bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementation of Public Information Disclosure in Creating Good Governance at Universitas Andalas
Authors: Fadila Azmaineti , Putera Roni Ekha , Ariany Ria
Published: October 2022

Implementation of Public Information Disclosure in Creating Good Governance at Andalas University. In line with the demands for reform, good governance comes in the form of a new transplant which is expected to be able to take care of the bureaucracy which has been represented as a bureaucracy full of acts of corruption and abuse of power. Transparency is an important aspect of governance that demands an increasingly open and transparent government system. The enactment of the Information Disclosure Act is one aspect to increase public oversight of the government system. Writing this journal is intended to be able to provide an overview by analyzing the implementation of public information disclosure in realizing good governance at Andalas University as a government institution that is to provide the information needed in the implementation of higher education. This study uses descriptive qualitative methods, while for data collection techniques in this research study the authors conducted interviews, and documentation. The results of the study indicate that the implementation of Public Information Disclosure in Creating Good Governance at Andalas University is still not running optimally, this is caused by communication that does not go well, inadequate resources.
Public Service Innovation Through the Implementation of the E-Boarding Pass System on Long Distance Trains at PT. Indonesian Railways (Persero)
Authors: Yudhanto Muhammad Ardi , Nurjaman Asep
Published: October 2022

This article aims to find out how to innovate the implementation of the e-boarding pass system at PT. Kereta Api Indonesia (Persero) whether delivered well to train users or not, until they switch from conventional ticket printing to ticket printing system via e-boarding pass with smartphone. The problem is focused on the e-boarding pass system which the author considers very innovative in utilizing technology that is growing every year, especially services must think how they optimize their services, one of which is by utilizing technology in changing the old system that is considered irrelevant to use and there are always problems in it by overhauling certain aspects such as purchasing and printing tickets manually through tellers are being changed to online based system ranging from purchasing or printing tickets. To approach the problem of the author using a theoretical reference from Cresswell by using a type of qualitative research that is a literature study that uses books and other literature as the main object, because the author uses literature research then the data obtained through books and literature that supports research. This paper concludes that policy innovations in the implementation of the e-boarding pass system whether it goes as expected.
Interactive Governance: Management of Potential Migrants in the Development of Nagari Sumanik, West Sumatra Province
Authors: Sari Miftahul Viona , Syamsurizaldi Syamsurizaldi , Koeswara Hendri
Published: October 2022

This study aims to see how the interaction process by Nagari Sumanik Government in managing migrants potentialities for the village  development from the interactive governance perspective according to Torfing, et  al. This research is using the qualitative type of research with a descriptive  approach. The results are indicating that in managing the migrants potentialities for the village development, they have been using the interactive governance perspective,  which can be seen in the institutional design variable that the village government  has designed the institutional according to their potential which is by incorporating the elements of Rantau into the vision and mission of the village of  Sumanik and forming the field of Rantau outside from the structure of the nagari  government and also involves migrants as the network actors for the village  development. In the Goal and Framework Steering variable, the relation between the village government and the migrants is coordination and more informal. In the process management variable, the Nagari Sumanik Government is taking the input and suggestions from migrants so that it can encourage innovation in development. In the direct participation variable, Nagari government has built the migrants trust by maintaining communication to provide the migrants understanding about the village conditions and the migrant support implementing programs that the benefits can be directly felt by the people of Nagari Sumanik. The interaction process is still dominated by the Wali Nagari and several special figures, and the Nagari social institutions involvements seems not enough. The function of this institution is important to optimize the migrant participations for the village development.
Evaluation of the Policy for Providing BLT Village Funds for Overcoming the Impact of the COVID-19 Pandemic in Tirto District, Pekalongan Regency
Authors: Wicaksana Hendika Dwinanda , Setiyono Budi , Martini Rina
Published: October 2022

The COVID-19 pandemic has forced the government in the Villages of Pacar and Dadirejo, Tirto Sub-district, Pekalongan Regency to use village funds to become BLT Village Funds to help communities affected by the pandemic. The purpose of this study is to evaluate the ongoing BLT Dana Desa policy. This study uses an exploratory qualitative approach, which describes in depth the policy of the Village Fund BLT in the Villages of Pacar and Dadirejo. data collection methods through interviews and documentation. As a result, the Pacar and Dadirejo governments did not succeed in implementing the Village Fund BLT policy properly, this was based on the public policy evaluation indicators from William N Dunn, such as effectiveness, efficiency, adequacy, equity, responsiveness.
Analysis of Business Development Services in Improving Taxpayer Compliance of Micro, Small and Medium Enterprises
Authors: Andrean Rudi , Setyowati Milla Sepliana
Published: October 2022

This study aims to analyze the role of implementing business development services (BDS) to improve the tax compliance of MSME taxpayers. To do this, a qualitative approach with the Library Research method is used. Data is collected by reviewing journals, conference publications, books, and other sources related to the research problem, such as news from credible sources, as well as final project research from another relevant research. The results of the study show that Business Development Services (BDS) is a form of business development services that facilitates MSME actors to grow. In Indonesia, the Director General of Taxes uses this program to encourage tax compliance by integrating it with tax socialization. This program then provides various event platforms that increase tax knowledge and perceptions of tax justice. The implication for the Tax Office is to be able to develop a BDS program that is as attractive as possible for MSMEs. This study provides originality as the first qualitative study to investigate the effect of BDS on tax compliance.
The Urgency of Research and Strengthening Entrepreneurship Policies in Generating Business Models in Ex-Conflict Areas
Authors: Zainal Suadi
Published: October 2022

Entrepreneurship contributes a lot to the economic growth of a regional area. In former conflict areas, entrepreneurship is a mechanism to facilitate prosperity and peace. The involvement of former conflict actors in micro, small and medium enterprises (MSMEs) provided them opportunities to enjoy peace dividends and repair the order of life damaged by prolonged conflict. Even so, failure of MSMEs become a problem because it causes economic stagnation and has the opportunity to create new conflict. Therefore, this paper aims to analyze the importance of research and strengthening policies related to entrepreneurship in former conflict areas. This study was conducted in Aceh Utara District using a qualitative approach. The data collection process carried out observation, interviews, and document studies. The empirical facts were analyzed by the stage of data reduction and data categorization, data display, and conclusion. The results showed that one of the causes of failure in MSMEs developments is weak policies and regulations related to community business empowerment. This fact was raised because the policies presented by the stakeholders were not based on research. Indeed, strengthening policies related to MSMEs can be done by making the results of studies and social mapping the primary basis for policymaking. Thus, the development of the MSMEs model for former conflict actors in Aceh has effects on increasing welfare and maintaining sustainable peace.
Fuzzy Partial Ordering
Authors: Kandwal Kuleep
Published: October 2022

In the expansive paper, added a cushioned fragmentary outlines and forsakenly demand the usage of warm assessment area and content with lacking assessment locale.
Corruption Control through Budget Maintenance
Authors: Reddy G. Kalyan Kumar , Srinivasan Dr.
Published: October 2022

Each nation authorities embody holds (Budget) for a selected cash associated 12 months in any occasion plan now no longer compasses to the same old occupants in listen such perpetual better confirmed knowledgeable made composed organized professionals and political trailblazers are omit blessings through the general public impact spending plan. We call for that an software live privy to the development of the cash conveyed through the nation lawmaking frame of a selected monetary 12 months and scholar manage dirtying. It offers the complete facts approximately the cash obliged a workplace, what is greater department clever and paintings clever. It is like way offers the facts approximately use of the organized coins completely. In the proposed shape completely unfold the coins associated plan for every department putting off the essentials. The apothegm of this undertaking is facts straightforwardness (clearness). In this manner, an general conventional occupant can aside from count on a significant element in controlling the beating.
Fuzzy Weakly Ordering
Authors: Kandwal Kuleep , Jain Poonam , Kevin Sherilyn
Published: October 2022

In the prevailing paper, delivered a fuzzy weakly ordering the use of fuzzy metric area and fuzzy partial metric area.
Analysing Reviewer’s Credibility and Sentiment to Build A Profile Model for Product Recommendation of User
Authors: Janarthanan Dr. Vignesh , Jain Esha Kumari , Kumar M. Sai Pavan , Redyy Hanumantha , Vemulawada Madhukar
Published: October 2022

Understanding a particular customers product needs, likes, and dislikes and to make an automation based on it is a very convolute job. This project augments heuristic-driven user interest profiling with reviewer credibility analysis and fine-grained feature sentiment analysis to conceive a vigorous recommendation methodology. The proposed credibility, interest and sentiment enhanced recommendation (CISER) model has five modules: candidate, feature extraction, reviewer credibility analysis, user interest mining, candidate feature sentiment assignment, and recommendation module. Review corpus is given as an input. The first module uses context and sentiment confidence to procure useful, crucial features.To detect the untrustworthy reviews and reviewers, reviewer credibility analysis proffers an approach to weigh reviews according to the parameters of credibility. The user interest mining module, uses fairness of review writing as heuristics for interest-pattern mining. The candidate feature sentiment assignment module comparesexisting features in review based on their fast Text sentiment polarity. The final module uses credible sentiment scoring for purchase recommendations. The proposed recommendation modelutilizes not only numeric reviewsbut also uses sentiment expressions connected with components, customer preference profiles, and reviewer credibility for quantitative analysis of various alternative products. The mean average precision (MAP@1) for CISER is 93%, and MAP@3 is 49%, which is better than current state-of-the-art systems.
Detection of Fraudulent data in IOT devices using Machine Learning framework
Authors: Sri Ms. P. Ramya , Jahanavi Guduru J , Pasupuleti Shreya , Sravya Itha , Vishal Madupu
Published: October 2022

The Internet of Things (IoT) refers to a network of physical objects, or "things," that are based in software and other technologies in order to communicate and exchange data with other devices and systems over the internet. These gadgets range from common domestic items to high-tech industrial instruments. Currently more than 7 millions users are connected today. Experts predict that by 2023, there will be more than 10 billion connected IoT devices, and by 2026, there will be 23 billion. IoT devices generate a vast volume of data in a variety of modalities, with differing data quality characterised by their speed in terms of time and location reliance. In such a scenario, machine learning algorithms can play a critical role in providing biotechnology-based security and permission, as well as anomaly detection to improve the usability and security of internet-of-things (IoT) platforms The detection of IoT devices using the Machine Learning framework is offered to achieve this goal. Five machine learning models are evaluated using various metrics with a vast collection of input feature sets in this ML framework. Each model calculates a spam score based on the input attributes that have been adjusted. This score represents the IoT device's dependability under various conditions. The proposed technique is validated using certain common appliances. The acquired findings support the suggested scheme's effectiveness in comparison to other current schemes.
Human Activity Recognition using CNN and Pretrained Machine Learning Models
Authors: Kumari Dr. N Vinaya , Talha MohdSalmanuddin , Vinod CH Venkata , Kamitikar Mithilesh , Pattar VaibhavM
Published: October 2022

People's lives are enriched by human activity recognition (HAR), which extracts action-level details about human behaviour from raw input data. There are a variety of uses for Human Activity Recognition, including elderly surveillance systems, abnormal behaviour, and so forth. However, deep learning models such as Convolutional Neural Networks have outperformed traditional machine learning methods. As a result of CNN, it is possible to extract features and reduce computational costs. Transfer Learning, on the other hand, refers to the use of pre-trained machine learning models that can be used to detect human activity using a special type of Artificial Neural Network known as Leveraging CNN. Resnet-34 Use of a CNN model can provide detection accuracy up to 96.95 percent for human activity recognition Numerous studies and research have been conducted on HAR. There are only a few models in the majority of the paper, however What we know is that the more data we have, the better the model and the more accurate the model will be.
Minimizing the Misinformation in Social Networks using Heuristic Greedy Algorithm
Authors: Jaganathan Dr. M. , Kumar Arun , Keerthana  , Kumar Naveen , Teja Shiva
Published: October 2022

In recent years, online social media has grown in popularity, and a vast volume of information has circulated over social media platforms, altering people's access to information. The credibility of information material is being questioned, and various types of misinformation are using social media to propagate quickly. The importance of network space administration and maintaining a trusted network environment cannot be overstated. In this paper, we look at a new challenge termed the activity minimization of misinformation influence (AMMI) problem, which involves removing a group of nodes from the network in order to reduce the total amount of misinformation interaction between nodes (TAMIN). To put it another way, the AMMI challenge is to choose K nodes from a given social network G to block in order to minimize the TAMIN.We demonstrate that the objective function is neither submodular nor supermodular, and we suggest a heuristic greedy algorithm (HGA) for removing the top K nodes.
Stock Price Prediction Using Machine Learning
Authors: Kumari Dr. N. Vinaya , Mokshit A. , Vineet  , Yashwanth
Published: October 2022

Shares in publicly traded companies, or equity shares, can be purchased and sold on the stock market. There are three basic types of stock market investors. All three types of investors: FII (foreign institutional investors), DII (domestic investors), and retail investors. Foreign Institutional Investors, such as mutual funds and banks, who have the experience and knowledge necessary to make their investment. Non-professional investors are known as retail investors. Machine learning is used to make an accurate prediction with less risk management in the stock market because there is a lot of uncertainty there. Through forecasting and LSTM (Long/Short Term Memory), we can theoretically predict stock prices through the use of machine learning. Effective stock market prediction gives us some suggestions on trading strategies, which is why stock market prediction is so important when it comes to investments. There is, however, no way to guarantee that the data will be 100% accurate because of future uncertainty in the field of study. For stock price prediction, this paper reviews studies on machine learning techniques and algorithms.
Forewarn Traffic Signal with Ambulance Detection By GPS and Light Standard Signal Using Machine Learning
Authors: Kumari Dr. N. Vinaya , Amrutha S. V. S , Prasanna A. A. S. Laxmi , Varma P. M. N. Ajay , Sujith K.
Published: October 2022

People's lives are enriched by human activity recognition (HAR), which extracts action-level details about human behaviour from raw input data. There are a variety of uses for Human Activity Recognition, including elderly surveillance systems, abnormal behaviour, and so forth. However, deep learning models such as Convolutional Neural Networks have outperformed traditional machine learning methods. As a result of CNN, it is possible to extract features and reduce computational costs. Transfer Learning, on the other hand, refers to the use of pre-trained machine learning models that can be used to detect human activity using a special type of Artificial Neural Network known as Leveraging CNN. Resnet-34 Use of a CNN model can provide detection accuracy up to 96.95 percent for human activity recognition Numerous studies and research have been conducted on HAR. There are only a few models in the majority of the paper, however What we know is that the more data we have, the better the model and the more accurate the model will be.
Image-Based Plant Disease Detection by Comparing Deep Learning and Machine Learning Algorithms
Authors: Vishwanath Dr A. , Swathi D. , Srikanya Y. , Basha K. Jeelan , Ramanjaneyulu B.
Published: October 2022

Plant diseases area unit the most issue two-faced in agriculture. As population can increase, the assembly of plants in addition can increase and due to plant diseases it's going to have a control on the assembly of food.The traditional methodology used for illness detection is knowledgeable visual observation. but it's very sophisticated to go look out the illness manually as a result of the time interval and knowledge of the plant's diseases. So, it had been necessary to develop a system that detected the illness in less time and value effective manner.We discuss the employment of machine learning and deep learning to sight diseases in plants automatically.Using a public dataset of fifty four,306 photos of pathological and healthy plant leaves collected below controlled conditions, we have a tendency to tend to coach a deep convolutional neural network to identify fourteen crop species and twenty six diseases (or absence thereof). The trained model achieves academic degree accuracy of 9ty nine.35% on a held-out take a glance at set, demonstrating the practicability of this approach. Overall, the approach of coaching job deep learning models on additional and additional large and publicly out there image datasets presents a clear path toward smartphone-assisted illness identification on a huge world scale.
Partial Replacement of Cement, Fine Aggregates & Coarse Aggregate with fly Ash, Steel Slag & Recycled Aggregates Respectively in Concrete
Authors: Kumar Dr. A. , H .j Pallavi , P .P Mr.Prasoon , Vani G. , Subashchandrabose Dr. R.
Published: October 2022

Around the world, a sizable number of people are employed in the construction industry. Today, development is occurring at an alarmingly rapid rate, which has led to an increase in the use of building materials that are already present in nature. The majority of the millions of tonnes of trash produced each year around the world is not recyclable. Additionally, recycling trash uses energy and harms the environment. Furthermore, both the accumulation of trash in the suburbs and the disposal of waste pose serious environmental risks. It is acceptable to accomplish two goals simultaneously by using waste material in the production of concrete, including the addition of advantageous properties. For this undertaking the globe. Today, development is occurring at an alarmingly rapid rate. Experimental findings from a study to determine the compressive strength of concrete with various cement replacements as well as fine and coarse particles were presented. An M-20 grade of concrete (1:1.8:3.16) with a water-cement ratio of 0.5 was developed, per IS-10262-2009. The findings show that cement, fine aggregates, and coarse aggregates can all be replaced with fly ash, steel slag, and recycled aggregates at percentages of 10%, 20%, and 30%, respectively, without compromising the concrete's compressive strength. To ascertain how much the strength will be increased, we are altering the materials one at a time. It stops when it reaches a specific percentage. To find out the mechanical properties of concrete, it will be increased and all of the ingredients will be changed at once.
An Application of a Deep Learning Algorithm for Detection of Accidents under bad CCTV Monitoring Conditions in Tunnels using ODTS &R-CNN
Authors: Kumar Dr. V. Senthil , Reddy L. Yashwanth , Vinnie Y. , Tejaswini N. , Raju A. Vishal
Published: October 2022

In this project, an Object Detection and Tracking System (ODTS) can be brought and used together with a famous deep gaining knowledge of community, the Faster Regional Convolution Neural Network (Faster R-CNN), for Object Detection and a Conventional Object Tracking set of rules for computerized detection and tracking of surprising occasions on CCTVs in tunnels, which can be probable to be (1) Wrong-Way Driving (WWD), (2) Stop, (three) Person out of the automobile in ODTS takes a video body in time as enter and makes use of Object Detection to generate Bounding Box (BBox) findings, evaluating the BBoxes of the modern and former video frames to assign a completely unique ID wide variety to every shifting and diagnosed item. This technique lets in you to display a shifting item in real-time, that's hard to do with conventional item detection frameworks. With a group of occasion pix in tunnels, a deep gaining knowledge of version in ODTS changed into educated to Average Precision (AP) values of zero.8479, zero.7161, and zero.9085 for goal items Car, Person, and Fire, respectively. The ODTS-primarily based totally Tunnel CCTV Accident Detection System changed into then examined the use of 4 twist of fate recordings, one for every twist of fate, the use of a educated deep gaining knowledge of version. As a consequence, inside 10 seconds, the gadget can locate all injuries. The maximum important truth is that once the education dataset grows larger, the detection functionality of ODTS can be robotically multiplied with none adjustments to the programme codes.
Evaluating Descriptive Answer Using Machine Learning And Natural Language Processing
Authors: Kumari T. Sai , Kumar Hemant , Ahmed Shaik , Sree Janvee , Sravani Josna
Published: October 2022

Assessment of the descriptive paper is a tough challenge. It requires lot of man power. In educational institutions a primary hassle is evaluation of descriptive type questions & answers. Using NLP this descriptive answer assessment proper answers and the pupil answer scripts. More marks is probably awarded, if the similarity withinside the answers is more. There are several advantages of using this automated assessment device as it permits in decreasing the time concerned about the resource of the usage of faculty to correct the descriptive papers. The examinations can be accomplished online, the answers can be evaluated right now and it would be beneficial for universities, schools and schools for academic purpose with the resource of the usage of presenting ease to colleges and the examination evaluation cell.
Future Methods Of Managing Privacy And Data Security At The Technical Age Cashless Society
Authors: Reddy Anuradha , Bindu K. , Kumar K. Arun , Yashwant J. , Adarsh J.
Published: October 2022

Financial transactions in a cashless global are carried out the usage of virtual statistics in place of real banknotes or coins (commonly an digital illustration of cash). [1] Cashless civilizations have existed for the reason that sunrise of human civilization, primarily based totally on barter and different varieties of exchange, and cashless transactions at the moment are possible utilizing credit score playing cards, debit playing cards, cellular bills, and virtual currencies which include bitcoin. However, this newsletter makes a speciality of the term "cashless society" withinside the feel of a motion toward, and implications of, a society wherein coins is changed with the aid of using its virtual equal—in different words, criminal tender (cash) exists, is recorded, and is most effective traded in digital virtual form. A few publications of movement may be coupled to attain a everlasting and applicable result for customers in a cashless society to boom privateness: A new kind of banking carrier that assigns randomised numbers to credit score playing cards, using blockchain to song all man or woman transactions, and a marketing campaign to train and tell key stakeholders approximately safety and privateness dangers so that they have got the gear and historical past expertise to guard their personal statistics earlier than coping with a overseas entity or different 1/3 events (i.e. cybersecurity departments, IT technicians, etc). Both blockchain and card variety randomization are liable to zero-day vulnerabilities, flaws, and ranging ranges of social acceptance. This exploratory observe makes use of a structures evaluation of cashless structures to perceive and have a look at a fixed of social and technical alternatives for a robust cashless gadget that protects customers' privateness even as keeping gadget safety. The statistics amassed and evaluated may be beneficial in uncovering flaws in present day facts integrity and safety procedures. In order to create preemptive countermeasures, it might be useful to study gift and destiny strategies of dealing with privateness and facts safety withinside the contemporary-day age. In a cashless gadget, this studies identifies essential techniques to keep away from the loss of private privateness.
Machine Learning Based Solution for an Effective Credit Card Fraud Detection
Authors: Kumar Mr. V. Naveen
Published: October 2022

Credit card utilization has been growing with the emergence of e-trade and different programs that permit bills to be made on-line. However, whilst credit score card is stolen or any fraudulent interest takes place, it effects in monetary issues to the cardboard holders. It additionally reasons problems to the provider of playing cards. Therefore, it's far crucial to have a mechanism to stumble on fraudulent on-line transactions. In this regard, there exists many answers as located withinside the literature. One such technique is to have ancient transactions divided into fraudulent and non-fraudulent transactions. This ought to assist educate classifiers to stumble on or suspect fraud transactions. These answers focused spending conduct of clients so that you can stumble on opportunity of fraud. In the present device, statistics mining method is accompanied with random forests to version the conduct of ordinary and fraudulent transactions for credit score card fraud detection. The trouble with the version is that it really works best with dataset this is best tuned. If dataset isn't always good, its overall performance is deteriorated. To conquer this trouble, on this project, a characteristic choice set of rules is proposed to beautify the overall performance of classifier. The proposed device additionally could have comparative have a look at with more than one classifiers like Random Forests and SVM to assess the characteristic choice technique
Geoinformation mapping of sor depression in the Northwestern Caspian
Authors: Berdengalieva Asel , Shinkarenko Stanislav , Vypritskiy Artem
Published: October 2022

The article discusses the results of mapping sor depressions in the Sarpinskaya lowland based on geoinformation technologies and Sentinel-2 satellite data. The research area is subject to desertification processes, which are expressed in a decrease in the productivity and density of vegetation up to its complete destruction as a result of uncontrolled pasture loads and climatic fluctuations. The consequence of these processes is an increase in the area of shifting sands, intensification of dust storms and economic losses. For these reasons, it is extremely important to timely determine the centers of desertification in order to take measures to limit pasture loads on them and carry out phytomelioration. Satellite data are widely used to monitor desertification processes. However, the presence of natural areas devoid of vegetation due to their genesis—solonchaks and sors—is practically not considered. Attributing these categories to desertification is incorrect; for this reason, they should be mapped separately and not considered in the future. Sory (sor depressions) is a closed arid drainless landform with a temporary drying up reservoir. The area of sor depressions is constant; only the ratio of areas of water, salt crust, mud, and vegetation along the periphery changes. As the water dries up and forms a white salt crust during the growing season, the albedo of the sor surface increases, due to which they can be classified as lands subject to desertification in the classification of satellite images. In total, as a result of the work, about 7 thousand objects were identified: sors, solonchaks and dry ilmens with a total area of 143 thousand hectares. More than half of the total share of all depressions has an elongated shape in the sublatitudinal direction. Sor depressions with a depth of 1–2 m predominate compared to the surrounding area. There are also salt marshes that are not expressed in relief or rise up to 1 m above the surroundings. The results obtained can be used in geomorphological and soil studies and will also allow more accurate satellite monitoring of desertification processes in the region.
The hybrid method of water levels and volumes reconstructing in the Arakhley lake (Trans-Baikal territory) according to Landsat remote sensing data with unmanned aerial vehicles images fusion
Authors: Kurganovich Konstantin , Kochev Denis , Bosov Maxim
Published: October 2022

The use of a hybrid method for reconstructing water levels and volumes of water mass in a reservoir is considered on the example of the Arakhley Lake of the Trans-Baikal Territory. The method makes it possible to obtain high spatial resolution cuts of water levels on the relief based on satellite images of the Landsat system of different time intervals and images from unmanned aerial vehicles (UAVs) as a source of a highly detailed digital elevation model. As a result of processing the Landsat satellite data, the values of the Arakhley Lake surface areas for the period 1987–2018 were obtained. Based on the results of the UAV survey, the water levels in the lake were extracted according to the survey dates corresponding to the areas. The root mean square error of water level determination (RMSE) was 0.23 m, which is lower than the horizontal resolution of the elevation model (0.3 m) obtained from the UAV data. Also, the characteristics of the water mass volume were obtained for the variable part of the lake volume for the period 1987–2018. The use of the hybrid method considered in the article will solve the problem of insufficient or complete absence of data on the long-term water regime of unexplored lakes and reservoirs. Evaluation of the possibilities of using this technology by comparing with the instrumental characteristics of water levels at the regime point of hydrological observations, shows the boundaries of its use, advantages and disadvantages. At the same time, the main advantage can be recognized as the possibility of obtaining time series of changes in levels and volumes over the past years in those lakes and reservoirs where there have never been ground observations and are unlikely to be. In the case of establishing the dependences of the water mass volume on the areas of the water surface, it becomes possible to perform operational hydrological monitoring of water bodies using only Landsat satellite images.
Use of UAV Geoscan 201 for surveying a linear object of the Khiva–Urgench highway
Authors: Shukina Olga , Ruziev Azizjon , Ergashev Mansur
Published: October 2022

The aim of this work is to perform a linear aerial survey of the Khiva–Urgench highway using the Geoscan 210 UAV, the results of which will create orthophotomaps at a scale of 1:1 000, which are necessary for designing bicycle and sidewalk paths along this route. Surveyors of the Applied Geodesy Department of UZGASHKLITI performed a field planned-altitude reference at this object. 48 control points were determined. Characteristic solid contours along the route were chosen as reference points. The binding of control points was carried out from the starting points of the State Geodetic Networks, using satellite receivers (SN 5242498595, 5243499034, 4827155394) in the RTK mode in a radial way, by the calibration method on the ground. The coverage area was 17.4 sq. km. Aerial photography was carried out at a height of 211 m by a Geoscan 201 unmanned aerial vehicle at a scale of 1:500 with a DSC RXIR digital camera with a focal length of 35 mm. Forward overlap of aerial photographs was 70 %, and lateral—50 %. 4 aerial routes were made at this facility, the photography basis was 42 m. The number of aerial photographs at the facility was 3 868 pieces, and the coverage of aerial photography was 300 m. The images and their EXIF files were georeferenced by performing field processing using the Geoscan Planner program. Before the start of field work, the GNSS receiver (Trimble R6) was installed at a known point on the ground and started in static mode (10 Hz). The aircraft has a GNSS receiver (Topcon) operating in fast static mode (10 Hz). The GNSS data on the ground and on board the aircraft are balanced. Image center coordinates are calculated from the base station GNSS receiver data using MAGNET Tools software. Then the data is imported into Agisoft Metashape software for automatic processing. In this case, the coordinates of the image centers were recalculated from the WGS-84 system into the SK-42 (Pulkovo 1942) system adopted in our country. The process of optimization and alignment of aerial photographs was carried out. After that, in order to obtain a high image quality, the orthophoto map was built using a height map built on the basis of a dense point cloud. The result of the work performed are orthophoto maps for the Khiva–Urgench highway, which will be used to design the location of bicycle and sidewalk paths.
Festival Anak Shaleh STIQ (FASTIQ) Desa Awayan Hilir Kabupaten Balangan
Authors: Syarifuddin Syarifuddin , Nurhafidzah Maryam , Halidah Nor , Winda Winda , Rahmita Rahmita
Published: October 2022

Program Kuliah Kerja Nyata (KKN) ini bertujuan untuk melakukan pengabdian kepada masyarakat di desa Awayan Hilir. Melalui Kuliah Kerja Nyata (KKN) diharapkan memberikan semangat dan motivasi terhadap anak-anak dalam menghadapi pandemi covid-19 ini. Festival Anak Shaleh STIQ (FASTIQ) diadakan selama satu hari sekaligus dengan acara pembagian hadiah diakhir acara. Lomba yang disertakan ada empat: lomba tahfidz, lomba tartil, lomba adzan dan lomba fashion show. Kegiatan lomba ini dapat memberikan dorongan kepada anak-anak agar kembali semangat dan bergembira serta melatih kemampuan bersosialisasi terhadap sesama, selain itu juga lomba Festival Anak Shaleh STIQ (FASTIQ) akan sangat memberikan dampak positif terhadap anak-anak agar berusaha lebih melatih kemampuan dibidangnya masing-masing.
The Special Bilingual Education Program: Pace-Setter for a Harmonized Educational System in Cameroon
Authors: Ayuk Judith Nkongho
Published: October 2022

This article considers the government’s strategy to densify young learners’ education in their Second Language (L2) through a Special Bilingual Education Program (SBEP) as a pace-setter for harmonizing the Anglo-saxon and the French subsystems of education. This article is guided by Foucault’s (1997) theoretical perspective of Governmentality which according to Dean (1999), identifies an approach towards thinking about the state and different mentalities of government. Three hundred and eighty (316) informants from the SBEP centres provided data for this study through Questionnaires, Interviews and Observations. The results revealed that: there is a SBEP where learners are partially immersed in their L2 with a shift in teaching approach from the Skill-Based Approach (SBA) to the Competency-Based Approach (CBA); learners, teachers and parents have a positive attitude towards the program; parents from Francophone homes had already taken the lead in fully immersing their children in the Anglo-saxon subsystem of education; and teachers and learners have made proposals to ameliorate and maintain the program. This article recommends that rather than stick to the Arts Series, the program should consider including learners from both the Arts and Science Series in the Second Cycle.
Hepatoprotective Potential of Caesalpinia bonducella: Molecular Insight
Authors: Bhatt Mahesh , Malik Jitender K
Published: October 2022

Abstract: Liver fibrosis is a wound healing process initiated in response to chronic liver damage caused by viruses, toxins, and hepatotoxic drugs. The disease is characterized by inflammation followed by deposition of extracellular matrix proteins to form scar tissue. Ephrin receptor A2 (EphA2) has been identified as a host cofactor for hepatitis C virus (HCV) entry. The plant Caesalpinia bonducella is used in a variety of systems a traditional medicine used to treat human ailments and affiliation prickly shrub belonging to the Caesalpiniaceae family found throughout the world, especially tropical region. It is a very valuable medicinal plant because all parts of the plant have medicinal properties. It was like traditional Indian herbal medicine considered an important therapeutic modality for the treatment of various diseases. As per literature survey the plants containing kaempferol and quercetin-3-methylether are traditionally utilized for the cure of cancer and liver related disorders from the immortal time. The exact mechanism of action for the hepatoprotective action of kaempferol and quercetin-3-methylether was still not revealed. With intent to propose the most probable mechanism of action of kaempferol and quercetin-3-methylether the docking based computational analysis has been performed against the hepatoprotective drug targets like PPARα enzyme.
Percentage Fertility of Female Wistar Rats Treated with Extracts of Persea americana
Authors: Obiandu Chibuike , Owhorji Bright I. , Oriji Eunice I. , Emeghara Gideon I. , Reuben Edith
Published: October 2022

The purpose of this research study was to investigate the effects of ethanolic stem bark extract of Persea americana on some reproductive parameters of female Wistar rats. In this study, female Wistar rats were randomly assigned into three (3) groups of 5 rats each. The control group (Group 1) was given distilled water. Group 2 received 200mg/kg of the extract and group 3 received 400mg/kg of the extract daily for a period of 21 days following acclimatization. The female rats were cohabited with males in the ratio 2:1 (M:F) for 10 days. Blood samples were collected and some tissues harvested at sacrifice. The statistical analysis was done using Statistical Package for Social Sciences (SPSS). One-way analysis of variance (ANOVA) test was used to compare groups followed by post-hoc testing to determine whether there were significant differences between the control and treatment groups. P-value less than 0.05 was considered significant and result presented as Mean±SEM. The result showed that the extract of Persea americana caused stimulatory effect on anterior pituitary synthesis of luteinizing hormone (LH) and follicle stimulating hormone (FSH) and may have also caused changes in the gonads leading to decreased gonadal hormone synthesis (estrogen and progesterone). The percentage fertility of the female Wistar rats was significantly reduced suggesting that the stem bark extract of Persea americana possess antifertility effects.
Adhesive Capsulitis Motor and Sensory Stimulation during Radiofrequency Treatment
Authors: Mousa Hussein Imran
Published: October 2022

Background: Adhesive Capsulitis is a frequent issue that can cause serious impairment. There have been many different treatments explored, with encouraging outcomes, but the effectiveness of these interventions is not well supported by the available data. Anecdotally, pulsed radiofrequency (PRF) to the suprascapular nerve (SSN) has been described as a safe and effective procedure. In addition to the PRF SSN, this study provides evidence of therapeutic motor and sensory stimulation. Methods: 110 patients with adhesive capsulitis underwent percutaneous PRF to the SSN under ultrasound guidance, and the results were prospectively evaluated. Patients were split into two groups. The SSN was demonstrated by the first group (60) in the suprascapular region. A second group of 50 people used a radio frequency equipment to apply motor and sensory stimulation (MSS) cycles to the proximal SSN in the supraclavicular area in addition to the PRF. At 2, 8, and 12 weeks, respectively, the pain was monitored using the Visual Analog Scale and active range of motion (AROM) in the shoulder. Results: Patients in both groups reported significantly substantial reductions in pain scores and improved movement all-time points as compared to pre-procedure scores (P<0.001). Supraclavicular pRF with stimulation significantly reduced pain scores and improved shoulder motions at 2 and 4 weeks compared to suprascapular PRF with stimulation (p<0.05). Regarded 12-month follow-up group showed a substantial improvement in shoulder motions (p<0.05), but there was no discernible difference in pain level. Conclusion Proximal PRF SSN with MSS demonstrated encouraging outcomes for early pain relief and enhancement of shoulder functioning. There are financial advantages. Without the need for hospitalization or extended physical therapy sessions, return to work sooner. However, the sample size was too tiny to allow for any significant interpretation.
Pengaruh Insulin Sliding Scale terhadap Episode Hipoglikemia dan Hiperglikemia Pasien DM Tipe 2 RSA UGM
Authors: Manullang Anna Maria , Wiiedyaningsih Chairun , Probosuseno Probosuseno
Published: October 2022

Diabetes mellitus tipe 2 adalah penyakit metabolik akibat terjadinya resistensi insulin disertai defisiensi insulin relatif sehingga memerlukan insulin yang dapat menurunkan glukosa darah dengan kerja cepat. Insulin sliding scale merupakan metode untuk mendapatkan dosis insulin yang sesuai di mana memiliki risiko fluktuasi kadar glukosa darah sehingga terjadinya hipoglikemia (<70 mg/dl). Penelitian ini bertujuan untuk mengetahui pengaruh terhadap pengendalian kadar glukosa darah dan resiko hipoglikemia pada pasien diabetes mellitus tipe 2 di RSA UGM. Penelitian ini merupakan penelitian cross sectional dan data penelitian ini diambil secara retrospektif. Subjek penelitian adalah pasien diabetes mellitus tipe 2 yang masuk rawat inap periode Maret 2021 - Oktober 2021 yang teridentifikasi menggunakan insulin sliding scale.  Jumlah pasien pada penelitian adalah 97. Selanjutnya di lakukan evaluasi episode kejadian hipoglikemia dan hiperglikemia. Kadar glukosa darah sewaktu pasien menentukan episode hipoglikemia dan hiperglikemia. Uji statistik regresi logistik berganda digunakan untuk hubungan pengaruh variabel jenis obat. Hasil penelitian menyatakan insulin sliding scale yang digunakan terdiri dari 3 kelompok, yaitu insulin sliding scale tunggal (41.2%), kombinasi insulin sliding scale dengan long acting insulin (55.7%), dan kombinasi insulin sliding scale dengan premixed insulin (3.1%). Hasil analisis didapatkan tidak terdapat jenis terapi insulin sliding scale yang signifikan memengaruhi pengendalian kadar glukosa darah (p>0,05). Tingkat episode hipoglikemia dan hiperglikemia masing-masing adalah 1,21 dan 54,46 per 100 pengukuran kadar glukosa darah. Episode hiperglikemia lebih sering terjadi pada pasien diabetes mellitus tipe 2 yang mendapatkan terapi insulin sliding scale.
Product Recommendation System using Machine Learning and Robotic Process Automation
Authors: B.P Darshan , M Shalmali , M.S Ziyad , T.K Shivaprasad
Published: October 2022

Recent research has increasingly indicated that social media branding can bring about desired benefits for firms. Firms are turning to social media to promote their products and to engage their customers. Companies try to achieve this by grabbing the customer's attention towards their products through advertisements. But the publicity of their products does not reach the right audience. This paper describes a technique which automates the business processes in advertising the products in the social media through robotic processing automation tool where the inputs are taken from the company. The robot then processes this data in such a way that the product is advertised automatically displayed on customer’s social media feed, so that the company grabs their customer attention effectively. This software makes smart advertisers can target more users for the given budget, which makes the company maximize the number of reached unique preferred users. Further product recommendation can be done for different products with different websites so that based on product name websites can be looped. Improvements to this recommendation method can also be done by considering other elements like named-entities, people and their occupation
Region-of-Interest Based Transfer Learning Assisted Framework for Skin Cancer Detection
Authors: Shirke Ms. Prajakta P. , Gadekar Dr. Amit R.
Published: October 2022

Melanoma, or skin cancer, is usually detected visually from dermoscopic pictures, which is a time-consuming and difficult job for the dermatologist. Existing systems either utilize classic machine learning models that concentrate on hand-picked acceptable features, or deep learning-based approaches that learn features from full pictures. Melanoma, or skin cancer, is usually detected visually from dermoscopic pictures, which is a time-consuming and difficult job for the dermatologist. Due to many artifacts such as poor contrast, diverse noise, presence of hair, fiber, and air bubbles, etc., such a visual examination with the naked eye for skin malignancies is tough and onerous. This paper provides a robust and automated system for Skin Lesion Classification (SLC), in which image augmentation, Deep Convolutional Neural Network (DCNN), and transfer learning are all combined. Our lesion classification experiments show that the suggested technique can effectively classify skin cancer with a high degree of accuracy, and that it can also identify skin lesions for melanoma detection