bluuebunny/crossref_metadata_2025 huggingface dataset:
The Government's Efforts in Fulfilling the Accessibility of the Rights of Persons with Disabilities through Social Rehabilitation in East Java
Authors: Putra Muhammad Kanda Setia , Hijri Yana Syafriana , Kamil Muhammad
Published: October 2022

One of the benchmarks for democracy in a government is considering the state's ability to fulfill and guarantee the rights of its citizens. The East Java Provincial Social Service carries out rehabilitation regularly, both inside and outside the orphanage through program activities carried out by the Social Rehabilitation Division of East Java Province. The purpose of this research is how the government's efforts to fulfill the accessibility of the rights of persons with disabilities through social rehabilitation in East Java. This research uses qualitative research with a case study approach. This study uses 2 data sources, namely primary data and secondary data. Primary data was obtained through interviews with the Social Service of East Java Province regarding the Government's Efforts in Fulfilling Accessibility of Rights of Persons with Disabilities through Social Rehabilitation in East Java, while secondary data was obtained through journals for persons with disabilities, journals on the role of the government towards persons with disabilities, operational instructions for the work of the social services of the Java province. East Java, books or documents about persons with disabilities as references and supporting elements relevant to fulfilling the accessibility of persons with disabilities in East Java. In general, several programs have had a very positive impact on people with disabilities, but several things made the program less effective, such as the uneven distribution of programs in various districts/cities in East Java due to the limited number of targets, and inadequate follow-up after the program implementation monitored.
Implementation of E-government in Education Services through the Development of Education Management Information Systems (SIMDIK) in Malang City
Authors: Wardana Dini Kusuma Arya , Kamil Muhammad , Hijri Yana Syafriana
Published: October 2022

Electronic Government (E-government) application in various regional apparatus organizations is the government's effort to provide excellent public services to the community. The implementation of e-government through the development of an Education Management Information System is a policy taken by the Malang City Government to solve educational management problems and provide optimal educational services. This research is qualitative research with a case study approach. The research location is in the Department of Education and Culture of Malang City and the Department of Communication and Information Technology of Malang City. The findings of researchers in the field indicate uncertainty in the implementation of e-government through the development of  an education management information system (SIMDIK) in Malang City. The massive commitment of the institution is inversely proportional to the support of the state civil apparatus. It impacts uncertainty in the implementation of e-government through the development of education management information systems in the city of Malang. This inconsistency is motivated by inadequate resources. In the end, the implementation of e-government through the development of education management information systems in Malang City failed. The existence of these failures impacts the non-fulfilment of the dimensions of smart governance, which at the same time hinders the realization of good governance.
Transfer of Land and Building Taxes in the Plantation and Forestry Sector in Indonesia in a SWOT Analysis Review
Authors: Sandy Nastiti Tri , Inayati Inayati
Published: October 2022

Indonesia is a country that has high natural resource potential. This potential encourages the government to collect the tax on land and building plantations, forestry, mining, and other sectors (PBB-P3). Then the proceeds are allocated to local governments to overcome vertical fiscal inequality. However, in practice, problems were found related to the low fiscal independence of regions due to dependence on Transfers to Regions (TKD) by the central government and the distribution of Revenue Sharing Funds (DBH) on Land and Building Taxes and natural resources. This paper analyzes the strengths, weaknesses, opportunities, and threats of Land and Building Tax (PBB) in the Plantation and Forestry sector devolution from the central tax to local taxes. Also, analyze the strategies for the transfer of PBB plantation and forestry sector. This study uses a qualitative approach with SWOT analysis and primary collection techniques through in-depth interview data and literature study. The analysis results show that PBB plantation and forestry sector has several weaknesses and threats related to the readiness of local government human resources, the mechanism for collecting PBB-P3, and the impact on the exploitation of natural resources. However, the strengths and opportunities found in this study can be considered for the regionalization of PBB plantation and forestry sector in the future. Strength-opportunity, strength-threat, weakness-opportunity, and weakness-threat strategies that can be prepared are preparing local government human resources, technological facilities for PBB-P3 administration, and special rules governing PBB-P3 regionalization.
Block chain Based Accounts Payable Platform For Goods Trade
Authors: Kumar E. Pavan , kumar Mr. Hemanth
Published: October 2022

In the prevailing paper, delivered a fuzzy weakly ordering the use of fuzzy metric area and fuzzy partial metric area.
Facial Expression Recognition based Restaurant Scoring System Using Deep Learning
Authors: Srinivas Mr. Anumula , Kambam Vikas Reddy , Pinnu Sai keerthana , Edla Sriram , Komera Arun Kumar
Published: October 2022

Food plays an important role in every human being’s life. Taking this as major objective several people are coming up with numerous new restaurants. Many of these restaurants are with less or no staff. Because of this reason, the rating of most of the restaurants is inaccurate. To overcome this problem and give a practical and exact rating to restaurants, this paper presents a Facial Expression Recognition-based Restaurant Scoring System with a pre-trained CNN model. By this model, customers can rate the food as well as the environment of the restaurants in three different expressions (Satisfied, Neutral, Disappointed). For implementing and using this system, we consider an application and server.
Technique for interpretation of archive and recent satellite images to study the slope processes dynamics in the Geyzernaya river valley (Kamchatka)
Authors: Baldina Elena , Lebedeva Ekaterina , Medvedev Andrei
Published: October 2022

Based on the database of spatial thematic data sources for the Geysernaya River valley (Kamchatka), the work was carried out to identify the areas of the greatest activation of modern exogenous processes and the manifestation of endogenous processes over the maximum possible time interval (more than 50 years). Space images of high spatial resolution (0.5–3 m), received from Key-Hole-4 (1964), GeoEye (2009), Pleiades-1A/1B (2013, 2016), WorldView-2 (2017) satellites, results of field survey and UAV imagery in 2021, literature and archive materials were used as sources. The developed interpretation technique included both sequential interpretation of preliminary geometrically coordinated multi-temporal images and their digital processing: brightness quantization, calculation of vegetation index NDVI, formation of color multi-temporal composite, which allowed to separate vegetation-covered and bare slope areas by formal features and increased the overall reliability of interpretation. Calculations based on the interpretation results determined that the proportion of the total valley area affected by modern slope processes was 10.5 % in 1964, 14.8 % in 2009, and 13 % in 2017. In the process of images interpretation, it was established that slope processes dominated on the left bank of the Geyser River, where more than 75 % of the area of all outcrops (or 10.2 % of the total studied area of the valley) was concentrated, which is apparently caused by confinement of this valley side to the caldera limiting circular fault, which preserves its activity, and also by the presence of the area of modern uplift there. On the right bank of the river, large areas are occupied by ancient large gravitational shifts, possibly associated with collapsing edges of extrusive massifs. Landslides-slides and erosion in the groundwater outlets are predominant among the modern processes here. The right bank accounts for less than 25 % of the area of all outcrops (or 3.3 % of the total study area).
Climate-driven “greening” of the kurum landscape in the valley of the lower reaches of the Podkamennaya Tunguska river
Authors: Vysotskaya Anna , Medvedkov Alexey
Published: October 2022

The paper considers changes in the biological productivity of the landscapes recorded in the Yenisei Siberian taiga kurums associated with climate warming of mid-1970s to early 1980s. Specifically, changes in NDVI (as an indicator of plant-mass productivity) from 1992 to 2018 were assessed within representative sites of the key study area located in the west of the Central Siberian Plateau. To study the bioproductivity dynamics and the current state of kurum landscapes, 30-meter resolution satellite images—Landsat 4.5 (TM), 7 (ETM+), and 8 (OLI) series—with atmospheric correction (Landsat Surface Reflectance) were used. Refinement of data on individual kurums was carried out with the help of WorldView-1 (2.4 m) and PlanetScope (3 m) multi-zone images. From the end of the first decade of the 21st century to 2019, NDVI increased by 0.38 units, on average. This is manifested in a larger area under moss cover, spread of shrubs and small-leaved species undergrowth, and emergence of sparse stands. The data calculated from processing of the 30-meter resolution satellite images (Landsat) exhibit a high-degree correlation with the results obtained by using higher-resolution analogous images (WorldView-1 and PlanetScope). It appeared that the cold-exposure slopes covered with block accumulations were more responsive to the growth of plant-mass. The results of remote-sensing data processing allow for a field-based extrapolation within a large and genetically unified territory. It was revealed that the intensity of kurums “greening” in the considered middle taiga area is comparable with the increase in NDVI in even higher latitude regions (north taiga, forest-tundra, and tundra) of Central Siberia.
A method for detecting plastic waste floating using Sentinel 2 high spatial resolution image: a case study in the coastal area of Vietnam
Authors: Trinh Le Hung , Nghiem Van Tuan , Bien Tran Xuan , Le Van Phu , Nguyen Sach Thanh
Published: October 2022

Ocean plastic waste pollution is now becoming a serious environmental problem, especially for a country with a long coastline and wide sea like Vietnam. The remote sensing method is considered suitable and effective in early detection and classification of ocean plastic waste due to the difference in spectral reflectance of plastic waste compared to the surrounding sea. This paper presents the results of identification and classification of plastic mesh in coastal areas of Vietnam by using Sentinel 2 MSI high spatial resolution optical images. First, water was extracted from Sentinel 2 image by thresholding method on a near-infrared band. Then, the plastic mesh was identified and classified based on Float Debris Index (FDI) index using Otsu thresholding algorithm. In the study, spectral indices such as NDVI, NDWI were also used to improve the accuracy in classifying plastic mesh. In the study, Google high spatial resolution satellite images were also used to evaluate the accuracy of plastic mesh classification. The obtained results show that, in 02 test areas, the proposed method allows detecting plastic mesh with an accuracy of over 90 %. The results obtained in the study can be used to provide input information for models of forecasting and assessing the impact of ocean plastic waste pollution on coastal environments.
Determination of transverse structures based on lineament analysis: a case study of the Fergana valley
Authors: Sichugova Lola , Fazilova Dilbarkhon
Published: October 2022

As a result of the stress state of the lithospheric block, a structure of orthogonal cracks may appear as a network of straight or arcuate topographic elements of the regional extent on the Earth’s surface—lineaments. In the last decade, one of the directions of lineament analysis had been the identification of the so-called transverse structures using remote sensing methods, which often serve as the geological boundaries of crustal blocks. Various lineament analysis methods are being actively developed: image enhancement, manual digitizing methods, and automatic extraction using software and algorithms. Revealing the relationship between lineaments and their characteristics with natural and anthropogenic processes is the relevant task. The tectonic lineament network is associated with deep faults and, in particular, ore regions that can be localized at the intersection of large lineaments. Therefore, most studies of increased accumulation of lineaments are carried out in areas where mineral deposits and groundwater deposits are identified. These areas include the Fergana region, which is one of the five oil and gas regions of the Republic of Uzbekistan. The presence of a fund of promising traps justifies the need for comprehensive geoinformation support, including satellite methods, and the possibility of transition to automatic methods for analyzing tectonic processes. Therefore, in this study, an automated lineament analysis was carried out in order to identify and interpret the transverse structures in this region. The study period (May–November 2019) was chosen to take into account the intensive exploration work in the region and the technical parameters of the images (without clouds). Landsat 8 satellite images were processed by the automated method of lineament structures interpretation in the LEFA program in the MATLAB environment. During the visual analysis of the processed images, it was identified that there was a temporary change in the number of lineament structures by month. At the same time, the northwestern part of the region (Namangan region) is characterized as the zone of the strongest manifestation of lineament structures. Further detailing of the lineament structures in terms of direction and orientation made it possible to determine the transverse structures. Thematic maps with the geospatial location of transverse structures showed that the nature and clarity of transverse structures varied depending on the features of the geological structure of the sections they intersected.
Comparative analysis of the ice coverage in the Bering sea according to the Sea Ice Index and Masie data
Authors: Oganezov Artur , Pishchalnik Vladimir , Romanyuk Valery
Published: October 2022

This paper presents a comparative analysis of the ice cover of the Bering Sea. The analysis was performed according to the National Snow & Ice Data Center (NSIDC) using NASA algorithms Team (Sea Ice Index) and Near-Real-Time Passive Microwave/Visible Data Sharing DMSP SSMIS Daily Polar gridded Sea Ice Concentrations and Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data (MASIE-NH). The absolute and relative difference of the ice cover values were calculated using the algorithms Sea Ice Index and MASIE-NH with daily discreteness for 14 ice seasons from 2006 to 2020. Despite the fact that the spatial resolutions of the data of the algorithms under consideration and the quantitative criteria for the condition for classifying a pixel as pure water or ice extent differed (the side of the pixel was 25 and 4 km, identification was 15 and 40 %, respectively), the curves of the average seasonal variation of the ice cover were in phase and that was confirmed by the high value of the correlation coefficient (0.92). It was determined that the difference in ice cover values were not critical and were within the calculation limits, which allowed using data from both sources without calculating correction factors. Sea Data Ice Index data should be appropriate for long-term analysis of inter-seasonal variability, since data series of observations with daily discreteness have been available since 1978. It was concluded that the use of both sources would be quite acceptable in the analysis of intra-seasonal fluctuations. A characteristic feature of Sea Ice Index was noted—the presence of ice throughout the warm season. Although according to literary sources, such a phenomenon in the Bering Sea was typical only for severe types of winters. That was probably due to the technical difficulties in identifying the ice extent using passive microwave sounding methods.
Evaluation of the possibility of vegetation interpretation on thermal infrared satellite images, case of the Southern Urals and Kuznetsk Alatau
Authors: Grishchenko Mikhail , Lucher Denis , Bocharnikov Maxim
Published: October 2022

The paper presents the results of the vegetation cover interpretation using multitemporal thermal satellite images of two mountain-steppe areas: in the Southern Urals (Abzelilovsky district of the Republic of Bashkortostan) and in Kuznetsk Alatau (Ust-Abakansky and Shirinsky districts of the Republic of Khakassia). These areas have a large amount of field data on vegetation, which allows for reliable verification of satellite data. On the basis of field data and images of high spatial resolution in the optical range, vegetation maps were compiled, which became the basis for further interpretation of thermal images—images of the TIRS sensor, Landsat 8 satellite, were used. Methods of controlled and uncontrolled classification were applied to multitemporal images. In the course of the study, it was possible to establish that, based on the results of vegetation interpretation using thermal satellite images for a site in the South Urals, it is possible to determine forest areas with good reliability (up to 50–70 %), and confidently draw the border between forest and treeless areas. With satisfactory accuracy (up to 44 %), petrophytic steppes are determined. The site in the Southern Urals is characterized by a small size of the territory, a low diversity of plant communities, and rather a large dependence of the intensity of thermal radiation on the exposure of slopes. The site in Kuznetsk Alatau showed more representative interpretation results. Larch and birch-larch forests (up to 70 %), fir and birch-fir forests (up to 56 %), dwarf birch and moss-lichen tundras (up to 49 %), and steppe vegetation (up to 45 %) are most confidently recognized.
The Relationship between Awareness and Retail Investors Investment Intentions in the Derivatives Market
Authors:   Associate Professor, Department of Studies in Commerce, Davangere University, Shivagangothri (Karnataka), India., I B Dr. Cirappa , K C Ms. Tejashwini ,   Research Scholar, Department of Studies in Commerce, Davangere University, Shivagangothri, Davangere.
Published: October 2022

The Indian derivatives market remains small despite a lengthy history, several committee recommendations, and continuous developments. The Indian derivatives market is dominated by institutional investors, with little participation from individual investors due to a lack of awareness and comprehension of the product. As a result, the objectives of this research are to establish the level of retail investor derivatives market awareness, as well as the relationship between awareness and derivatives market investment intention. A questionnaire- based survey is being conducted with a sample size of 30 respondents. The findings of the survey demonstrate that the majority of respondents have either average or below average derivatives market awareness, and that there is a strong link between awareness and derivatives market investment intention.
Comparative Evaluation of the Antibacterial Activities of Ethanol Leaf Extracts of Moringa oleifera (Lamarck) and Dialium guineense (Jacqueline)
Authors: John Dan , Lambert Okwubie , Emma Eugenes, Ugonne
Published: October 2022

The antibacterial activities of many medicinal plants have been carried out to assess their potential use in bacteria borne diseases. In this study the antibacterial activities of two medicinal plants, Moringa oleifera and Dialium guineense as well as their phytochemical contents were carried out and compared. Their leaves were collected separately, dried, pulverized to powder and extracted with ethanol. The phytochemical analysis of M. oleifera and D. guineense extracts were carried out using standard methods, while their antibacterial activities were evaluated and compare using some bacterial isolates and by agar well diffusion method. The result of the phytochemical screening showed that both plants possess the same phytochemicals with exemption of steroids which is present only in D. guineense, and cardiac glycosides only present in M. oleifera. The results of the antibacterial activities are as follows; on Staphylococcus aureus, at concentration of 100 mg/ml, M. oleifera and D. guineense gave inhibition zone diameters (IZD) of 9.5± 0.30mm and 7.5 ± 0.14mm respectively, with minimum inhibitory concentration (MIC) of 1.25% and 0.625% respectively. On Streptococcus pneumonia, at concentration of 100mg/ml M. oleifera and D. guineense gave IZD of 8.5± 0.26mm and 8.5 ± 0.26 mm respectively, with (MIC) of 0.625% and 1.25% respectively. On Escherichia coli, at 100 mg/ml, M. oleifera and D. guineesne gave IZD of 10.0± 0.34mm and 8.5 ± 0.26 mm respectively, (MIC) of 2.5% and 1.25% respectively. On Pseudomonas aeruginosa at concentration of 100 mg/ml, M. oleifera and D. guineense gave IZD of 9.5± 0.32mm and 7.0± 0.09mm respectively. Examination of these results showed that M. oleifera is slightly more active than D. guineesne.
Linezolid as Potent Inhibitor of SARS-CoV-2 Nsp13 Helicase: Grid Based Docking Approach
Authors: Singh Neha , Malik Jitender K
Published: October 2022

Abstract: A diversified originator in humans and wildlife, the corona virus (COVID-19) is an enveloped RNA virus. Six different species have been shown to be the root of human sickness. Human diseases are greatly influenced by viral infections, and one of the most recent global epidemics is the appearance of the new corona. The SARS (Severe Acute Respiratory Syndrome) virus, a potentially fatal viral infection, was caused by the SS-RNA virus from the enveloped corona virus family. In many nations around the world, disease is rapidly expanding. 462,684 confirmed cases and 20,834 fatalities had been reported as of March 26, 2020, internationally. On March 11, 2020, COVID-19 was declared a pandemic by the World Health Organization (WHO). There are numerous medication trials ongoing, and some of the outcomes are encouraging. However, since there is no vaccine, the only approach to fight the virus is through preventative measures. Patients with bacterial nosocomial pneumonia were successfully treated with the antibiotic "Linezolid" by receiving an intravenous dose of 600 mg of linezolid every 12 hours for 7 to 10 days. All of the patients made a full recovery and were allowed to leave the hospital. Additionally, previous studies have shown that linezolid is more clinically and microbiologically effective than other antibiotics (vancomycin). The goal of the current study was to use a molecular docking approach to evaluate linezolid's potential against SAR-CoV-2 infection.
Role of Aromatase Inhibitor to Improve Semen Quality in Case of Eugonadotropic Hypogonadism
Authors: Nasreen Dr. Rehena , Islam Mohammad Kamrul , Sumi Mariam Akter , Sen Sumon Kumar , Hasan Md. Mahmudul
Published: October 2022

Background: Excess aromatase activity is common in males with severely impaired sperm production, as shown by low Semen testosterone and somewhat increased estradiol levels. Elevated estrogen levels cause inhibitory effects of the hypothalamic-pituitary-gonadal axis, resulting in a reduction in LH required for testosterone production and FSH to maximize sperm motility. The main objective of this study was to see how an aromatase inhibitor to Improve Semen Quality in Case of Eugonadotropic Hypogonadism. Methods: This Prospective study was conducted in the Department of obstetrics and gynecology, Dhaka Medical College Hospital, Dhaka, Bangladesh during the period from June 2020 to May 2021. The sample size was 40 subfertile men with oligospermia. (≤ 10 million/ml), low semen testosterone level (<300 ng/dl) and low testosterone to estradiol ratio (<10). All patients were treated with Aromatase Inhibitor 2.5 mg daily for 4 months. At the end of the 4 months the semen analysis was performed. Statistical analysis was carried out by using IBM Statistical Package for Social Sciences version 25 for windows (SPSS version 25.0). Results: The sperm concentration, sperm motility and total motile sperm count significantly increased after Aromatase Inhibitor treatment. The side effects were mild and well tolerated. Conclusions: According to the findings of this study, some men with oligospermia, low Semen testosterone levels, and normal gonadotropin levels may have curable endocrinopathy. In infertile males with a low Semen testosterone to estradiol ratio, Aromatase Inhibitor may be administered to enhance sperm parameters.
A Study on Subtitle Translation of City Publicity Video: City for Life
Authors: Wang Leyang , Zheng Yiyang
Published: October 2022

City publicity video spreads city images with strong visual impact, and high-quality subtitle translation builds a bridge for cultural exchange. So this paper takes the short video City For Life of Xiong'an as an example and bases on its stylistic features to discuss the strategies of sound and picture synchronization, discourse coherence strategies, and cultural value principles applied by translators in the process of subtitle translation. The translator should strive to achieve textual coherence and cultural transmission on the basis of the inherent characteristics of subtitles.
The Metabolic Syndrome And Specific Populations At Risk: Can Precision And Individualized Medicine Change Things?
Authors: Cristina Davide , Faranna Luciana A.
Published: October 2022

Objectives of the study: the metabolic syndrome (MS) consists of a group of metabolic alterations that have insulin resistance as their common denominator and identifies a pathophysiological condition at high risk of developing cardiovascular disease and type 2 diabetes. 20% and 30% of the adult population is affected by MS Design and method: in this article the authors try to make a scientific contribution regarding the problems of some patient populations often having to necessarily take drugs with an important metabolic impact while developing an iatrogenic-based MS (IMS) and propose to further investigate the aspects and the clinical pharmacological problems of the population of psychiatric patients at risk of MS. Results: Although the prevalence of MS has been observed to be often higher in the urban population of some developing countries, there are patient populations who develop MS due to the extensive use of certain drugs with obesogenic-metabolic adverse effects, in particular some generations of antidepressant and neuroleptic drugs (NL) used in mental disorders and antiretroviral drugs, such as integrase inhibitors used in HIV infection. Conclusions: Populations at risk of IMS should be at the center of the search for an individualized precision medicine with the careful choice of pharmacological therapies and appropriate lifestyle. Unfortunately, precision medicine in the psychiatric field seems to be stopping its growth due to the lack of identification of biomarkers and indicators of psychopathology.
FORENSIC BIOMETRICS IDENTIFICATION SYSTEM FOR DNA PROFILE HUMAN BASED ON ASSOCIATION RULES
Authors: Faleh Najah H. , Al-Saedi Karim H.
Published: October 2022

It should be noted that there is a joint work between biomedicine such as forensic medicine and information technology through the use of information technology technologies in all fields, including determining the of DNA profile. One of the leading biotechnologies in this field is data mining techniques. There are many ways to identify disaster victims, such as fingerprints, dental record and DNA profile matching. DNA matching is a highly accurate identification way that does not need specific parts of the victim's body. Deoxyribose Nucleic Acid (DNA) is the basic elements that make up an entire section of a human. The core elements store unique information for each individual and will be passed on through generations. DNA also helps in identifying the father in paternity testing,. The limitation of applying DNA matching for disaster victim identification lies on expensive and time consuming process. To address this situation, in this paper, we performed a method to measure the confidence of matching of human DNA profiles identification using Association Rule Classification System is proposed. In this Classification system, DNA profile data is used as an input that stores human identity along with its DNA profile. advisable information or good patterns from present datasets for certain objective. The results were satisfactory and characterized by large percentage and high accuracy. Finally, performance of this system is evaluated and in turns the proposed system proves its capability in forensic human identification and scalability to handle huge amounts of data.
cSPAM Cloud based Student Project Administration and Management
Authors: Suhag Sandeep , Raut Devesh , Joshi Shreyash
Published: October 2022

In today’s world, time is very crucial and thus valuing time is of utmost importance. Managing projects and submissions of each subject mini project and semester mini project becomes a hectic task for both faculties and students. Efficiency is thus compromised in such situations. The time spent in the whole process of mini project from start to end takes a lot of time if done manually and the monitoring and tracking the progress of all the groups by the faculty is too hectic for the faculties. Project management tool plays a crucial role here, skipping all the wastage of time and hassle of project submissions. Our proposed system is a common platform for our institute to manage project submissions and interacting with faculty members and teammates everything online to achieve efficiency.Our proposed system will provide 3 different logins i.e student, faculty and admin.Here students could easily submit their progress of the project and faculties would be able to take to give feedback to the group , keep tracking and monitoring the progress and admin would be authenticating students and faculties and also creating the separate channels for the groups and assign the mentors.
Multi View Video Summarization Using RNN and SURF Based High Level Moving Object Feature Frames
Authors: Paramanantham Vinsent , S Dr. SureshKumar
Published: October 2022

Multi-View Video summarization is a process to ease the storage consumption that facilitates organized storage, and perform other mainline videos analytical task. This in-turn helps quick search or browse and retrieve the video data with minimum time and without losing crucial data. In static video summarization, there is less challenge in time and sequence issues to rearrange the video-synopsis. The low-level features are easy to compute and retrieve. But for high-level features like event detection, emotion detection, object recognition, face detection, gesture detection, and others requires the comprehension of the video content. This research is to propose an approach to over- come the difficulties in handling the high-level features. The distinguishable contents from the videos are identified by object detection and feature-based area strategy. The major aspect of the proposed solution is to retrieve the attributes of a motion source from a video frame. By dividing the details of the object that are available in the video frame wavelet decomposition are achieved. The motion frequency scoring method records the time of motions in the video. The frequency motion feature of video usage is a challenge given the continuous change of objects shape. Therefore, the object position and corner points are spotted using Speeded Up Robust Features (SURF) feature points. Support vector machine clustering extracts keyframes. The memory-based re- current neural network (RNN) recognizes the object in the video frame and remembers a long sequence. RNN is an artificial neural network where nodes form a temporal relationship. The attention layer in the proposed RNN network extracts the details about the objects in motion. The motion objects identified using the three video clippings is finally summarized using video summarization algorithm. To perform the simulation, MATLAB R 2014b software was used.
Purchase and Analytics for Grace Marketing
Authors: FM Mohammed Farooq Abdulla , V Tamilselvan , V S Harshini , R S Deepthikka
Published: October 2022

In recent years development of computer systems were able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data is known as machine learning.In this phase sales of different lubricants were predicted using a multivariate time series forecasting algorithm.Previously it showed that the model was accurate in predicting the engine oil sales for a particular time.Using Regressions the accuracy of sales prediction was less (74%) and the models like SVM and Random forest were showing signs of over fitting.The accuracy obtained in the multivariate time series forecasting was good than other algorithms.Time series algorithms are used extensively for forecasting time-based data.In time series ARIMA,SARIMA and SARIMAX are the common methods to forecast time based data.SARIMAX are efficient in forecasting data which has seasonality trends than ARIMA which are good in forecasting data which is stationary in nature Time series methods are extensively used for forecasting time based data.In time series ARIMA,SARIMA and SARIMAX are the common methods to forecast tie based data.ARIMA is the abbreviation of Auto Regressive Integrated Moving Average a model which explains a given time series model based on its lags and other values.SARIMAX is the abbreviation of Seasonal Auto Regressive Integrated Moving Average with Xegeneous variables. ARIMA model is best for forecasting stationary time series data and SARIMAX is used for forecasting values which is seasonal in nature.
Conventional Feature Selection Filter Based Techniques Used in Image Classification
Authors: U Kumar Siddamallappa , Gandhewar Dr.Nisarg
Published: October 2022

With the increased volume of unstructured information coming from various sources, image classification has become substantially more applicable. Various image arrangement strategies have been developed. One of the set up issues in image arrangement is the high-dimensionality of element space. Highlight determination is one of the methods to lessen dimensionality. Highlight determination helps in expanding classifier execution, decrease over sifting to accelerate the grouping model development and testing and make models more interpretable. A review of experimental results examining the execution of few element choice methods (Chi-squared, Information Gain, Mutual Data, and Symmetrical Uncertainty) coupled with classifiers such as guileless bayes, SVM, choice tree, and k-NN. The purpose of this paper is to investigate the effects of component determination strategies on different classifiers on image datasets. The concentrate also enables contrasting the general exhibition of the classifiers and techniques. The assessment of element determination techniques for image grouping with little example datasets should think about arrangement execution, dependability, and productivity. It is, consequently, a numerous rule navigation (MCDM) issue. However, there has been little examination in include determination assessment utilizing MCDM techniques that think about various standards. Subsequently, we use MCDM-based strategies for assessing highlight determination techniques for image arrangement with little example datasets. Trial review of five MCDM strategies is intended to compare and contrast the proposed approach with 10 component choice techniques, nine assessment measures for paired characterization, seven assessment measures for multi-class ordering, and three classifiers with 10 little datasets. We propose strategies for highlight determination based on the positioned effects of the five MCDM techniques. This study indicates the effectiveness of the utilized MCDM-based strategy in evaluating highlight determination techniques.
Geolocation Analysis Using Machine Learning
Authors: Sinha Sakshi Rajesh , Pundkar Prof. Sumedh
Published: October 2022

A new journey commences every time a student leaves his/her home for education or work thereby leading themselves to self-discovery and self-reliance. But along with new adventures comes various challenges such as unfamiliar health care systems, personal safety issues, financial problems, etc, but the major problem of them all is accommodation issues. Students and young adults often face difficulties when it comes to immigrating to new cities or states for pursuing higher studies from colleges or for work purposes. As different people have different priorities and interests, finding a suitable place that fits their budget and have easy access to their daily requirements for sustainable living becomes a challenge. The objective of this project is to create a system to find the best accommodation for the user in a particular city by classifying the user based on the preferences given by them such as budget, proximity to a certain location, daily necessities, etc. This system can be expanded and further be used for various purposes such as finding a suitable location for any business (for eg. restaurants/cafes or stationery shops are best suited near an educational institution) or for the best area of land for crop cultivation for maximum yield etc.
A Review on HRI for Child Learning
Authors: Morya Shubham , P Raja
Published: October 2022

Human robot interaction (HRI) becomes an effective method of interacting with kids. Many HRI's system are currently available. In this paper, a review of various robotic tutor system based on design aspects, safety aspects, mechanical and electronic aspects of robots, learning outcome of kids, type of interaction, configuration of various learning modules, real time behavior monitoring and socio centric aspect are presented in this paper. As the robot tutoring has several benefits over human tutoring because these kinds of system have various pre-installed learning modules so that without any human monitoring child learn its concept. The robotic system is now a days become very effective for the learner for real time applications
Computerized Reasoning Based Portable Following and Radio Wire Pointing in Satellite Earthly Organization
Authors: Sagar Sudeep , Shukla Siddharth , K A Akankasha , Mohanty Tejaswini , Shetty Surakshith , S G Spandana
Published: October 2022

Unique lately, versatile administrations have grown quickly and customary satellite-earthbound Networks have been not able to help them.We are confronted with the issues of how to find portable terminals precisely and process the information we gathered rapidly to diminish correspondence pressure. To tackle this issue, this paper concentrates on a pointing and following strategy in light of man-made reasoning for versatile stations and terminals in satellite-earthbound organization, to ensure that our versatile stations and terminals would be able access best receiving wire signal and experience the ill effects of different stations or terminals. A man-made intelligence based self-learning (ASL) network system is intended to help sifting and right unique testing information, portable following of versatile stations and terminals, and unaided satellite determination and receiving wire change plot. Profound learning of authentic data information of stations and terminals to accomplish continuous pointing and following, and foresee the dispersion of stations and terminals sooner or later in the future. At last, the ASL is contrasted with existing frameworks with measure their usefulness andconvenience.
Design and Implementation of Smart Shopping Trolley with Mobile Cart Application
Authors: Mariam Fiza , S P Niharika Nandi , B S Ganavi , B S Prof Gowrishankar
Published: October 2022

As there is a lot of advancement in the field of technology there are many eye-catching inventions in the domains of machine learning, artificial intelligence, internet of things and so on, due to these advancements, with the customer point of view people start expecting a lot. Nowadays people go to shopping on a daily basis. Customers have very little time to spare for standing in queues for billing purpose. In this paper, we are presenting a smart shopping cart with mobile cart application which is a prominent solution for the above-mentioned problem. this smart shopping cart comes with raspberry Pi controller, RFID Reader, RFID Tags, L298N Motor Drivers, Pi Camera, Load Cell and a Mobile Cart application. The customer needs scan the product using RFID reader which is attached to the cart, the load cell will get the weight of the items in cart and all the price details will be reflected in the online application. After all the items are scanned the final bill will be displayed on the application and the bill payment can be done using the same application
SELF-REGULATED LEARNING DAN OPENNESS TO EXPERIENCE TERHADAP ADAPTABILITAS KARIER REMAJA
Authors: Lucky Purwantini  , Selma Rene Mariki Rais
Published: October 2022

Remaja memiliki banyak tugas perkembangan. Beberapa diantaranya adalah mencapai kemandirian ekonomi dan dapat melakukan persiapan karier dengan melakukan perencanaan karier yang tepat. Penelitian ini bertujuan untuk menyelidiki dan menguji pengaruh self-regulated learning dan openness to experience terhadap adaptabilitas karier pada remaja. Responden pada penelitian ini adalah 386 siswa. Metode cluster sampling digunakan dalam penentuan responden. Pengumpulan data menggunalan metode wawancara dan kuesioner. Alat ukur yang digunakan adalah skala self-regulated learning dengan nilai r=0.929, skala big-inventory dengan nilai r= 0.883 dan skala adaptabilitas karier dengan nilai r= 0.925. Data penelitian dianalisis dengan menggunakan analisis regresi berganda dalam program SPSS for windows. Hasil analisis menunjukkan bahwa self regulated learning (β=0.225, ρ<0,05) dan openness to experience (β=0.685, ρ<0,05) secara bersama-sama memiliki pengaruh terhadap adaptabilitas karier.

Adolescents have many developmentals tasks, some of them are to achieve economic independence and can make career preparations by doing a proper career planning. The aims of the study are investigate and examine the effect of self-regulated learning and openness to experience in the career adaptability on adolescents. Respondents in this research were 386 students. Cluster sampling method was used to determine the respondents. Interviewe and questionnaire methode are applied in this study. The scale used was self-regulated learning scale with r= 0.929, big-five inventory scale with r=0.883 and career adaptability scale with r=0.925. Analysis data was conducted using multiple regresion method in SPSS for windows. The result shown that self regulated learning (β = 0.225, ρ <0.05) and openness to experience (β = 0.685, ρ <0.05) together had an effect in the career adaptability on adolescents.
RESILENSI AKADEMIK DAN KEPUASAN BELAJAR DARING DI MASA PANDEMI COVID-19 PADA MAHASISWA
Authors: Sabrini Mentari Rezeki  , Rianda Elvinawaty
Published: October 2022

Kepuasan belajar bagi mahasiswa sangat berpengaruh dalam penilaian akademik mahasiswa. Pembelajaran daring membuat mahasiswa dan dosen unutk lebih meningkatakan kreativitas dalam proses belajar mengajar. Pandemi covid-19 melakukan pembelajaran penggunaan dan pemanfaatan media, serta internet. Sebagian mahasiswa mengalami kesulitan untuk melakukan terutama untuk pelajaran yang dianggap membutuhkan penjelasan yang mendalam untuk itu sistem pembelajaran dosen harus disesuaikan dengan keadaan yang terjadi. Dibutuhkan resilensi akademik agar mahasiwa dapat lebih memahami mata kuliah yang disampaikan meskipun secara daring. Penelitian ini bertujuan untuk melihat hubungan antara resiliensi akademik dan kepuasan mahasiswa dalam pembelajaran daring pada masa pandemi COVID 19. Penelitian ini menggunakan pendekatan kuantitatif, dan korelasi pearson sebagai tehnik yang digunakan untuk menguji hipotesis. Sebanyak 171 mahasiswa yang menjadi partisipan. Partisipan penelitian direkrut dengan populasi sebanyak 300 mahasiswa,dengan mahasiswa aktif S1 yang memiliki pengalaman mengikuti proses belajar daring di Fakultas Psikologi Universitas Prima Indonesia. Berdasarkan hasil analisis korelasi antara resilensi dan kepuasan belajar diperoleh koefisien korelasi pearson sebesar 0,456 dengan sig sebesar 0,000 (p ˂ 0,05), hal ini menunjukkan bahwa adanya korelasi positif signifikan antara resilensi dan kepuasan belajar dan artinya hipotesis diterima.

Learning for students is very influential in student academic assessment. Bold learning makes students and lecturers to increase creativity in the teaching and learning process. The COVID-19 pandemic is learning about the use and use of media, as well as the internet. some students find it difficult to do especially for lessons that are considered to require in-depth explanation for that the learning system must be adapted to the circumstances that occur. Academic resilience is needed so that students can better understand the subjects delivered even though they are brave. This study aims to see the relationship between academic resilience and student satisfaction in bold learning during the COVID 19 pandemic. This study uses a quantitative approach, and Pearson correlation as a technique used to test hypotheses. A total of 171 students took part. Research participants were recruited with a population of 300 students, with active undergraduate students who have experience following a bold learning process at the Faculty of Psychology, Universitas Prima Indonesia. Based on the correlation analysis between resilience and learning satisfaction, the Pearson correlation coefficient is 0.456 with a sig of
“THE IMPACT OF COVID-19 ON RETAIL INVESTORS' SPENDING AND INVESTMENT BEHAVIOUR”
Authors: Nimbalkar Dr. Vipul
Published: October 2022

The extraordinarily infectious sickness corona virus has had a worldwide effect within the twelve months of 2020. This unpredictable and remarkable calamity has pushed economies to battle and strive. Most of the sectors within the financial system were significantly hit, which caused significant financial strain. There is a paradigm shift within the round drift of earnings, which has affected the way of life and modified human beings' spending and funding behaviour. This looks at objectives to understand how the COVID-19 pandemic has encouraged the economic decision-making and funding preferences of retail buyers. This study paper also researches the changes in the spending patterns of human beings for the duration of the lockdown because of COVID-19. A sample survey was performed via a based questionnaire to determine the effect of the pandemic on people's investment choices inside the town of the Pune region. A random sampling technique has been used to acquire the information for the study. The examine's findings display that human beings' existence and spending habits have changed significantly due to the pandemic worry and lockdown. The study additionally suggests that there has been a shift in the spending preferences of people toward healthy products and essentials.