and a trusted source of public opinion. The success of the film can be predicted by analyzing the tweets and researching the impact of the film. This report discusses the application of emotional analysis and in-depth machine learning methods to understand the relationship between online movie reviews, and this story is used to generate revenue at the movie box office. In this paper, this work present a Intelligent Extensive Information Rich Transfer Network (IEIRTN). It is modeled with information from sentences (i.e., reviews) and aspects simultaneously. First, IEIRTN extract all aspects of the sentence. After obtaining the aspects, it utilize all data in the source domain and the target domain for training Multiview Light Semi Supervised Convolution Neural Network (MLSSCNN) classifier. To understand the predictive performance of this approach several performance metrics are used. The experimental result shows that the MLSSCNN offers a superior predictive effect than other classifier.
Data Visualization for Accelerated Business Intelligence in the Indian Health Care Sector using Tableau
Authors:   General Management and Analytics, VES Business School, Mumbai, India., Sharma Dr. Brijesh R. , Deshmukh Dr Sachin ,   Dean – PGDM Program Chair – Business Analytics, VES Business School, Mumbai, India.
Published: November 2020

Purpose Big data analytics capability is the new source of competitive advantage. This is very axiomatic and it is also known that this capability covers the domain of descriptive, diagnostic, predictive and prescriptive analytics. Apart from the capability of managing data coming with high velocity, huge volume, and high variety the capability to analyze data with the same or more speed is a not only a hygiene factor but a compulsion for any organization. Ease of use of data visualizing tools which help in describing the data is driving the consumption of visualization tools and Tableau has taken a clear lead, and is witnessing mass adoption. The paper is a detailed account of creating a interactive visualization of heath care infrastructure data using Tableau Publix as a business intelligence tool. Methods: The Visualization is done on data taken from Open Government Data (OGD) Platform India. The paper is a demonstration of the use of visualization for exploration of data, generation of relevant questions and thereafter finding the right answers. Result: The papers explores the data and does the following through visualization 1. Maps the geography (Indian states) with total number of patients) 2. Maps the state name with segregated number of patients suffering from acute and chronic disease. 3. Maps the state name with segregated number of patients suffering from chronic disease. 4. Maps the state name with segregated number of patients suffering from acute disease. 5. Builds all the above in an interactive dashboard.
Technology and Sustainable Solutions: An Approach for Curbing Air Pollution in India: Way Forward Lessons to Learn
Authors:   Associate Professor at Amity international Business School, Amity University, Noida(UP), India., Mahajan Dr. Navita , Garg Dr Seema ,   Associate Professor at Amity International Business School, Amity University, Delhi, India.
Published: November 2020

Magnitude of tainting air quality has been a count of ginormous difficulty in metropolis regions and Indo Gangetic Plains during winters in India. It has detrimental impact on surroundings and human vigour. The reduction in environmental air pollution is one of the most significant and societal concern for our country. As valuable means for pollution control, minimization and mitigation remains serious approaches, we need to look at the sustainable solutions to curb this on long term. Different measures are being taken at individual level, society level and institutional level, however an effective approach that will work for everyone has to be considered. Artificial intelligence (AI), IoT’s technologies, ICT Solutions, breeze Technology, Titanium Technology, automated cars, Smog towers are some of the effective approaches and technology solutions for tackling these complexities. In this study, the recent advancements of these technologies apart from the various initiatives by Indian start-ups have been highlighted and examined. Information relevant to the subject area is investigated. The study also covers some of the progressive answers from the world over to lessen the vehicular pollutants and to offer an unceasing community to converge to the dreams of sustainable development, and how countries with least air pollution can be a pioneer example to follow their footsteps to understand the smart technologies used by different Countries.
Design of Bio-retention Filter Basin for Conservation and Purification of Storm water runoff in Urban Areas
Authors:   Civil Engg., Amity School of Engineering and Technology, Amity University Mumbai, Panvel, Maharashtra, India., Mishra S. sangita , Verma Vishesh ,   Civil Engg., Amity School of Engineering and Technology, Amity University Mumbai, Panvel, Maharashtra, India.
Published: November 2020

Urban areas are more susceptible to water logging and subsequent flood conditions because of reduced rate of infiltration arising from construction activities particularly during the monsoon season. However, if the storm water runoff is conserved and purified, it will be useful to cater to the needs of the huge population in urban areas during the periods of less rainfall or non-monsoon season. Bio-retention basins are best management practices that use a biogeochemical process within a vegetative eco-system to provide soil moisture retention and purification of storm water. While this structure has been implemented in many countries around the world, it is yet to be implemented in Indian cities with necessary modifications considering the topography, population pressure, hydrological characteristics of a basin, and the soil and water management practices. This project work is oriented to design a bio-retention filter basin in the parking lots or roadsides or streetscapes in Indian urban cities.