bluuebunny/crossref_metadata_2025 huggingface dataset:
Oxidative Stress‐Related Mechanisms in Schizophrenia Pathogenesis and New Treatment Perspectives
Authors: Ermakov Evgeny A. , Dmitrieva Elena M. , Parshukova Daria A. , Kazantseva Daria V. , Vasilieva Alisa R. , Smirnova Liudmila P.
Published: January 2021

Schizophrenia is recognized to be a highly heterogeneous disease at various levels, from genetics to clinical manifestations and treatment sensitivity. This heterogeneity is also reflected in the variety of oxidative stress‐related mechanisms contributing to the phenotypic realization and manifestation of schizophrenia. At the molecular level, these mechanisms are supposed to include genetic causes that increase the susceptibility of individuals to oxidative stress and lead to gene expression dysregulation caused by abnormal regulation of redox‐sensitive transcriptional factors, noncoding RNAs, and epigenetic mechanisms favored by environmental insults. These changes form the basis of the prooxidant state and lead to altered redox signaling related to glutathione deficiency and impaired expression and function of redox‐sensitive transcriptional factors (Nrf2, NF‐κB, FoxO, etc.). At the cellular level, these changes lead to mitochondrial dysfunction and metabolic abnormalities that contribute to aberrant neuronal development, abnormal myelination, neurotransmitter anomalies, and dysfunction of parvalbumin‐positive interneurons. Immune dysfunction also contributes to redox imbalance. At the whole‐organism level, all these mechanisms ultimately contribute to the manifestation and development of schizophrenia. In this review, we consider oxidative stress‐related mechanisms and new treatment perspectives associated with the correction of redox imbalance in schizophrenia. We suggest that not only antioxidants but also redox‐regulated transcription factor‐targeting drugs (including Nrf2 and FoxO activators or NF‐κB inhibitors) have great promise in schizophrenia. But it is necessary to develop the stratification criteria of schizophrenia patients based on oxidative stress‐related markers for the administration of redox‐correcting treatment.
Application of Histogram Equalization for Image Enhancement in Corrosion Areas
Authors: Xiong Jianbin , Yu Dezheng , Wang Qi , Shu Lei , Cen Jian , Liang Qiong , Chen Huanyang , Sun Baocheng
Published: January 2021

In this paper, an image enhancement algorithm is presented for identification of corrosion areas and dealing with low contrast present in shadow areas of an image. This algorithm uses histogram equalization processing under the hue‐saturation‐intensity model. First of all, an etched image is transformed from red‐green‐blue color space to hue‐saturation‐intensity color space, and only the luminance component is enhanced. Then, part of the enhanced image is combined with the original tone component, followed by saturation and conversion to red‐green‐blue color space to obtain the enhanced corrosion image. Experimental results show that the proposed method significantly improves overall brightness, increases contrast details in shadow areas, and strengthens identification of corrosion areas in the image.
Parameters Optimization and Energy Absorption Evaluation of the Steel Ball Friction Energy Absorber
Authors: Gong Bin
Published: January 2021

The energy absorber is used to simulate the reaction of a working piece subjected to a vibration stimulus, by which the consistent and repeatable reactions to the tool’s vibration inputs could be achieved. According to the proposed coupling simulation model by using commercial software RecurDyn and EDEM, the energy dissipated by the energy absorber and the contact force between the drill rod and the piston are evaluated under different load conditions such as the impact frequency and impact stroke. Moreover, the effects of the ball diameter, ball column height, and diameter on the energy absorption characteristics are also studied. The results show that the impact frequency and stroke influence the energy absorber by changing the impact force; the energy absorption is more obvious under higher impact frequency and long impact stroke. The filling ball diameter influences the energy reflectivity by changing the porosity, which is negatively correlated to the energy reflectivity, and a 6 mm filling ball diameter is suggested. The energy reflectivity is inversely proportional to the ball column height and diameter, and the suggested ball column diameter and height are 160 mm and 600 mm, respectively, with energy reflectivity of 0.045. Even when the increase in impact frequency and stroke will increase the contact force, the dynamic load factor decreases. The contact force and dynamic load factor are inversely proportional to the ball column height, but they are not influenced by the ball diameter and the ball column diameter.
Analysis of Tear Ferning Patterns in Young Female Subjects with Refractive Errors
Authors: Alanazi Mana A. , El-Hiti Gamal A. , Al-Madani Alaa , Fagehi Raied
Published: January 2021

To evaluate the dry eye symptoms and ocular tear film in young female subjects with refractive errors (RE) using the ocular surface disease index (OSDI), phenol red thread (PRT) and tear ferning (TF) tests. Methods. A group of 50 young female subjects (mean ± standard division = 20.3 ± 1.1 years) with RE (−0.25 to −6.00D) completed the study. An age-matched control group consisting of 50 healthy normal eye female subjects (22.2 ± 1.5 years) was recruited for comparison. The OSDI was completed first, followed by PRT and TF tests. Results. Median OSDI and TF scores were significantly higher (Mann–Whitney test;

P
<
0.001

) among the study group subjects [median (interquartile range (IQR)) = 13.5 (15.3) and 1.6 (1.3), respectively] compared to the control group [6.0 (4.0) and 0.9 (0.8), respectively], whereas the median PRT score was significantly lower (Mann–Whitney test;

P
=
0.003

) in the study group [(27.5 (6.3) mm] compared to the control group [29.5 (5.0) mm]. For subjects within the mild RE group (N = 30), significant differences (Mann–Whitney test,

P
<
0.001

to 0.005) were found between the median OSDI, PRT, and TF scores and those recorded within the control group. For the subjects with moderate RE (N = 20), significant differences (Mann–Whitney test,

P
<
0.001

to 0.002) were found between the median OSDI and TF scores, and those recorded within the control group. Conclusion. The presence of RE in young females has a negative effect on tear film in terms of dry eye symptoms, tear volume, and TF grades. Dry eye symptoms experienced by subjects with RE and the TF grades were significantly higher compared with the control group. In addition, the tear volume was significantly lower in the study group. Clearly, RE has a risk factor for dry eye.
A Generalization of Spatial Monte Carlo Integration
Authors: Yasuda Muneki , Uchizawa Kei
Published: January 2021

Spatial Monte Carlo integration (SMCI) is an extension of standard Monte Carlo integration and can approximate expectations on Markov random fields with high accuracy. SMCI was applied to pairwise Boltzmann machine (PBM) learning, achieving superior results over those of some existing methods. The approximation level of SMCI can be altered, and it was proved that a higher-order approximation of SMCI is statistically more accurate than a lower-order approximation. However, SMCI as proposed in previous studies suffers from a limitation that prevents the application of a higher-order method to dense systems. This study makes two contributions. First, a generalization of SMCI (called generalized SMCI (GSMCI)) is proposed, which allows a relaxation of the above-mentioned limitation; moreover, a statistical accuracy bound of GSMCI is proved. Second, a new PBM learning method based on SMCI is proposed, which is obtained by combining SMCI and persistent contrastive divergence. The proposed learning method significantly improves learning accuracy.
Annotated List of Orchidaceae for Myanmar
Authors: ORMEROD PAUL , KURZWEIL HUBERT , WATTHANA SANTI
Published: January 2021

A list of all Orchidaceae recorded for Myanmar is presented, primarily based on many years of research in herbaria and libraries around the world, supplemented by recent fieldwork in various parts of Myanmar. As such, it is intended to form the basis for a treatment of Orchidaceae in the new flora of Myanmar project. A total of 1037 species in 152 genera is listed, which includes a number of uncertain identifications and indicates the need for further research. In addition, for four taxa occurrence in Myanmar is also suspected, but the available herbarium and literature information is not conclusive in this regard. The total number is comparatively low relative to neighbouring Thailand but expected to rise, given the fact that biodiversity is currently poorly understood even though extensive inventory efforts are now under way. In the introduction, the orchid flora of Myanmar, phytogeographical affinities and endemism are discussed and illustrated by graphs and tables. Each species entry in the taxonomic section consists of the name, place of original description, type information (if from Myanmar), list of citations of Myanmar specimens examined and global distribution; specific notes under many species elaborate various taxonomic issues. Two new combinations are made here, and five lectotypes and one neotype are designated. Six species are definite new distribution records for Myanmar, whereas identification of another three needs to be confirmed.
First record of the rare stenopodidean shrimp Odontozona spongicola (Alcock & Anderson, 1899) (Decapoda: Stenopodidea: Stenopodidae) from Indonesia
Authors: CHEN CHIEN-LIN , CHAN TIN-YAM
Published: January 2021

The stenopodidean shrimp Odontozona spongicola (Alcock & Anderson, 1899) collected by the South Java Deep-Sea Biodiversity Expedition 2018 (SJADES 2018) is a new record from Indonesia. The specimen of O. spongicola recently listed from the South China Sea is also formally reported here in. The characteristcs and coloration of this rare species are described and illustrated.
Contribution to the knowledge of Dialeurodes (Gigaleurodes) Quaintance & Baker (Hemiptera: Aleyrodidae), with description of a new species from China
Authors: WANG JI-RUI , DU YU-ZHOU , XU ZHI-HONG , ZHOU GUO-XIN
Published: January 2021

A new whitefly species, Dialeurodes (Gigaleurodes) parakmeriae Wang sp. nov., collected on Parakmeria sp. (Magnoliales: Magnoliaceae) in Shuangxikou (Zhejiang, China) is described using morphology, line illustrations, photographs and scanning electron microscope (SEM) images. In addition, Dialeurodes (Gigaleurodes) maxima Quaintance & Baker, is reported as new to the fauna of China. An identification key to Chinese Dialeurodes (Gigaleurodes) species is provided. The holotype is deposited in the Insect Collection of Zhejiang Agriculture & Forestry University (ZAFU).
The Influence and Mechanism of Paeoniflorin and Albiflorin on Strychnine and Brucine Transport Through Madin-Darby Canine Kidney/Multidrug Resistance1 Cells In Vitro Model
Authors: Liu Yun-Feng , Guan Yong-Mei , Huang Shi-Yu , Wu Lu , Zhu Wei-Feng , Chen Li-Hua
Published: January 2021

This research sought to study the influence and potentialmechanism of paeoniflorin and albiflorin on strychnine and brucine transport in MDCK-MDR1 cells regulated by P-gp. Cytotoxicity of drugs was tested by MTT assay, and the transport studies were performed in both directions in MDCK-MDR1
cells. The influence of drugs on P-gp ATPase, and the efflux function of P-gp, the expression levels of P-gp and MDR1 mRNA were also estimated. Strychnine and brucine showed well absorption, and the main transport mechanism might be passive diffusion. Verapamil could significantly decrease
the efflux rate (ER) of strychnine and brucine, while the ER of strychnine and brucine was increased significantly when co-administrated with paeoniflorin or albiflorin, indicating that paeoniflorin and albiflorin could promote the efflux of these two alkaloids. Strychnine and brucine could
activate the activity of P-gp ATPase, suppress the efflux function of P-gp, but have no significant effect on the expression of P-gp. In addition, strychnine could upregulate the expression of MDR1 mRNA. Paeoniflorin and albiflorin could increase the transmembrane transport of strychnine and
brucine mediated by P-gp when co-administrated with strychnine or brucine via stimulating the activity of P-gp ATPase, enhancing the efflux function of P-g, increasing the expression levels of MDR1 mRNA and P-gp.
Study on the Establishment of a Rapid Propagation System for Succulent Plant Haworthia heidelbergensis
Authors: Cen Zhongyong , Su Jiang , Tu Hongrun , Lin Shiting
Published: January 2021

This study took the inflorescence and leaves of the succulent plant Haworthia heidelbergensis as explants, and explored the effects of different mediums with different hormone ratios on the rapid propagation of Haworthia heidelbergensis. The results showed that the optimal
medium component for inflorescence callus induction was MS (Murashige and Skoog)+2.0 mg/L 6-BA+1.0 mg/L 2,4-D+0.2 mg/L NAA, the callus induction rate was 90%; the optimal medium component for leaf callus induction was MS+0.5 mg/L 6-BA+2.0 mg/L KT+0.3 mg/L NAA; the optimal medium for callus
differentiation was MS+1.0 mg/L 6-BA+2.0 mg/L KT+0.3 mg/L NAA, the clump bud differentiation rate was 50%; the optimal medium for clump bud proliferation was MS+0.5 mg/L 6-BA+1.0 mg/L KT+0.05 mg/L NAA, the proliferation rate was 600%; the best medium for rooting was 1/2 MS+ 0.2 mg/L NAA+0.3
g/L AC. In conclusion, this study selected the explants and culture mediums, established an aseptic propagation system and provided a reference for the in vitro culture and rapid propagation of Haworthia heidelbergensis.
Regulation of Ethyl Carbamate of Saccharomyces cerevisiae in Chinese Luzhou-Flavor Liquor Fermentation
Authors: Wang Chuan , Zhang Meng-Ping , Wang Mou
Published: January 2021

The carcinogen ethyl carbamate (EC) in alcoholic beverages mainly comes from the spontaneous reaction of ethanol and urea, and urea is produced by the breakdown of arginine by arginase in Saccharomyces cerevisiae. Regulating activity of arginase and decreasing urea content are
beneficial to reduce EC in liquor. In this study, Saccharomyces cerevisiae isolated from Daqu was fermented under a series of stress conditions to evaluate the content changes of EC and its precursors. Temperature and pH below 25 °C and pH 4.0, ethanol concentration of 4–6%
and a certain initial salt concentration could reduce arginine consumption and urea production by decreasing transcription level of arginase and increasing transcription level of urea carboxylase, and eventually lead to the reduction of EC. These methods will help to improve the strategy of
EC control in Chinese liquor.
Compound Luolong Jiangu Capsule Protects Glucocorticoids Induced Osteoporosis Through the Nrf-2/HO-1/NF-κB Pathway
Authors: Zhao Tianyi , Wang Renguang , Zheng Shujing , Pil Park Jong , Wang Shumin , Leng Xiangyang
Published: January 2021

Compound Luolong Jiangu Capsule (CLJC) is a classic traditional Chinese medicine prescription for patients with osteoporosis. This study explored the potential mechanisms of the protective effects of CLJC on glucocorticoid-induced osteoporosis in rats. After oral administration of CLJC
for 8 weeks, osteoporosis was induced in the rats by dexamethasone treatment for twice a week. The expression levels of HP, ALP, TRAP, IL-6, TNF-α and IL-1β in bone samples as well as the concentrations of MDA and SOD in serum samples were determined using ELISA reagent
kits. Besides, Western blotting was used to assess the expression levels of proteins involved in NF-κB/Nrf-2/HO-1 pathway. Our results showed that oral CLJC noticeably reduced the pathological damage of glucocorticoidinduced osteoporosis, decreased oxidative stress and suppressed
the expression of inflammatory cytokines in bone and serum samples. It was also observed that oral administration of CLJC significantly suppressed the protein expression of Nrf-2, HO-1, p65/p-p65 and IkBa/p-IkBa. In conclusion, CLJC can play a protective role in glucocorticoid-induced osteoporosis
by enhancing the antioxidant system and reducing inflammatory responses.
Beauvericin Inhibits the Growth of U251 Glioma Cells and Promotes Apoptosis In Vitro
Authors: Hu Liming , Zhao Tianyi , Wang Jia , Wang Renguang , Bu Hongshi , Zheng Shujing , Li Yang , Liu Junze , Wang Shumin
Published: January 2021

To elucidated the inhibitory effect of beauvericin (BEA) on glioma cells and its possible molecular mechanism, in this study, the MTT assay was performed to observed the effect of BEA on cell proliferation, the flow cytometry was used to measure its protective effect on cell apoptosis,
and the Western Blot assay was performed to test the expression levels of signal transduction proteins. In the results, the concentration of BEA was 0.5 μmoL/L in the drug group, indicating that it has obvious protect effect to the U251 cells. The apoptosis rates of BEA, Cis and
BEA+Cis groups, compared with the U251 group, were 2.93, 3.71 and 5.0 times higher respectively. In addition, the expression levels of Cyclin D1, E, B and Bcl-2 in BEA group were 75, 69, 78 and 67% of that in the U251 group, while Bax and cleaved caspase-3 were twice as much as that in the
U251 group. In conclusion, beauvericin can inhibit U251 cell apoptosis and the possible mechanism is to reduce the expression of Cyclin D1, B, E and Bcl-2, while the levels of Bax and cleaved Caspase-3 increased. Thus, BEA has a broad application prospect in the treatment of glioma.
Niacin Metal-Organic Framework-Laden Self-Healing Hydrogel for Wound Healing
Authors: Deng Youming , Hu Jie , Qu Zhan , Tao Ran , Wang Gefei , Liu Weidong
Published: January 2021

Bacterial infection is one of the most significant impediments to wound healing. To treat wounds, non-biological and non-pharmacological interventions have gained increasing importance as they are easily translatable into clinical products. In this study, we developed a niacin metal-organic
frameworks (NOFs)-laden hybrid hydrogel with self-healing ability for better wound healing. The copper based-NOFs (Cu-NOFs) and zinc based-NOFs (Zn-NOFs) were constructed and encapsulated into the self-healing hydrogels, which could prevent NOFs from directly interacting with protein-containing
solutions (e. g., tissue fluid). The hydrogel was prepared by using four-armed benzaldehyde-terminated polyethylene glycol (BAPEG) and carboxymethyl chitosan (CMC). Our results showed that the hydrogel gained self-healing ability through reversible Schiff base reaction. In addition, after
loading NOFs, the hybrid hydrogel exerted significant effects on antibacterial and antioxidant activities. The in vivo studies demonstrated that the hybrid hydrogel could alleviate inflammation and enhance the formation of granulation tissue, collagen and vascular tissue, thereby promoting
wound closure in rats with E. coli -infected wounds. Overall, this study highlights the tremendous potential for the clinical implementation of NOFs-laden hydrogel with good self-healing, antibacterial and antioxidant properties in wound healing.
Synthesis of Nanocomposites Layered Double Hydroxide via Ocimum basilicum and Its Acaricidal Efficacy Against Multi-Resistance Rhipicephalus annulatus Tick
Authors: Aboelhadid Shawky M. , Mahran Hesham Abdo , El-Ela Fatma Abo I. , Shokeir Kalid M. , Henedy Khaled Hussien , Gadelhaq Sahar Mohamed , Mahmoud Ahmed A. , Abdel-Baki Abdel-Azeem S. , Al-Quraishy Saleh , Abdel-Tawab Heba
Published: January 2021

A layered double hydroxide (LDH) incorporated with Ocimum basilicum essential oil (OB) was prepared and its acaricide efficacy against Rhipicephalus annulatus tick was investigated. The OB essential oil was extracted from plants farmed in the study area. Zn–Al LDH/Gallate was
prepared by co-precipitation method then OB oil was added to obtain OB/LDH nano-composite. The obtained product was characterized by X-Ray Diffraction (XRD), Fourier-transform infrared (FT-IR) and scanning electron microscopy (SEM). The acaricidal activity of different concentrations of the
obtained OB/LDH nanocomposite (6.25, 12.5, 25, 50, 100, 200 and 300 l/mL) was evaluated via the adult immersion test (AIT), egg hatchability test (EHT), larval packet test (LPT) and repellency test. OB oil and OB/LDH nano-composite showed 100% adult mortality and prevent egg deposition at
a dose of 300 l/mL. Also, eggs hatching was fully inhibited at 300 l/mL while at the concentration of 200 l/mL the inhibition rate was 95%. In LPT, OB/LDH showed a high toxicological effect which leading to 100% and 43% larval mortality at doses of 200 μ l/mL and 100 μl/mL, respectively.
Meanwhile OB alone showed 100% and 45% larval mortality at doses of 300 μl/mL and 200 μl/mL, respectively. The LC50, LC90 and LC99 values of OB/LDH and OB were found to be 107.46 versus 209.908 μl/mL, 171.22 versus 282.63 μl/mL and 196.15 versus
298.26 μl/mL, respectively. The repellence activity was lasted for 3 h after application against larvae. OB/LDH was found to be more repellent than OB as evidenced by the RC50 values after 2 h and 3 h (48.82 vs. 79.99 μl/mL and 89.47 vs. 185.32μ l/mL, respectively). Overall,
our results proved that LDH enhanced the larvaicidal and repellent efficacy of OB against R. annulatus tick larvae.
Adaptive Visual Learning Using Augmented Reality and Machine Learning Techniques
Authors: Ghana Satyajit , Singh Shikhar , Jalali Aryan , Badani Vivek , Shankar Sahana P.
Published: January 2021

The current curriculum forces students to understand topics by visualizing axonometric structures in their cognitive minds depending upon the conceptual texts and information. This methodology is inconsistent as the idea of visualization through conceptual knowledge is dependent on
the level of reasoning and IQ (Intelligence Quotient) a student possesses. It is usually common for a student to misinterpret an information due to lack of reasoning and imaginative skills. Our educational model aims to diminish this intellectual barrier by incorporating Augmented Reality
(AR) and Machine Learning (ML) techniques together and create an Adaptive Visual Learning experience for students. A mobile interface with OCR (Optical Character Recognition) and TTS (Text-To-Speech) feature is given to make this whole process simple and easy to use for any student. In this
paper, two ML techniques Logistic Regression and Neural Network are applied in order to enhance and modify the existing educational system by removing the intellectual barrier involved due to neurodiversity. A comparative study is performed between the two ML algorithms, where in Logistic
Regression performed better than the Neural Network. This form of adaptive visual learning aims to boost student performance in academia.
A Study on Brain Tumour Detection Using Image Processing
Authors: Divya D. J. , Prakasha S.
Published: January 2021

Worldwide, people are getting affected from Brain Tumour. It is not only limited to aged people but also affects younger people. Brain Tumour is created due to the abnormal growth of cell inside the brain cranium results in limited functioning of brain. Early detection of this disease
is possible because of advancement of image processing techniques. Imaging tumours with better accuracy plays significant role in diagnosis of the tumours. The existing diagnosis techniques include MRI, CT, PT etc. For studying the body’s intuitive structures. Magnetic Resonance Imaging
(MRI) which is a non-invasive technique is an useful option as it gives better quality brain images and cancerous tissues compared to Computed Tomography (CT). The steps used for image processing are image acquisition (capturing image), pre-processing which involves activities like scaling,
filtering, highlighting certain features, image enhancement, segmentation, image compression, image restoration, identification and labelling. In this work, a study has been carried out to compare the performance of various algorithms used in image processing.
Review on Anomaly Detection in Mobile Networks Using Traditional Learning, Machine Learning and Deep Learning
Authors: Prabhakar T. S. , Veena M. N.
Published: January 2021

Increasing usage of smart phones involves in the developing large amount of data and high speed internet is used for transfers this large amount of data. This in-turn gives rise to the development of various attacks to hack the data. Anomaly detection in the network analyzes the pattern
in the network activity and found the abnormality in the network. The accurate detection of abnormality in network helps to prevent the attackers to steal the data. Many researches were conducted to improve the performance of anomaly detection in the mobile networks. Traditional methods results
for performance of anomaly detection are not much effective. Machine learning techniques are used for the anomaly detection to increase the performance. The deep learning techniques are applied to increase the detection rate and decrease the false positive. Both the techniques machine learning
uses k-means and Deep learning uses Artificial Neural Network method provides the considerable performance in anomaly detection.
Milk Adulteration and Detection
Authors: Rani K. Sudha , Amulya G. Sai Sundara , Kumari K. Mani , Shobana D. V. S. , Nireekshana T. , Santosh M. V. Arun , Chandra K. Vijaya
Published: January 2021

Milk adulteration is a worldwide apprehension that adversely affects progressing countries like India. Milk is a healthy drink that consists of several macro and micro nutrients which offer gamut of health benefits and is consumed by people of all age groups. Addition of extraneous
matter like starch, sugar, caustic soda, ammonia refined vegetable oil, common detergent etc into the milk lowers its nutritious value there by posing risk to health. Hence it is very important to test the purity of milk before consumption as synthetic milk and pure milk more or less look
the same and have a same taste. This paper describes a detection system that consumes less time to determine the parameters like Nacl, urea, pH and water percentage contained in the milk with the help of sensors incorporated in the system.
Business Tax Monitoring Analysis with Goods Services and Tax, Tax and Amount Tracking System Using Block Chain System
Authors: Ponraj Anitha , Gupta D. Vishnu Vardhan , Reddy D. Sai Kumar , Canessane R. Aroul , Roobini M. S.
Published: January 2021

There is no automatic process in identifying the misbehaving activities in the Tax payment as well as GST bill payment system. In the proposed framework is to devise a strategy that distinguishes gatherings of individuals who submit avoidance in the products and enterprises charge by
controlling their deals as well as buys with the inspiration to lessen their duty obligation. Specifically, we perform bunching investigation on certain delicate parameters relating to every one of the sellers. At that point by breaking down the quantity of vendors over the various bunches,
we distinguished the suspicious arrangement of sellers who are additionally examined by taking a gander at other delicate parameters. In the modification process. Values of the rupee are linked with the currency number which is implicitly linked with the Expiry date which is not notified to
any of the users. So, vendors while receiving the money need to update in the shop server which is directly communicates to the taxing server, which is automatically updated in their account. We implement this Process securely using Block chain Technology.
Object Detection for Blind People Using Faster Region-Based Convolutional Neural Networks
Authors: Devahema D. , Shyaam S. M. K. , Karthikeyan M. , Vishal V. S. , Pushpak G.
Published: January 2021

Age is not just a number as human body also ages as time pass by. The time passes our vision can also begin to deteriorate as a study suggests 82% of blind people in 39 million blind population are about 50 years and older. So the device suggested can help people to walk without support
of others as it uses image recognition by machine learning and informs the user about the obstacle ahead. Such a way of using machine learning has already been applied in self-driving cars and it is quite effective. And also the device can help disable people who were born blind. The camera
will be mounted on the user chest and Faster R-CNN will divide the live image into 3 * 3 grid and processes various object in a single grid and compares it with its own database. The algorithm can also calculate the distance from the user to the object like a chair and staircase etc. The device
can also read the colour of the traffic lights and can tell the user when the light is green and when the light is red. This device can help many old as well as young people who are blind and reduce the travel difficulties by a large amount.
Color and Texture Feature Based Scene Classification
Authors: Gayathri V. , Clapten Eric , Mahalakshmi S. , Kannan S. Rajes
Published: January 2021

Right now, overall trademark based multiscale multiresolution multistructure (M3LBP) neighborhood parallel example and nearby characteristic based totally min blend feature extraction is proposed for scene category. To extract international functions, characterize the leading spatial
features in a couple of scale, a couple of choice, more than one structure way. The micro/macro shape facts and rotation invariance are guaranteed inside the worldwide function extraction approach. Neighborhood function extraction, coloration histogram characteristic (CHF) can thoroughly explain
the spatial coloration statistics of an image. It also describes the image brightness, color statistics of a photo, which encompass the picture coloration distribution, photo assessment. The CHF can be computed from the min max shade quantizes. Ultimately Fused feature instance amongst nearby
and international capabilities because the scene descriptor to prepare a portion based absolutely extreme finding a workable pace for scene style is outfitted. The proposed strategy is radically assessed on benchmark scene datasets (the 21 magnificence land use scene), and the trial results
show that the proposed procedure prompts predominant kind standard execution as contrasted and the realm of-work of art style systems.
Theme Park of Renewable Energies in the District of Tomas with an Ecotouristic Approach-Perú
Authors: Rodriguez Ciro , Esenarro Doris , Jave Jorge , Martínez Fabiola , Puma Juan , Vasquez Wilson
Published: January 2021

The proposal of a renewable energy theme park aims to sensitize the use of clean energy, the integration of ecotourism as an economic activity and environmental sustainability of the population of Tomas in Peru, to turn it into an identity reference point regional and local. For this,
the green axis is composed of a series of elements such as thematic squares, vegetation segments, recreation, and incorporation of renewable energies. The bioclimatic architectural design of the theme park is related to the balance of nature’s surroundings, so a series of renewable energy
prototypes is proposed in a theme park that takes advantage the use of natural resources from sunlight, radiation, winds, organic waste, among others, which are the components of the proposal. Likewise, interactive education is considered among the resident population of Tomas, and with their
renewable resources are the pillars, to sensitize visitors, in caring for the environment.
Proactive Assistance System for Visually Challenged Persons Using Internet of Things Based on Machine Learning
Authors: Ramalingam M. , Gomathi D. , Saranya D.
Published: January 2021

In this Paper, mainly focusing the visually challenged persons are struggling to move from one place to another place, identification of location, non-visibility of persons and reading newspapers. Due to lack of non visual information in their nearby environment, In order to reduce
the burden of the visually challenged persons problems, the proposed system is consist of Wearable device with well equipped earphone and camera, location identification, face recognition, text recognition by use of Android mobile device. The deep learning approach is proposed to predict secure
and consistent walk able commands. The Android Mobile Application is used to voice recognition, identifying the location, face recognition and text recognition. The proposed low cost prototype is effective way the visually challenged person to interact with their surrounding environment.
The Time Independent Analysis of Finite Waiting Space Generalised Multichannel Mixed Queuing System with Balking and Reneging Due to Long Queue and Some Urgent Message
Authors: Gupta Meenu , Singh Man , Gupta Deepak
Published: January 2021

The Proposed queuing model comprises of M serial service channels connected to N non-serial service channels. Inside every serial as well as non-serial service channel multiple parallel servers are allocated. Customers are allowed to balk as well as renege at any server inside the queuing
model. Along with welsh because of long queue, reneging due to some urgent phone call or text information received, while waiting in the queue is applied in this queuing model. Using (Kelly, F.P., 1975. Networks of queues with customers of different types. Journal of Applied Probability,
12(3), pp.542–554) the difference-differential equations of the proposed model are obtained. Considering the system to be time independent, the time independent equations and corresponding solutions for various cases in the proposed queuing model are obtained. Further, it is submitted
that the appearance process is Poisson, the administration time circulation is exponential, waiting space is finite, arrival of the customer depends upon the queue size at every service channel (serial/nonserial) and Service is done in random order rather than First come first serve principle.
Deep Learning Based Object and Railway Track Recognition Using Train Mounted Thermal Imaging System
Authors: Kapoor Rajiv , Goel Rohini , Sharma Avinash
Published: January 2021

An intelligent railways safety system is very essential to avoid the accidents. The motivation behind the problem is the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. Continuous research is being carried out by distinct
researchers to ensure railway safety and to reduce accident rates. In this paper, a novel method is proposed for identifying objects (obstacles) on the railway tracks in front of a moving train using a thermal camera. This approach presents a novel way of detecting the railway tracks as well
as a deep network based method to recognize obstacles on the track. A pre-trained network is used that provides the model understanding of real world objects and enables deep learning classifiers for obstacle identification. The validation data is acquired by thermal imaging using night vision
IR camera. In this work, the Faster R-CNN is used that efficiently recognize obstacles on the railway tracks. This process can be a great help for railways to reduce accidents and financial burdens. The result shows that the proposed method has good accuracy of approximately 83% which helps
to enhance the railway safety.
Cryptographic Keyed Hash Function: PARAŚU-256
Authors: Sharma Arvind K. , Mittal Sudesh K.
Published: January 2021

Cryptography has distinct paramount significance in interconnected environment where whether we concern about ‘Computer-Security,’ ‘Information-Security,’ ‘Network-Security’ etc., doesn’t matters and, ingredients of this particular branch of
computer science viz. ‘Encryption/Decryption’ systems, ‘Hash-Functions,’ ‘Digital-Signatures’ etc. also playing vital role from years in order to manage ‘Confidentiality,’ ‘Integrity’ and ‘Authenticity’ of resources. The
Encryption/Decryption Cryptosystems managing the Confidentiality and Hash-Functions are fully devoted towards to look after the Integrity, Authenticity either alone or with Digital Signature schemes. There is a huge list of ‘Hash-Algorithms’ available with us to provide dedicated
services (i.e., security) depends on how complex is to break it. Few renowned names are MD5, Blake, CRUSH, Grøstl, HAIFA, JH, Lake, SHA, Skein, Whirlpool etc., Keyed/Un-keyed constructions having its own justifiable capabilities. So in this direction we’re proposing a new secure
keyed Hash-Function especially for military services where security is major concern apart from resource utilization which not only fulfilling basic properties but also providing justifiable services in order to manage integrity/authenticity of resources.
Moment-Generating Function Based Symbol Error Probability Comparison of M-ary Modulation Techniques in Fading Environment
Authors: Gupta Kapil , Mehta Rachna
Published: January 2021

This paper analyses and compare Symbol Error Probability (SEP) of M-ary modulation in different fading environment. Maximal ratio combining (MRC) technique with N branch receiver diversity is taken into consideration for the analysis. Expression for probability of symbol error
for M-ary frequency shift keying/M-ary phase shift keying/M-ary differential phase shift key/and M-Level Quadrature Amplitude Modulation are obtained through moment-generating function (MGF) approach. Conventional integration process has probability of uncertainty
and erroneousness because of composite mathematical calculations and infinite integration bounds. MGF method is used to avoid complex numerical computation for calculation of SEP. Comparison of SEP for diverse values of Rician factor “K”, Nakagami-M factor, modulation
order “M” and diversity order “N” has been carried out.
Specially Structured Three Stage Flow Shop Scheduling to Minimize the Total Waiting Time of Jobs
Authors: Gupta Deepak , Singla Payal , Singh Sukhvir
Published: January 2021

Basic Flow shop scheduling is converted to three stage flow shop scheduling, this paper describes waiting time of jobs on Specially Structured machines aimed at minimizing total waiting time of ‘n’ jobs when the number of machines (or processing stations) is ‘3’.
The problem discussed has wider applicability and has better practical usage when it comes to reducing the overall waiting time of scheduled jobs. The objective of the observation is to bring forth the arrangement/sequence of jobs associated with the least amount of total waiting time using
iterative algorithm. The application of the algorithm is universal under given constraints discussed here. Furthermore, a practical example is discussed step by step to clarify the application of the algorithm.
Recent Advancement for Diagnosing Diabetic Retinopathy
Authors: Nagpal Dimple , Panda Surya Narayan , Gupta Nayan
Published: January 2021

Diabetic retinopathy (DR) is a sight-threatening disease that can be prevented by early diagnosis and screening. It damages the retinal vasculature and can cause retinal abnormalities. The diagnosis of DR can be done accurately by detecting various retinal signs such as microaneurysms,
hemorrhages, exudates, etc. In this paper, a review of various retinal abnormalities along with the comparison of imaging modalities has been done. Furthermore, the paper elaborates on the methodology of detecting the lesion among diabetic patients. This review is important to those who are
new to the field of medical image analysis and want to contribute more to the field of DR.
Performance Comparison of Data Mining Classifiers on Web Log Data
Authors: Malik Varun , Rattan Vikas , Singh Jaiteg , Mittal Ruchi , Tandon Urvashi
Published: January 2021

Web usage mining is the branch of web mining that deals with mining of data over the web. Web mining can be categorized as web content mining, web structure mining, web usage mining. In this paper, we have summarized the web usage mining results executed over the user tool WMOT (web
mining optimized tool) based on the WEKA tool that has been used to apply various classification algorithms such as Naïve Bayes, KNN, SVM and tree based algorithms. Authors summarized the results of classification algorithms on WMOT tool and compared the results on the basis of classified
instances and identify the algorithms that gives better instances accuracy.
Strategy of Networked Cooperative E-Learning and Its Effect in Facilitating the Learning of Arabic Grammar in Light of the Quranic Text
Authors: Sayed Mohamed Aziz Abdelmaksoud , Manzo Ousmane , Taher Rusdee , Katih Isma-ie , Panprae Prasert , El-Ebiary Yousef A. Baker
Published: January 2021

Often see complaints about the difficulty of learning the rules of Arabic grammar. Also that how many claims were made to its simplification, books and literature were classified to make it easier and this is a vision in facilitating E-learning the rules of Arabic grammar through networked
cooperative E-learning strategy. So the question is can introduce the rules of the Arabic educational grammar in an electronic template using modern technology means? To make it easier for learners of Arabic grammar to understand its rules and that is through application models in the light
of the Quranic text, to understand it and to understand its context. Keeping pace with modern technological developments (inventions), the requirements and developments of the time, these factors push specialists of Arabic grammar to think about presenting its rules in various new ways. Maintaining
its constants while benefiting from modern electronic technologies away from traditional ones that are concerned with preserving the rules in deaf molds, which led to the exclusion of many from learning the rules of Arabic grammar. There are many claims made to facilitate the teaching of Arabic
grammar, beginning with Ibn Mada’ Al Qurtubi in his book “al-Radd ‘ala‘ al-Nuhat” Response to specialists of Arabic grammar. Second is Ibrahim Mustafa in his book “Revival of grammar,” and third Dr. Shawqi Daifin his preface of the book “Responding
to specialists of Arabic grammar” by Mada’ Al Qurtubi where he called for the necessity of a new classification of grammatical material. There are some other claims went in the field of renewal and facilitation.
An Optimized Novel Technique for Video Synopsis Using Bayesian Object Tracking Algorithm
Authors: Thirumalaiah G. , Pandian S. Immanuel Alex
Published: January 2021

This paper presents another analytical video description of the methodology, which is far superior in pressure and depth to previous methodologies. In preparation, the video of the reconnaissance was usually packed by moving the pushing objects alongside the time hub, which undoubtedly
resulted in a real crash and ordered issue antiques between the items being pushed. The main idea in this paper is that these antiques can be reduced by using the Bayesian calculation for fragmentation, and the last approach for foundation extraction is used following the products. We offer
the best way to integrate these three heterogeneous activities into a single improvement system and achieve excellent outline performance. The Calculation of Metropolis does not like past methodologies that usually use optional improvements to fathom summary improvements to find the answer
for our three-variable progress problem. A range of research demonstrates the feasibility of our technology.
Maintainability Procedure in Component-Based Software
Authors: Kaur Amandeep , Kaur Puninder , Kaushal Payal
Published: January 2021

Changes in service requirement of software demands consequent changes in its maintainability. An important aspect of changes is that it affects various factors in Component Based Software Engineering which is reuse-based approach to define, implement, and integrate different components
into system. Variety of Component-based software frameworks for distributed, real-time and embedded systems in Component-oriented programming are existing for specific domains in order to deal with different requirements. Functionalities under component based system affecting multiple factors
in a distributed environment. It is therefore more than necessary to consider various quality attributes like reliability, maintainability, interpretability and reusability for determining quality assurance. The article presents an approach to enhance the promptness of system maintainability
in case of changes in component based software.
A Systematic Review About Prediction of Academic Behavior Through Data Mining Techniques
Authors: Kaur Puninder , Kaur Amandeep , Kaur Rajwinder
Published: January 2021

In the IT world, predicting the academic performance of the huge student population poses a big challenge. Educational data mining techniques significantly contribute in providing solution to this problem. There are several prediction methods available for data classification and clustering,
to extract information and provide accurate results. In this paper, different prediction methodologies are highlighted for the prediction of real-time data analysis of dynamic academic behavior of the students. The main focus is to provide brief knowledge about all data mining techniques and
highlight dissimilarities among various methods in order to provide the best results for the students.
Plant’s Leaf Analysis Using Pattern Recognition Algorithm
Authors: Malhotra Neha , Rani Geeta
Published: January 2021

Plant species identification is an important area of research which is required in number of regions. Design and development of an automatic leaf based plant species identification system is a challenging task. The initial step of any coordinating/acknowledgment framework is to identify
intrigue areas in the pictures and portray them. The proposed system is based on pre-processing, feature extraction and their weighted normalization and finally classification. In this paper, pattern recognition/retrieval techniques are studied by extraction of novel features in all three
domains and their performance has been evaluated based on Entropy, Peak-Signal-to-Noise-Ratio (PSNR), Standard Deviation (SD), Euler Number and Gradient Magnitude Similarity Deviation. This paper presents scientific ideas for distinguishing and depicting image features.
Supply Chain Orientation, Integration, Sustainability and Organizational Performance in Healthcare Industry
Authors: Kumar Rajesh , Kumar Sanjay
Published: January 2021

The concept of Supply chain Orientation (SCO), Supply Chain Integration (SCI), Supply Chain Sustainability(SCS) and Organizational Performance (OP) has been envisaged independently or incombination by researchers. Present paper is an attempt to provide comprehensive view on SCO,SCI,
SCS and OP including the areas of organizational strategy, Organization structure and organizationenvironment getting insight from healthcare industry. This study reviews how synchronizationof Intra-organization and Inter-organizations strategies, structure and environment help to improveOrganization
Performance.
Verification of All-Optical Regeneration with Hybrid Modulation and with On-Off Keying Modulation with Return to Zero and Non-Return to Zero Coding
Authors: Oliveira Jackson Moreira , da Silva Hudson Afonso Batista , de Sousa Fabio Barros , de Oliveira Lelis Araujo , de Oliveira Jorge Everaldo , de Sousa Fiterlinge Martins , Caldas Costa Marcos Benedito
Published: January 2021

In this work we study the non-linear effects through the analysis of the operating results of three alloptical 3R regeneration (re-amplifying, re-shaping and re-timing) under the effects of cross-phase modulation (XPM) and four-wave mixing (FWM), being a system with hybrid modulation
and two other communication systems with modulation on-off keying (OOK) with return to zero (RZ) and non-return to zero (NRZ) coding. The main part of the 3R regeneration system proposed here is a Mach-Zehnder interferometer (MZI) composed of an acousto optical filter (AOF) and a highly nonlinear
photonic crystal fiber (HNL-PCF), so the system proposed here was named 3R-MZIAOF regenerator. The comparison of the system results occurred through the variation of the input power variation from -10 dBm to 10 dBm for the link length of 121.3 km and transmission rate 10 Gbps. The results
showed that the regeneration 3R scheme OOK-NRZ with AOF presented excellent values of bit error rate (BER) equal to 10-21 and quality factor (Q-Factor) equal to 9.4, when compared to a system with OOK-NRZ 3R regeneration and hybrid modulation.