bluuebunny/crossref_metadata_2025 huggingface dataset:
Ratiometric BRET Measurements of ATP with a Genetically-Encoded Luminescent Sensor
Authors: Min Se-Hong , French Alexander R. , Trull Keelan J. , Tat Kiet , Varney S. Ashley , Tantama Mathew
Published: August 2019

Luciferase-based reporters provide a key measurement approach in a broad range of applications, from in vitro high-throughput screening to whole animal imaging. For example, luminescence intensity is widely used to measure promoter activity, protein expression levels, and cell growth. However, luminescence intensity measurements are subject to quantitative irregularities caused by luminescence decay and variation in reporter expression level. In contrast, bioluminescence resonance energy transfer (BRET) sensors provide the advantages of luciferase-based reporters but overcome the aforementioned irregularities because of the inherently ratiometric readout. Here, we generated a new ratiometric BRET sensor of ATP (ARSeNL—ATP detection with a Ratiometric mScarlet-NanoLuc sensor), and we demonstrated that it provides a stable and robust readout across protein, cell, and whole animal tissue contexts. The ARSeNL sensor was engineered by screening a color palette of sensors utilizing variants of the high photon flux NanoLuc luciferase as donors and a panel of red fluorescent proteins as acceptors. We found that the novel combination of NanoLuc and mScarlet exhibited the largest dynamic range, with a 5-fold change in the BRET ratio upon saturation with ATP. Importantly, the NanoLuc-mScarlet BRET pair provided a large spectral separation between luminescence emission channels that is compatible with green and red filter sets extensively used in typical biological microscopes and animal imaging systems. Using this new sensor, we showed that the BRET ratio was independent of luminescence intensity decay and sensor expression level, and the BRET ratio faithfully reported differences in live-cell energy metabolism whether in culture or within mouse tissue. In particular, BRET analyte sensors have not been used broadly in tissue contexts, and thus, in principle, our sensor could provide a new tool for in vivo imaging of metabolic status.
3D Virtual Reconstruction of the Ancient Roman Incile of the Fucino Lake
Authors: Di Angelo Luca , Di Stefano Paolo , Guardiani Emanuele , Morabito Anna Eva , Pane Caterina
Published: August 2019

The construction of the artificial emissary of Fucino Lake is one of the most ambitious engineering buildings of antiquity. It was the longest tunnel ever made until the 19th century and, due to the depth of the adduction inlet, it required a monumental and complex incile, which, for functionality, cannot be compared to other ancient emissaries. The Roman emissary and its "incile" (Latin name of the inlet structure) were almost completely destroyed in the 19th century, when Fucino Lake was finally dried. Today, only few auxiliary structures such as wells, tunnels, and winzes remain of this ancient work. As evidence of the ancient incile remains a description made by those who also destroyed it and some drawings made by travelers who, on various occasions, visited the site. This paper presents a virtual reconstruction of the Roman incile, obtained both through the philological study of the known documentation, interpreting iconographic sources that represent the last evidence of this structure, and through the survey on the territory. The main purpose is to understand its technical functionalities, the original structures, and its evolution during the time, taking into account the evolution of the Fucino Lake water levels, technological issues, and finally offering its visual reconstruction.
Detecting Water Diversion Fingerprints in the Danjiangkou Reservoir from Satellite Gravimetry and Altimetry Data
Authors: Chao Nengfang , Chen Gang , Luo Zhicai , Su Xiaoli , Wang Zhengtao , Li Fupeng
Published: August 2019

The Danjiangkou Reservoir (DJKR) is the freshwater source for the Middle Route of the South-to-North Water Diversion Project in China, and its water level and storage changes are important for water resource management. To maximize the potential capacity of the Gravity Recovery and Climate Experiment (GRACE) mission, an improved Lagrange multiplier method (ILMM) is first proposed to detect terrestrial water storage anomalies (TWSA) in the small-scale basin (DJKR). Moreover, for the first time, water diversion fingerprints are proposed to analyze the spatiotemporal pattern of the TWSA in the DJKR. The results indicate that the increased water level and storage signals due to the DJKR impoundment in 2014 can be effectively detected by using the ILMM, and they agree well with the results from altimetry and in situ data. Additionally, the water diversion fingerprints due to the DJKR impoundment are inferred, and describe the progression of spatiotemporal variability in water storage. The results show that water storage decreased in the upper Hanjiang River and increased in the DJKR as well as to the east of it during the period 2013–2015. Our research provides a scientific decision-making basis for monitoring the water resources of the DJKR and managing the South-to-North Water Diversion Project.
Measurement of Dynamic Responses from Large Structural Tests by Analyzing Non-Synchronized Videos
Authors: Yang Yuan-Sen
Published: August 2019

Image analysis techniques have been employed to measure displacements, deformation, crack propagation, and structural health monitoring. With the rapid development and wide application of digital imaging technology, consumer digital cameras are commonly used for making such measurements because of their satisfactory imaging resolution, video recording capability, and relatively low cost. However, three-dimensional dynamic response monitoring and measurement on large-scale structures pose challenges of camera calibration and synchronization to image analysis. Without satisfactory camera position and orientation obtained from calibration and well-synchronized imaging, significant errors would occur in the dynamic responses during image analysis and stereo triangulation. This paper introduces two camera calibration approaches that are suitable for large-scale structural experiments, as well as a synchronization method to estimate the time difference between two cameras and further minimize the error of stereo triangulation. Two structural experiments are used to verify the calibration approaches and the synchronization method to acquire dynamic responses. The results demonstrate the performance and accuracy improvement by using the proposed methods.
Predicting Renovation Waste Generation Based on Grey System Theory: A Case Study of Shenzhen
Authors: Ding Zhikun , Shi Mengjie , Lu Chen , Wu Zezhou , Chong Dan , Gong Wenyan
Published: August 2019

With the rapid development of urbanization, more and more people are willing to improve their living conditions, thus substantial attention has been paid to residential renovation in China. As a result, large quantities of renovation waste are generated annually which seriously challenge sustainable urban development. To effectively manage renovation waste, accurate prediction of waste generation rates is a prerequisite. However, in the literature, few attempts have been made for predicting renovation waste as renovation activities vary significantly in different cases. This study offers an approach to estimate the amount of renovation waste based on the vacancy rate and renovation waste generation rates at a city level. The grey system theory was applied to predict the amount of renovation waste in Shenzhen. Results showed that the amount of renovation waste would reach 135,620 tons in 2023. The research findings can provide supportive information to relevant stakeholders for developing a renovation waste management framework.
Enterprise Resilience Assessment—A Quantitative Approach
Authors: Sanchis Raquel , Poler Raúl
Published: August 2019

Enterprise resilience is a key capacity to guarantee enterprises’ long-term continuity. This paper proposes a quantitative approach to enhance enterprise resilience by selecting optimal preventive actions to be activated to cushion the impact of disruptive events and to improve preparedness capability, one of the pillars of the enterprise resilience capacity. The proposed algorithms combine the dynamic programming approach with attenuation formulas to model real improvements when a combined set of preventive actions is activated for the same disruptive event. A numerical example is presented that shows remarkable reductions in the expected annual cost due to potential disruptive events.
Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery
Authors: Wu Jindong
Published: August 2019

Urban trees provide various important ecological services, the quantification of which is vital to sustainable urban development and requires accurate estimation of tree biomass. A limited number of allometric biomass equations, however, have been developed for urban species due to the prohibitive cost. Remote sensing has provided cost-effective means for estimating urban forest biomass, although the propagation of error in the estimation process is not well understood. This study aimed to offer a baseline assessment of the feasibility of estimating urban tree biomass with remote sensing-based general equations applicable to broad taxonomic groups by conducting a large urban tree inventory on a university campus. The biomasses of 191 trees of seven species from the inventory, separated into two categories (i.e., evergreen and deciduous), were calculated exclusively with urban-based species-specific allometric equations. WorldView-2 satellite imagery data were acquired to retrieve normalized difference vegetation index (NDVI) values at the location, crown, and stand levels. The results indicated that biomass correlated with NDVI in varying forms and degrees. The general equations at the crown level yielded the most accurate biomass estimates, while the location-level estimates were the least accurate. Crown-level spectral responses provided adequate information for delivering spatially explicit biomass estimation.
Contrasting Toxin Selectivity between the Marine Pufferfish Takifugu pardalis and the Freshwater Pufferfish Pao suvattii
Authors: Gao Wei , Kanahara Yoko , Yamada Misako , Tatsuno Ryohei , Yoshikawa Hiroyuki , Doi Hiroyuki , Takatani Tomohiro , Arakawa Osamu
Published: August 2019

To clarify the differences in toxin selectivity between marine and freshwater pufferfish, we conducted experiments in artificially reared nontoxic specimens of Takifugu pardalis (marine) and Pao suvattii (freshwater) using tetrodotoxin (TTX) and paralytic shellfish poison (PSP; decarbamoylsaxitoxin (dcSTX) or saxitoxin (STX)). T. pardalis specimens were administered feed homogenate containing TTX or dcSTX (dose of toxin, 55.2 nmol/fish) and P. suvattii specimens were administered feed homogenate containing TTX + STX (dose of each toxin, 19.2 nmol/fish) by oral gavage. The toxin content in the intestine, muscle, skin, liver, and gonads was quantified after 24 and 48 or 72 h. In T. pardalis, TTX administered into the intestine was absorbed into the body and transferred and retained mainly in the skin and liver, while dcSTX was hardly retained in the body, although it partly remained in the intestine. In strong contrast, in P. suvattii, little TTX remained in the body, whereas STX was absorbed into the body and was transferred and retained in the ovary and skin. The findings revealed that TTX/PSP selectivity differs between the marine species T. pardalis and the freshwater species P. suvattii. T. pardalis, which naturally harbors TTX, selectively accumulates TTX, and P. suvattii, which naturally harbors PSP, selectively accumulates PSP.
Flood Risk Assessment of Global Watersheds Based on Multiple Machine Learning Models
Authors: Li Xiangnan , Yan Denghua , Wang Kun , Weng Baisha , Qin Tianling , Liu Siyu
Published: August 2019

Machine learning algorithms are becoming more and more popular in natural disaster assessment. Although the technology has been tested in flood susceptibility analysis of several watersheds, research on global flood disaster risk assessment based on machine learning methods is still rare. Considering that the watershed is the basic unit of water management, the purpose of this study was to conduct a risk assessment of floods in the global fourth-level watersheds. Thirteen conditioning factors were selected, including: maximum daily precipitation, precipitation concentration degree, altitude, slope, relief degree of land surface, soil type, Manning coefficient, proportion of forest and shrubland, proportion of artificial surface, proportion of cropland, drainage density, population, and gross domestic product. Four machine learning algorithms were selected in this study: logistic regression, naive Bayes, AdaBoost, and random forest. The global susceptibility assessment model was constructed based on four machine learning algorithms, thirteen conditioning factors, and global flood inventories. The evaluation results of the model show that the random forest performed better in the test, and is an efficient and reliable tool in flood susceptibility assessment. Sensitivity analysis of the conditioning factors showed that precipitation concentration degree and Manning coefficient were the main factors affecting flood risk in the watersheds. The susceptibility map showed that fourth-level watersheds in the global high-risk area accounted for a large proportion of the total watersheds. With the increase of extreme hydrological events caused by climate change, global flood disasters are still one of the most threatening natural disasters. The global flood susceptibility map from this study can provide a reference for global flood management.
Scour at Bridge Foundations in Supercritical Flows: An Analysis of Knowledge Gaps
Authors: Link Oscar , Mignot Emmanuel , Roux Sebastien , Camenen Benoit , Escauriaza Cristián , Chauchat Julien , Brevis Wernher , Manfreda Salvatore
Published: August 2019

The scour at bridge foundations caused by supercritical flows is reviewed and knowledge gaps are analyzed focusing on the flow and scour patterns, available measuring techniques for the laboratory and field, and physical and advanced numerical modeling techniques. Evidence suggests that the scour depth caused by supercritical flows is much smaller than expected, by an order of magnitude compared to that found in subcritical flows, although the reasons for this behavior remain still unclear. Important questions on the interaction of the horseshoe vortex with the detached hydraulic-jump and the wall-jet flow observed in supercritical flows arise, e.g., does the interaction between the flow structures enhance or debilitate the bed shear stresses caused by the horseshoe vortex? What is the effect of the Froude number of the incoming flow on the flow structures around the foundation and on the scour process? Recommendations are provided to develop and adapt research methods used in the subcritical flow regime for the study of more challenging supercritical flow cases.
Quantifying Vertical Deformation in the Tigris–Euphrates Basin Due to the Groundwater Abstraction: Insights from GRACE and Sentinel-1 Satellites
Authors: Rateb Ashraf , Kuo Chung-Yen
Published: August 2019

This study explores the occurrences of land subsidence in response to dropping groundwater levels in the central part of the Tigris–Euphrates basin. We estimated the groundwater depletion related to human and climate drivers between 2003 and 2017 based on estimates from the Gravity Recovery and Climate Experiment (GRACE) and two global hydrological models (NOAH-3.3 and WGHM-2.2d). The cumulative displacement was calculated using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) for 96 interferograms, which were generated by 31 images acquired by the Sentinel-1 satellite. The results show that the basin is experiencing a decline in groundwater storage at a rate of −7.56 km3/year with a total loss of 106.81 km3. This depletion rate has led to inelastic compaction and has resulted in subsidence near the city of Baghdad at a rate of −10 mm/year. The measured coherence phase between the two signals is ~0.67, and the depletion precedes the subsidence by ~1.5 months. The new data from GRACE-Follow on, Sentinel-1, and the piezometric water level could help to constrain the rate of depletion and displacements in the basin. Combining these remote sensing techniques provides an independent tool for water management in areas where in-situ data are scarce.
Removal of Diesel Oil in Soil Microcosms and Implication for Geophysical Monitoring
Authors: Bosco Francesca , Casale Annalisa , Chiampo Fulvia , Godio Alberto
Published: August 2019

Bioremediation of soils polluted with diesel oil is one of the methods already applied on a large scale. However, several questions remain open surrounding the operative conditions and biological strategies to be adopted to optimize the removal efficiency. This study aimed to investigate the environmental factors that influence geophysical properties in soil polluted with diesel oils, in particular, during the biodegradation of this contaminant by an indigenous microbial population. With this aim, aerobic degradation was performed in soil column microcosms with a high concentration of diesel oil (75 g kg−1 of soil); the dielectric permittivity and electrical conductivity were measured. In one of the microcosms, the addition of glucose was also tested. Biostimulation was performed with a Mineral Salt Medium for Bacteria. The sensitivity of the dielectric permittivity versus temperature was analyzed. A theoretical approach was adopted to estimate the changes in the bulk dielectric permittivity of a mixture of sandy soil-water-oil-gas, according to the variations in the oil content. The sensitivity of the dielectric permittivity to the temperature effects was analyzed. The results show that (1) biostimulation can give good removal efficiency; (2) the addition of glucose as a primary carbon source does not improve the diesel oil removal; (3) a limited amount of diesel oil was removed by adsorption and volatilization effects; and (4) the diesel oil efficiency removal was in the order of 70% after 200 days, with different removal percentages for oil components; the best results were obtained for molecules with a low retention time. This study is preparatory to the adoption of geophysical methods to monitor the biological process on a larger scale. Altogether, these results will be useful to apply the process on a larger scale, where geophysical methods will be adopted for monitoring.
PECULIARITIES OF FORMING NERVO-MENTAL DISORDERS
AND VISUAL IMPAIRMENT AMONG MOSCOW STUDENTS DURING THE LEARNING
PROCESS AT SCHOOL
Authors: Rapoport I.K. , A.P. Tsameryan A.P.
Published: August 2019

The peculiarities of the forming the most common functional deviations and chronic diseases in students in the
school ontogenesis dynamics are revealed. The morbidity dynamics of functional disorders and chronic diseases
of the nervous system and mental sphere is presented. We analyzed changes in the prevalence of functional
visual impairment and chronic diseases of the visual analyzer. The course of the pathological processes after the
diagnosis of each student was evaluated according to the data of specially developed catamnesis questionnaires.
We found a high level of functional disorders’ occurrence frequency of the nervous system and mental sphere
(together) in primary school students and the rapid growth rate of the indicator from the 8th to the 11th forms.
Visual impairment is characterized by an increase in the prevalence and unfavorable course of pathological
processes during the whole school ontogenesis. The revealed functions of deviation and chronic diseases testify
to the negative role of excessive academic load of students, psycho-emotional and visual overstrain in the
formation of pathological conditions in school students.
FACTORS DETERMINING THE ROLE OF THE DOMESTIC CAT AS AN
ECOLOGICAL STALEMATE OF OPISTHORCHIASIS AGENT IN THE EPISOOTIC
PHASE OF THE LOIMOPROCESS OF INVASION
Authors: Ushakov A.V.
Published: August 2019

shows that the wild ancestors of this animal that lived in the desert did not participate in the evolution of the
parasitic system of the opisthorchiasis agent. Formation of complex life cycles of trematodes of the family Opisthorchidae
in the Cenozoic era occurred with the participation of representatives of mammals’different systematic
groups. The domestic cat on the territories of Eastern Europe and Western Siberia historically did not
participate in the formation of the parasitic system Opisthorchis felineus, because it appeared in these territories
much later, when the parasitic system of the agent existed there since the end of the Miocene. The main factors
that determined the role of the domestic cat as the definitive host and the ecological stalemate of the opisthorchiasis
agent were its interaction with the environment and the genetically determined animal’s behavior.
The study of new types of alumina with a view to their use for the manufacture of highrefractory highdensity corundum ceramics by slip casting
Authors: Martynenko V. V. , Primachenko V. V. , Kushchenko K. I. , Krakhmal Yu. A. , Mishnyova Yu. Ye. , Karyakina E. L.
Published: August 2019

It was established that the using of alumina A 16 SG and A 1000 SG brands in combination with dispersing additives, in particular with a carboxylic acid based additive, for production by slip casting into gypsum molds of qualitative highrefractory corundum highdensity ceramics with Al2O3 content — not less than 99.5 %, Fe2O3 — not more than 0.05 %, MgO — no more than 0.25 % and open porosity not more than 0.8 % after firing at 1580 °C are suitable.
Ceramic-matrix composite materials for the diamond abrasive tools manufacture
Authors: Fedorenko D. O. , Fedorovich V. A. , Fedorenko E. Yu. , Daineko K. B.
Published: August 2019

The results of the development of high-resource ceramic diamond abrasive tool, the design of which was carried out using computer simulation of processes, that accompanying its manufacturing and grinding in the mode of rational self-sharpening, is presented. According to the results of simulation experiments, the composition of the diamond-bearing layer was developed and the instrument with the use of a low-melting ceramic bond with the given properties were made.
Development of technical specifications and changes to the technical specifications on refractories by PJSC “THE URIR NAMED AFTER A. S. BEREZHOY” in 2016
Authors: Belyayeva L. V. , Kostyrko I. Yu. , Pakhomova T. F.
Published: August 2019

This article includes information about development of technical specifications (TS) and changes to the TSs for refractories by institute in 2016. In 2016 in accordance to the requirements of the state standardization system 10 TS and 14 changes to the current TS have been developed, agreed with the companies and approved, including 7 new TS and 6 change to TS for pilot batches of refractories manufactured by PJSC “THE URIR NAMED AFTER A. S. BEREZHOY”, 3 TS and 8 change to TS for serial refractory products, produced by Ukrainian enterprises. Institute plans to continue work on the development of TS for refractory products, study and analysis of the global level of standardization in the field of refractories.
Digital Control System for Solar Power plant using IoT
Authors:   ECE, Oriental University, Indore, India., Karbhari Ganesh V. , Nema Dr. Pragya ,   ECE, Oriental University, Indore, India.
Published: August 2019

The Internet of Things (IoT) or Web of Things (WoT) is a modern technology which is relating computing machines with digital and mechanical devices and various objects. Today energy crisis is one of the major issues in the world. To overcome this issue, different renewable energy sources are being used. Nowadays solar energy has become a best alternative resource for satisfying power demands. Selected Solar power plant for implementation is of 1 MW capacity and generating power of 1.5 Million units per year with the use of Poly crystalline type of solar panel technology. Currently this power plant is monitored by PLC. All records of energy can be monitored only at plant on SCADA Device. In this Proposed work, we develop a model of online solar power monitoring as well as controlling so authorized person can monitor or control panels remotely by home also. As per the change in the atmospheric or weather conditions, user can control the solar panels also.
Effect of Speed, Feed and Depth of Cut on Machining Induced Residual Stresses in Aisi 1045 Steel
Authors:   Mechanical Engineering Department, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India, D N V Padma Ooha , Marimuthu K Prakash ,   Mechanical Engineering Department, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India, M Thenarasu ,   Mechanical Engineering Department, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India
Published: August 2019

Residual stress that are induced during machining of components plays a significant part in the endurance and life of the component. The magnitude and nature of the residual stresses have been of interest to many researchers across the globe. The present work involves methodology to find out the influence of factors on the residual stresses. The machining parameters were varied and the residual stresses were determined using non-destructive method, namely X-ray diffraction. Using statistical methods, the influence of the machining parameters was ascertained. This paper aims at investigating the residual stresses in AISI 1045 steel, induced due to milling. AISI 1045 steel was considered as it is a widely used material and its applications are innumerable. It was observed that speed and feed have significant influence on stresses left behind after the machining is completed. Using statistical techniques a mathematical model was developed which is further used to predict the residual stresses. The error percentage of the predicted values was less than 5%. The results obtained were promising and future work involves the optimization of the machining parameters.
Open Digital Education Space: Classification of E-Services at University
Authors:   Minin Nizhny Novgorod State  Pedagogical University, Nizhny Novgorod, Russian Federation., Alexandrovich Fedorov Alexander , Galina Alexandrovna Paputkova ,   Minin Nizhny Novgorod State  Pedagogical University, Nizhny Novgorod, Russian Federation., Irina Fedorovna Filchenkova ,   Minin Nizhny Novgorod State  Pedagogical University, Nizhny Novgorod, Russian Federation, Elena Yuryevna Ilaltdinova ,   Minin Nizhny Novgorod State  Pedagogical University, Nizhny Novgorod, Russian Federation., Marina Igorevna Klyueva ,   Minin Nizhny Novgorod State  Pedagogical University, Nizhny Novgorod, Russian Federation.
Published: August 2019

The article suggests new approaches to describing digital education space. The differentiation of the concepts "digital pedagogy", "digital didactics" and "digital education" is carried out. The study of the problem of e-services typology has both practical importance for structuring a digital education space of the university and methodological, prognostic significance that allows the authors to solve the task of developing a fundamentally new type of educational e-services. In the typology of services, it is necessary to single out services of educational program management and services of the content management, for digital education space. The second group of services is classified by the authors on two bases: firstly, stages of the content acquisition and, secondly, the theory of multiple intelligence, which is interpreted in terms of "teacher intelligence", proposed by the authors
Satellite Image Compression using RICE Algorithm
Authors:   Satellite Image Compression using RICE algorithm, UG  student, ECE Department, BNM Institute of Technology, Karnataka, India, R Pooja , U Harshitha ,   Satellite Image Compression using RICE algorithm, UG  student, ECE Department, BNM Institute of Technology, Karnataka, India, S Supriya ,   Satellite Image Compression using RICE algorithm, UG  student, ECE Department, BNM Institute of Technology, Karnataka, India, Supriya R ,   Satellite Image Compression using RICE algorithm, UG  student, ECE Department, BNM Institute of Technology, Karnataka, India, Kulkarni Keerti ,   Satellite Image Compression using RICE algorithm,  Assistant Professor, ECE Department, BNM Institute of Technology, Karnataka, India
Published: August 2019

Processing of satellite images is time-intensive owing to the large surface of the earth and the necessity for high resolution. Compression algorithms are an active research topic since there is no single algorithm which can achieve the best compression at the highest speed. Different compression algorithms need to be explored to enhance the speed of the analysis. Here, a lossless compression scheme using RICE algorithm is implemented using Matlab and Verilog on a satellite image according to the CCSDS (Consultative Committee for Space Data Systems) recommendation. The RICE algorithm uses a set of variable length codes. The architecture comprises of a Pre-processor, Adaptive entropy coder, Postprocessor and an Inverse mapper. The design has been implemented using Xilinx
Back To Back Converter Based Real and Reactive Power Control with Constant Speed Operation of Dfigin Wind Mill
Authors:   aassistant professor in the department of  EEE at SSM Engineering college. (Tamil Nadu ) India, E Mr. D. Madeswaranm , Selvam Dr. P. ,   professor and headin the department of EEE at  Vinayaka Mission's kirupananda Variyar Engineering College. (Tamil  Nadu ) India
Published: August 2019

The DFIG turbine could be a variable speed turbine typically used in world wide. In present world, DFIG wind turbines basically create utilization of the innovation that created ten years back. In any case, it's found within the paper that there's confinements regular management technique. The DTC is taken once for the direct power management (DPC) of electrical drives. The direct power management is accomplished by selecting exchanging applicable exchanging table that is formed by viewing the reference and assessed estimations of real and reactive power. The device potential difference is evaluated in light weight of the dc interface voltage and also the exchanging conditions of the device. The spatial relation of voltage vectors or position of virtual motion square measure used to regulate the real and responsive power. The dynamic and responsive power is controlled by rotor voltage, that experiences consecutive voltage supply device and DC-connect voltage is to boot sorted stable. the standard management approach is contrasted and also the projected management methods for DFIG turbine management underneath each consistent and breezy breeze conditions. A MATLAB primarily based copy frame work was work to approve the viability of the projected strategy. The projected strategy waveforms of real power, receptive power, DC interface voltage and generator speed square measure contrasted and ancient technique. This paper demonstrates that underneath the DPC management strategies, a DFIG framework have a prevailing execution in numerous angles.
Video Enhancement using Histogram Equalization with JND Model
Authors:   Associate Professor EC Department KVGCE Sullia, DK., H.K Bhagya , N Keshaveni ,   Professor, EC department KVGCE Sullia, DK.
Published: August 2019

The paper presents degraded Video contrast enhancement. These videosare taken by camera phones because of the improper illumination or limitation of the capturing devices. The existing enhancement approach may either flop to produce good and distortionless Videos. They do not enhance every area of interest properly, especially in face regions. The paperpropose histogram equalization method (HE) manipulating thenoticeable in difference model of the visual system represented as in JND-HE. This will be performed for generic frame that is contrast enhancement. In addition, the said method,JND-HE method is clubbed with the exposer correctivemethod represented by JND-HE-EC for video enhancement of face region. The EC method is to adjust the illumination of the video frame in the face region and obtain suitable illumination in the background. The demonstration result shows that generic videos and faces shallproduce pleasantvideosother than existing techniques.
An Apriori Method for Topic Extraction from Text Files
Authors:   Department of CS & E, JSS Science and Technology University, Mysore, India, K M Anil Kumar , B Ajay ,   Department of CS & E, JSS Science and Technology University, Mysore, India., R Shashank ,   Department of CS & E, JSS Science and Technology University, Mysore, India, D A Amogha Subramanya ,   Department of CS & E, JSS Science and Technology University, Mysore, India.
Published: August 2019

In this data age peta-bytes of data is generated every day. One of the biggest challenge today is to convert this data into useful information, this is known as data mining. Important kinds of data include text-based data, audio-based data, image-based data, video-based data etc. An important challenge in mining useful information from text-based data source (text mining) is topic modeling which is to find out the topic the text is talking about. The solution to this problem finds application, in clustering files based on the topic, pre-processing method in information retrieval, ontology of medical record etc. A lot of research work has gone into this area of topic modeling, and many approaches have been formulated. Some of these approaches take into account the occurrence and frequency of occurrence of words/terms, these models come under the Bag Of Words(BOW) approach. Others take into account the underlying structure in the corpus of text used, Wikipedia category graph is an example of this approach. This paper, provides an unsupervised solution to the above problem by extracting keywords that represent the topic of the text document. In our approach, topic modeling is carried out with a hybrid model which makes use of WordNet and Wikipedia Corpus. Promising experimental results have been obtained for well- known news dataset (BBCNews) from our model. We present the experimental result for our proposed approach along with the results of others in the same domain and show that our approach provides better results.
Development and Analysis of Semi-Automatic Safety Inflation Bag
Authors:   Department of Mechanical Engineering, Sri Sairam  Engineering College, Chennai,India, Akil R. , Aswin R. V. ,   Department of Mechanical Engineering, Sri Sairam  Engineering College, Chennai,India, Prasanna V. ,   Department of Mechanical Engineering, Sri Sairam  Engineering College, Chennai,India, Mohanakrishnan G. ,   Department of Mechanical Engineering, Sri  Sairam Engineering College, Chennai,India, Ravinthiran A. ,   Department of Mechanical Engineering, Sri Sairam  Engineering College, Chennai,India
Published: August 2019

Various safety gears and techniques are available in cars but save for the helmet, not much of safety gears have been introduced for the bike riders. Bike riders indulge in fatal accidents during their rides and race riders in spite of wearing the best safety gears get injured severely with spinal cord and chest being most vulnerable during the impact. Daily riders or race riders, accidents are inevitable. It’s entirely upon us to equip ourselves with an additional safety gear for our own safety purposes. The project, safety inflation bag, provides the best solution to prevent injuries to spinal cord and chest. Here, a pneumatic actuator is used to inflate the air channels sewn inside the bag which provides protection for chest and spinal cord. This technique is implemented in a bag, as bag is most commonly used during bike rides. Be it for office goers or for riders on long trips, bag is necessary and fixating the safety gear inside the bag serves the rider than just for carrying items. It could save the life. It could prevent him from enduring critical injury to spinal cord or chest. During the time of impact, the pneumatic cylinder goes off, releasing the compressed air through the air channels pressed against chest and spinal cord thus inflating them at the right time to provide a solid balloon protection. This project could serve as the first step to a major safety innovation for bike riders.
Optimization of Four Stroke c.i. Engine Performance by using Statistical Techniques (Mathematical Method)
Authors:   Assistant Professor, Mechanical Department, Indira Institute of Engineering and Technology, Pandur, Thiruvallur, Tamil Nadu, India., Vignesh Mr.P. , Madan Mr.P. ,   PG Scholar, Mechanical Department, Bharath Institute of Higher Education and Research, Tambaram, Chennai, Tamil Nadu, India., Kumar Mr.D.Mohan ,   Assistant Professor Automobile Department, Bharath Institute of Higher Education and Research, Tambaram, Chennai, Tamil Nadu, India., Chandran Dr.Naveen ,   Professor & Head of Department, Automobile Department, Bharath Institute of Higher Education and Research, Tambaram, Chennai, Tamil Nadu, India.
Published: August 2019

The concern for a clean environment, high oil prices and strict emission standards in research was the driving force behind the internal combustion engine. Popular direct injection engine nutrition with its compact size, low fuel consumption and low emission level. Here is the mathematically using the various statistical methods.
STCLARanS: An Improved Clustering Large Applications based on Randomized Search Algorithm using Slim-tree Technique
Authors:   Associate Professor III and designated as the Dean of the College of Computing Studies, Philippines., Camungao Ricardo Q.
Published: August 2019

Clustering has been used for data interpretation when dealing with large database in the fields of medicines, business, engineering etc. for the recent years. Its existence paved way on the development of data mining techniques like CLARANS (Clustering Large Applications based on Randomized Search) Algorithm. It is the most efficient k-medoids technique that uses randomized strategy to identify the best medoids in a large dataset. Likewise, it surpasses the clustering performance of both PAM (Partitioning Around Medoids) and CLARA (Clustering Large Applications) in terms of time. This paper addresses the task of integrating Slim-tree method to CLARANS for the development of the proposed Slim-tree Clustering Large Applications based on Randomized Search (STCLARanS) Algorithm and an experimental evaluation was prepared using synthetic and real datasets for the comparison of the quality of the clustered output of the CLARANS and the proposed STCLARanS algorithms. The Slim-tree method is used for pre-clustering of the objects in the dataset in identifying the objects in the middle level as the sample objects used to start the clustering process. The proposed Algorithm assumes that with the new sampling strategy to draw the initial cluster centers to start the clustering process may yield to better quality of the clustered outputs as compared to the clustered output of the CLARANS algorithm. The quality of the clustered output is measured on the accumulated distances of the objects to their cluster centers.
COALESCENCE: An Android-Based Instructional Application with Augmented Reality for Chemistry Students
Authors:   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines, Asuncion Maria Elora , Castromero Daryll ,   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines, Medrana John Jericho ,   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines, Parin Julian Aldrin ,   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines., Sales Calvin Jazer ,   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines, Constante Raymund ,   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines, Aquines Herchel ,   COECSA-DCS, Lyceum of the Philippines University – Cavite, General Trias, Cavite, Philippines
Published: August 2019

COALESCENCE is intended to let the Chemistry students learn and for Chemistry Teachers to use as a tool in teaching the subject. This application uses Augmented Reality to present information and 3D models of laboratory equipment, periodic elements, compound elements, and planet elements. Trivia and interactive quizzes are also provided to assess the user’s knowledge. Iterative Model was applied in project development. This application was created using Photoshop, Unity 3D, Blender, and Maya. In using the application, the minimum Android OS requirement is Android 6.0 (Marshmallow) and above. The test instruments used were Functionality, Compatibility, and Conformance test aligned with Android Core App Quality Standards. It got a 100% rating for the three test instruments’ used. In evaluation, Mobile Application Rating Scale was utilized with an average mean of “3.44”, the standard deviation of “0.17” and an interpretation with a “Highly Acceptable” feedback from the evaluators in all aspect of the application.
Deep Learning-based Facial Expression Recognition and Analysis for Filipino Gamers
Authors:   Electronics and Communications Engineering Department, De La Salle University, Manila, Philippines., Sena Juan Raphael , Cabatuan Melvin ,   Electronics and Communications Engineering Department, De La Salle University, Manila, Philippines.
Published: August 2019

This paper presents a computer vision based emotion recognition system for the identification of six basic emotions among Filipino Gamers using deep learning techniques. In particular, the proposed system utilized deep learning through the Inception Network and Long-Short Term Memory (LSTM). The researchers gathered a database for Filipino Facial Expressions consisting of 74 gamers for the training data and 4 gamer subjects for the testing data. The system was able to produce a maximum categorical validation accuracy of .9983 and a test accuracy of .9940 for the six basic emotions using the Filipino database. The cross-database analysis results using the well-known Cohn -Kanade+ database showed that the proposed Inception-LSTM system has accuracy on a par with the current existing systems. The results demonstrated the feasibility of the proposed system and showed sample computations of empathy and engagement based on the six basic emotions as a proof of concept.
Fruit Grading of Garcinia Binucao (Batuan) using Image Processing
Authors:   College of Engineering and Architecture, University of Antique, Philippines., Militante Sammy V.
Published: August 2019

Digital image processing, along with computer vision techniques, can be applied for automatic gradation of batuan fruits based on the quality of the fruit. It can increase the commercial value of the production. This paper presents an automated approach for fruit grading of Batuan fruits. First, it detects the batuan fruit and then after detection, it classifies the grade of the batuan fruit - Immature (light green), Mature (green) or Ripe (yellow). For gradation, we have used the color features and area of the fruit. The average accuracy for batuan fruit grading is up to 98%.
Analyzing the Students Behavior with Down Syndrome in a Gamified Learning Environment
Authors:   ITCS Department, Data Center College of the Philippines Incorporated, Baguio City, Philippines, Arenas Marvin R. , Dela Cruz Josephine S. ,   IT Department, University of the Cordilleras, Baguio City, Philippines
Published: August 2019

The main purpose of this study was to analyze the behavior of students with Down syndrome in a gamified learning environment of SPED school in Baguio City, Philippines. Education focused in the area which uses unique instructional methods, materials, learning aids, and toolkit to meet the educational needs of students with learning incapacities. This study investigated the extent to which a sample of special education teachers addressed various topical issues with students who have learning disabilities and behavior disorders. In collecting data, a survey instrument was employed to gather information pertaining to topical issues that involve sensitive subjects typically not addressed in the traditional academic curriculum in school. The authors also utilized literary studies, and observation, draws together the findings from a series of interviews, and applies these in an educational context. The data were analyzed with psychological, educational, and socio-cultural approaches, with qualitative descriptive analysis. Down syndrome (DS) is the most common genetic cause of intellectual disability worldwide, with language being one of the most affected area. The authors hypothesized factors that contribute to engagement with a learning activity and strategies and provide an example of the use of these factors in practice, and other hypotheses were supported by data. Based on the rating, the authors motivated to enhance the functionality of the Gamified Learning Environment (GLE) in the future. The target user strongly agrees with the ratio of 4.6 which means that the GLE has the functionality needed in their school course and has a greater impact to their academic performance.
Identifying Faulty Nodes in Wireless Sensor Network to Enhance Reliability
Authors:   Department of Computer science, Amrita School of Arts and Sciences, Mysuru, Amrita Vishwa Vidyapeetham, India, Prabhan Arun P , Anand Santosh ,   Department of Computer science, Amrita School of Arts and Sciences, Mysuru, Amrita Vishwa Vidyapeetham, India, Sinha Somnath ,   Department of Computer science, Amrita School of Arts and Sciences, Mysuru, Amrita Vishwa Vidyapeetham, India
Published: August 2019

WSN having several major issues to deliver information from source to sink. Such that secure data transmission, energy consumption, balancing the load and fault tolerance will be the major tasks. In the WSN, one node communicates with its neighbour nodes with limited energy source. So if any node does not work properly or become faulty nodes, which have less initial energy level, bandwidth to communicate with faulty nodes. Hence there is a need of system which can overcome with fault and give the reliable communication. Fault may also occur due to the dislocation of sensor nodes, battery depletion or instability of transmission medium.This proposed work will identify the faulty nodes and calculate the end to end delay as well as residual energy. Hence a reliable communication for all nodes in the WSN can be attained.
Low Glitch & Low Power Dual Edge Triggered D-Type Flip Flops for Integrated Applications
Authors:   Dept. of Electronics & Instrumentation, Shri G.S. Institute of Technology & Science, Indore (M.P), India, Pandey Viresh , Jain Pramod Kumar ,   Dept. of Electronics & Instrumentation, Shri G.S. Institute of Technology & Science, Indore (M.P), India, Ajnar Devendra Singh ,   Dept. of Electronics & Instrumentation, Shri G.S. Institute of Technology & Science, Indore (M.P), India
Published: August 2019

This paper presents Dual Edge Triggered (DET) master slave D-Type flip flops for glitch free, low power, low delay, low silicon area and low Power Delay Product (PDP). This DET master slave D-Type flip flops are compared against the existing DET flip flops using 45nm & 180nm CMOS technology which has been simulated using Cadence Virtuoso. The proposed DET master slave D-Type flip flops has reduced the number of transistors in use for operation, which leads to low glitch, low power and low delay design. Paper consist glitch free DET master slave D-Type flip flops analysis for power, delay and PDP. The proposed DET flip flop is also simulated and implemented for 18nm Fin-FET in Cadence Tool.