bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Temperature Variations on Rigid Pavement Concrete Slabs
Authors: Mahfuda Anno , Siswosukarto Suprapto , Suhendro Bambang
Published: May 2023

This research aims to assess the effect of temperature gradient developed within the concrete slab of rigid pavement, and to investigate its impact when incorporated with the traffic load, and the heat transfer pattern. The rigid pavement model considers an isotropic, uniform, and linear-elastic schemes to simulate the material properties. A numerical analysis approach was employed using Abaqus software incorporated with the 3D Solid model. The traffic loads were obtained from the field surveys, while the temperature of the slabs was measured directly on the site. The dimension of the rigid panel is 2.75 m in width, 5 m long, slab thickness of 25 cm, and concrete specification of 41.33 MPa. The results showed that the temperature gradient produced a significant impact on stress development within the concrete slab of rigid pavement. It was observed that the temperature gradient during the daytime generated higher stress than at night, with a value reaching the MOR (Modulus of Rupture). The exposure of the rigid pavement to 500C tends to produce a principle slab stress of 2.395 MPa, while 1.31 MPa was developed due to the traffic load. When the two factors were combined, the concrete slab acquired a maximum principle stress of 3.322 MPa, which is close to the MOR of 83.34% fa. These results showed that the pavement is capable of withstanding stress from temperature gradient and traffic load as indicated by the ratio of less than one (1). However, this ratio is high for fatigue failure mitigation purposes, and this reduces the quality of life of the rigid pavement.
Design of Stone Column to Mitigate Soil Liquefaction: Cases Study of Yogyakarta International Airport
Authors: Hartono Nicholas , Fathani Teuku Faisal
Published: May 2023

A low-to-medium cohesionless soil with low fines content was predominantly observed at the surfaces of Yogyakarta International Airport (YIA). The condition exposed subsoil of YIA to Liquefaction in addition to its location on a high seismic zone which has increased the likelihood of massive ground shaking. This means it is necessary to improve soil condition and vibro-replacement using stone column was selected as the appropriate method due to its recent popularity for the enhancement of sandy ground. Stone column has the ability to reduce the Cyclic Stress Ratio (CSR) of liquefiable soil and can be reliably evaluated. Therefore, this study was conducted to evaluate the risk of Liquefaction at YIA by adopting the SPT-based Liquefaction triggering procedure and presuming its manifestation using Liquefaction Severity Index (LSI). It is pertinent to state that the theoretical approach introduced by Priebe was used to design the geometry and center-to-center distance of stone column. The results were presented in the form of maps with a 50 m × 50 m grid size which include the cut and fill, LSI before and after improvement, stone column spacing, as well as stone column depth. It was discovered that the triangular spacing required for stone column ranged from 1.25 m to 2.5 m while the maximum depth was found to be 6 m. Moreover, stone column inclusion efficiently reduced the severity of Liquefaction from medium to very low for the areas studied. However, stone column has several limitations and this means a combination of soil improvement methods needs to be applied to areas with moderate LSI.
Establishing a Simple-yet-effective Approach of Early Warning System for Storm-Induced Earth-Filled Dam-Break Cases in Data-sparse Region
Authors: Yudianto Doddi , Wiguna Farrell , Ginting Bobby Minola , Wicaksono Albert , Yuebo Xie
Published: May 2023

Historically, the occurrence of dam-break cases has been proven to cause significant loss of life and economical damage. Apart from the catastrophic nature of dam-breaks, the absence of a robust disaster prevention system exacerbates the disasters that occur. This study proposes an Early Warning System (EWS) to mitigate the impact of dam-break disasters. However, predicting the occurrence of such disasters is challenging, specifically in areas like Indonesia, where comprehensive data recording is lacking. While it may be difficult to predict the occurrence of a sunny day break, the storm-induced break is more predictable. Therefore, this study proposes a simple yet effective macro-based EWS for Earth-Filled Dam-Break Cases using a macro approach based on the Evacuation Clearance Time (ECT). By comparing the ECT value with the arrival time of the floods from the affected areas, additional evacuation time can be obtained, which will be used to determine the EWS. The proposed EWS for Cengklik Dam is given in three levels of warning indicated by the reservoir water level at +141.36 m, +141.40 m, and +141.45 m. With the proposed EWS, the results show that 100% of people are expected to reach the evacuation point safely. The case study shows that the proposed EWS can significantly reduce the risk impact of the dam-break events.
Investigating the Capability of HEC-RAS Model for Tsunami Simulation
Authors: Amaliah Rifa , Ginting Bobby Minola
Published: May 2023

This study highlights the simulation of tsunami cases using HEC-RAS 6.1. The primary aim is to evaluate the capability of the software in performing tsunami simulation due to its standalone computational framework (pre-processing, execution, and post-processing stages), making the modeling process interactive. The model accuracy was tested against some benchmark cases of wave propagation, including analytical solutions, laboratory experiments, and field measurements. The results showed HEC-RAS was capable of modeling tsunami propagation. The maximum elevation and velocity magnitude were accurately computed for the analytical cases. Furthermore, sufficiently accurate results were obtained for the laboratory case, where the maximum elevation was properly computed. For the field cases, the wave arrival time and the fluctuations of water surface and velocity were appropriately calculated. The Root Mean Square Error values between the numerical results and the analytical/observed data were relatively low below 30%, with the Pearson Product Moment Correlation values ranging from 52–99%. In addition to its eminence, a drawback was found regarding the graphical user interface (GUI) of HEC-RAS for the input of boundary conditions. These findings will be beneficial for the coastal engineering community and the continuous development of HEC-RAS.
Wastewater Characterization and pH Neutralizing Effect of Adsorbents: A Case Study of Washed Concrete Wastewater from a Ready-Mix Plant
Authors: Adhin Harum Wulaningtyas  , Ni Nyoman Nepi Marleni
Published: May 2023

This study aims to characterize washed concrete wastewater and examine the effectiveness of three different adsorbents in reducing its high alkalinity and metal contents. It is important to note that proper treatment is essential before discharging wastewater into water bodies to prevent any negative impact on the environment. Therefore, in this study, an adsorption scenario was conducted to obtain optimum treatment for washed concrete wastewater. The objectives of this study are as follows (1) to determine the typical characteristics of washed concrete wastewater based on the parameters outlined in the Regulation of the Ministry of Environment of Indonesia No 5 of 2014 and (2) to assess the performance of different adsorbents. Three wastewater samples were obtained from a ready-mix plant and then tested in the laboratory. The initial test was conducted to identify influent characteristics, and from this test, it was found that only the pH level exceeded the specified standard. Following this, the study then assessed the ability of three adsorbents to reduce the pH level in washed concrete wastewater using the batch test in Duplo. The pH level was measured at 0.25, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, and 24 hours. The three adsorbents tested were activated carbon, clay brick, and dried domestic sewage sludge. The result shows that dried domestic sewage sludge was the most effective at reducing alkaline wastewater due to its acidic pH. Therefore, it has the potential to replace other commercial adsorbents and reduce the problem of sludge disposal. Further research on this material is recommended, such as evaluating its performance in a more solid form, such as brick, and assessing its contamination potential.
Methods to Determine Ductility of Structural Members: A Review
Authors: Ling Jen Hua , Lim Yong Tat , Jusli Euniza
Published: May 2023

Ductility plays a crucial role in ensuring the safety of a structure, as its inadequacy can lead to sudden and brittle failure. Despite its significance, there is no explicit method for determining, leading to inconsistency and confusion in selecting appropriate techniques. Misjudging a structure’s ductile behaviour can have catastrophic consequences. Therefore, this study examined several preliminary studies and identified twenty-one methods for computing ductility indices. These indices were categorized into three types, namely conventional, displacement-based, and energy-based. The conventional ductility indices are commonly applied to steel-reinforced members, deformation-based ductility indices to FRP-reinforced members, and energy-based ductility indices to earthquake-resistant and static-load structures. Conventional ductility indices are specific to ductile reinforcements, while displacement-based and energy-based ductility indices apply to both ductile and non-ductile reinforcements. However, different calculation methods can lead to significant variations in the computed ductility, particularly for those involving the first crack, and load factor, thereby leading to different ductility requirements for ensuring structural safety. Additionally, not all methods are explicit, and it is crucial to avoid indiscriminately applying requirements from one method to another.
A Few Words about the Market
Authors: Franjic Sinisa
Published: May 2023

The market is a place where supply and demand meet. Buying and selling can be done without the presence of goods (on stock exchanges and other markets), and even without direct contact between buyers and sellers. Buying and selling can be done according to the catalog, by phone, fax, internet, etc. Therefore, the market is defined as a constant and organized form of bringing supply into contact with the demand for goods and services. At the same time, the market is a mechanism that regulates the relations between sellers and buyers in the conditions in which the participants in the exchange or sale achieve their goals and interests due to which they enter into mutual relations.
Antiacne Herbal Cream
Authors: Lad Rohini , Pagire Dipali
Published: May 2023

Abstract: Objective- To formulate and evaluate herbal cream using Aloe Vera gel, Sandalwood Powder , extracts of Neem (Azadirachta indica) and Tulsi (Ocimumtenuiflorum) to give antiacne effect. Method: A cream with an oil-in-water (O/W) emulsion base (semisolid formulation) was created. The oil phase (Part A) was heated to 75° C while the emulsifier (bees wax) and other oil soluble components (liquid paraffin, rose oil) were dissolved in it. The water soluble additives and preservatives components (aloe vera ethanol extract, vitamin C, borax, methyl paraben, sandalwood, and Neem and Tulsi were dissolved and heated to 75° C in the aqueous phase (Part B). Once heated,parts of the aqueous phase were introduced to the oil phase while stirring continuously till cooling of Emulsifier was used. Results: The formulation showed good appearance, pH, viscosity, phase separation. Conclusion: All four herbal components demonstrated noticeably distinct behaviours. Based on the findings, we may infer that all of the formulations were stable and safe to apply to the skin, with acceptable viscosity and no evidence of phase separation. Additionally, the formulation had no redness, Itching and erythrema .When conducting the irritancy testing, they were simple to clean. The formula read at room temperature, stable
Navigation and Reservation Based Smart Parking Platfrom For Smart Cities
Authors: Nosaria Anjali , Singh Heena , Upadhyay Aviral , Pandey Aditi
Published: May 2023

Abstract: In the modern era of technology, smart devices are becoming more common in everyday life. To find a free parking slot is the most difficult task in our cities The principal role of this research paper is to analyze smart parking solutions from a technical perspective, underlining the systems and sensors that are available, as documented in the literature. In this paper we have proposed a navigation and reservation based smart car parking system. The proposed system is being controlled by an app so as to reduce human intervention. To book the slot for parking is being done with the help of web application, some amount of charges is deducted through wallet. We can navigate to the reserved slot location by using google map. The proposed method makes our life more easier and hassles free.
Design and Fabrication of Multipurpose Semi-Automatic Bag Filling Machine for Agricultural Cereals in Mills
Authors: M Naveen Kumar , C Saravana Prabu , S Arun Prasanth
Published: May 2023

Abstract: In mills and agricultural fields grains are collected by means of number of labors and more time consumption. In order to limit the time and work wages a simple mechanical heaping machine is been constructed to handle with less labors. The main objective of this project is to heap the paddy and also to clean the garden in an effective manner with simple adjustments and less remuneration. In this machine the driving shaft of the wheel is welded with sprockets on either side of the shaft. Grain collecting machines it is operated fully in a mechanical means. In modern grain handling machines, the grains are collected by means of vacuum suction and it requires external power supply.
ATM Network Technologies
Authors: Raju Vaishnavi Shravan A , Nagaraja GS
Published: May 2023

Abstract: ATM networks use a range of technologies, including wired and wireless communication systems, advanced security features, and specialized hardware components to provide various financial services to customers. Traffic management techniques are also employed to ensure efficient use of network resources. ABR (Available Bit Rate) traffic management is a specific technique that allows the network to analyze traffic levels and adjust bandwidth allocation in real-time, ensuring optimal network performance. By implementing these technologies, ATM networks are able to provide a high-quality user experience while managing network traffic in an efficient and effective manner.
Planning, Design and Estimation of Waste Water Treatment Plant Sector 1 of Virat Khand
Authors: Singh Abhirat , Gond Abhishek Kumar , Bhaskar Adarsh , Verma Aditya , Upadhyay Mr. Avinash Kumar
Published: May 2023

Abstract: This study's primary goal is to carry out the design of a sewage treatment facility for Lucknow's Virat Khand Sector 1. due to constant domestic and municipal sewage will be produced at a faster rate as the population grows. All species become sick from the foul stench that sewage produces. To prevent this however, appropriate treatment is required prior to disposal on land in order to utilise the treated water and avoid dumping sewage directly into natural resources, which ultimately lowers the demand for fresh water as a whole. Its goal is to generate solid waste and fluid waste that are safe for the environment and can be recycled or disposed of. In a single day, how much sewage was produced overall, based on the anticipated population of Virat Khand Sector 1 over the following 20 years? As a result, the sewage generation in the Virat Khand area is the main topic of this study, and a sewage treatment plant is constructed in accordance with it. It is suggested that the different parts of the sewage treatment plant be designed taking into account the various standards and allowable limits of treated sewage water. Screening, a grit chamber, a main sedimentation tank, a biological reactor, a secondary clarifier, an activated sludge tank, and drying beds are some of the parts of a sewage treatment plant.
Machine-Learning Approach for Predicting Harmful Diseases using Big Data and IoT: A Review
Authors: Pandey Ragini
Published: May 2023

Abstract: The magnitude of the enormous quantity of data in the healthcare sector is currently on the order of petabytes, and it is expanding exponentially. The massive increase of data has resulted in a number of issues with computing, storage, and transfer. With the aid of a conventional relational database system, this type of data may be evaluated and processed. Moreover, structured data can only be processed by standard database systems. Big data, on the other hand, stores unstructured data. ICT would be able to assist society in a better storage with invention of new and effective mechanisms for the storage and accessing of the information. ICT implementation in the healthcare sector is referred to as eHealth. The processing of data, subsequent analysis, and enhancement of the decision-making processes would all benefit from application in the health care sector in order to gather better treatment options for diseases' symptoms.
EcoBrick: A Waste Plastic Used As Construction Material
Authors: Gund Pruthviraj , Pawar Sandesh Sanjay , Patil Anil Laxman , Sakpal Shubham Premnath
Published: May 2023

Abstract: In this project we try to overcome the problem associated with plastic waste. In India huge amount of plastics are used for various purposes such as for making of water bottle, soda bottles & bag etc. which are not disposable. Because of these various problems occurs so we use waste plastic bottles for making of bricks by the various ways which are discussed below. After studying the problem we developed the effective way to overcome this problem. Bottle brick are light in weight and withstand high amount of load or pressure. Eco-bricks, polyethylene terephthalate (PET) bottles filled with mixed inorganic waste, have become a low cost construction material and a valid recycling method to reduce waste disposal in regions where industrial recycling is not yet available. Because Eco-bricks are filled with mixed recovered materials, potential recycling of its constituents is difficult at the end of its life.
Solar Air Conditioning System
Authors: Thadani Hitesh , Chasta Bhanu K. , Mahiya Hari Om , Yadav Komal
Published: May 2023

Abstract: Rotary desiccant wheel are used to regulate the relative humidity of air streams. These are commonly integrated into heating ,ventilation and air conditioning unit to reduce the relative humidity of incoming ventilation air. Passive ventilation system are able to deliver adequate ventilation air but cannot control the humidity of the incoming air. To overcome this, the honeycomb water structure of rotary desiccant wheel was redesigned. In addition to this, the temperature of the regeneration air for desorption was lowered. Cooling pads were introduced in between the spokes of the wheel and filled with silica gel particles to form a rotary desiccant wheel. Computational fluid dynamics (CFD) model of the design was validated using experimental data.
A Semantic Network Encoder for Associated Fact Prediction
Authors: N Abirami , J Sneha , Shanmugavel D.
Published: May 2023

Abstract: Semantic network is a network of concepts connected by semantic relations. It contains two forms of binary semantic network and multiplex semantic network. The associated fact prediction is a link prediction task that aims to infer the implicitly connected facts by mining the high-level representation of the network. Previous methods for associated fact prediction put much emphasis on the topological feature of network but not utilize the information of semantic expression. This paper proposes a Semantic Network Encoder (SemNE), which learns a feature mapping function from the binary semantic networks and can be applied to the multiplex semantic networks in a pre-training manner. SemNE is a two-stage framework that contains an embedding encoder and a prediction decoder. It jointly models the semantic information and network topology to enrich the network representation. A word self-organization method based on the factual boundary is proposed to unify the topological feature and the semantic feature representations. Experimental results on binary semantic networks show that SemNE achieves the state-of-the-art results in associated fact prediction and experimental results on multiplex semantic networks show that SemNE is scalable and can effectively improve the performance of existing
Human Emotion Detection Using Deep Learning
Authors: Pandarinathan Mr. , Velan S. , Deepak S.
Published: May 2023

Abstract: Human emotions are the mental state of feelings and are spontaneous. There is no clear connection between emotions and facial expressions and there is significant variability making facial recognition a challenging research area. Emotion recognition becomes a popular topic of deep learning and provides more application fields in our daily life. The primary idea of our project is to process the input imagesof human facial emotion to train the pre-trained models on datasets. In recent years, Machine Learning (ML) and Neural Networks (NNs) have been used for emotion recognition. In this project, a Convolutional Neural Network (CNN) is used toextract features from images to detect emotions. The numerical result of the algorithm will show a probabilistic result of each labeled class.
Finding Missing Person Based on Face Recognition Using AI in Video Surveillance System
Authors: S Mageswaran , C Siva Kumar , G Prasanth , M Sundaram
Published: May 2023

Abstract: AI-based face recognition for missing person searches is a promising strategy that has the potential to significantly speed up and improve accuracy. The system makes use of artificial intelligence algorithms to match surveillance camera realtime video footage with facial images of people who have gone missing. Face recognition technology in video surveillance systems is used in this project to come up with a strategy for locating people who have gone missing. The system involves gathering information about the missing person, creating a database of facial images, and matching those images to real-time video footage with the help of artificial intelligence algorithms. The goal of the field of computer science known as artificial intelligence (AI) is to create intelligent machines that can carry out tasks that typically call for human intelligence. This includes tasks like translating languages, visual perception, speech recognition, and decision-making. Machine learning algorithms are used by AI systems to learn from data and allow them to improve their performance over time. A powerful method for training artificial neural networks with many layers, deep learning, a subset of machine learning, has emerged, allowing. The system can be used to quickly identify and locate missing people in public places like airports and train stations. The speed and accuracy of missing person searches could be significantly enhanced by the proposed system, increasing the likelihood of successful reunions. Finding missing people in view of face acknowledgment utilizing Convolutional Brain Organization (CNN) calculation is a well-known approach that has shown promising outcomes. CNN is a deep learning algorithm that works well for face recognition because it is widely used for image recognition and classification.
Design and Model Making of Electric Vehicle Charging Station
Authors: Bhattacharya Purnendu , Ali Asif , Mondal Indrajit , Bose Prof. Partha Sarathi
Published: May 2023

Abstract: An EV charging station is a facility designed to supply electric power for charging electric vehicles (EVs). As the demand for EVs continues to grow due to their environmental benefits and cost savings, the demand for EV charging stations is increasing rapidly. This paper provides an abstract for an EV charging station, covering topics such as the different types of EV charging stations, their working principles, the importance of charging infrastructure, and the benefits of using EVs. The paper also discusses the challenges associated with the development and deployment of EV charging stations, including their cost, availability of charging points, and the need for standardization. Furthermore, the paper presents some possible solutions to overcome these challenges, such as promoting government incentives, adopting innovative technologies, and increasing collaboration among industry stakeholders. Overall, the paper provides an insightful overview of EV charging stations, highlighting the importance of these facilities for the widespread adoption of EVs and the transition to a sustainable transportation system.
Surmising Assault Resistant E-Healthcare Cloud Framework with Fine-Grained Access Control
Authors: Shanmugavel D. , Varma M. Sushanth , Harish G.
Published: May 2023

Abstract: The e-medicinal services cloud framework has demonstrated its capability to enhance the nature of social insurance and people's personal satisfaction. Shockingly, security and protection obstruct its broad arrangement and application. There are a few research works concentrating on saving the security of the electronic human services record (EHR) information. In any case, these works have two principle restrictions. In the first place, they just help the 'dark or white' access control strategy. Second, they experience the ill effects of the deduction assault. In this paper, out of the blue, we outline a deduction assault safe e-human services cloud framework with fine-grained get to control. We initially propose a two-layer encryption plot. To guarantee a productive and fine-grained get to authority over the EHR information, we outline the primary layer encryption, where we devise a particular access strategy for every datum trait in the EHR, and encode them independently with high proficiency. To save the security of job traits and access strategies utilized in the principal layer encryption, we deliberately develop the second-layer encryption. To take full favorable position of the cloud server, we propose to give the cloud a chance to execute computationally concentrated chips away at benefit of the information client without knowing any delicate data. To save the entrance example of information properties in the EHR, we additionally build a visually impaired information recovering convention. At last, we lead broad security investigations and execution assessments, which affirm the viability and effectiveness of our plans .
Design of Transmission Tower for a Sub Station of 132 KV
Authors: Dupare Pranjal , Sarage Amey , Nilawar Atharva , Somkunwar Nilakshi , Bhorkar Mangesh
Published: May 2023

Abstract: In order to properly plan and design a structure, it is necessary to have not only imagination and conceptual thinking, but also a solid understanding of the science of structural engineering, as well as practical knowledge of recent design codes and regulations, all supported by ample experience, intuition, and judgment, with the goal of ensuring safety while maintaining a careful balance between economy and safety. One type of steel structure that has seen significant progress in recent years is the transmission tower, which must be constructed with great care and maintenance in order to ensure the safety and comfort of surrounding beings. While traditional methods of designing and analyzing transmission towers can be time-consuming, software such as "Spadaro V8i" can be used to expedite the process. In this research manual calculation is done by traditional method and after that modelling is done with software.
Image Based Appraisal Real Estate Properties
Authors: Sankar E , varma M Durga Prasad , Varma M Mahendra
Published: May 2023

Abstract: Real estate appraisal, which is the process of estimating the price for real estate parcels, is vital for both deals and merchandisers as the base for concession and trade. Traditionally, the duplication deals model has been vastly espoused to estimate real estate price. still, it depends the design and computation of a complex profitable affiliated indicator, which is challenging to estimate directly. moment, real estate brokers give easy access to detailed online information on real estate parcels to their guests. We're interested in estimating the real estate price from these large quantities of fluently entered data. In particular, we dissect the vaticination power of online house cinema, which is one of the vital factors for online addicts to make a implicit visiting decision. In this work, we employ a intermittent Neural Network( RNN) to prognosticate real estate price using the state- of- the- art visual features. The experimental results indicate that our model outperforms several of other state- of- theart birth algorithms in terms of both mean absolute error( MAE) and mean absolute chance error( MAPE).
Development of Course and Online Certification Process for Student Application Using React JS
Authors: K Jagadeesh , S Sharath , G Arjun Praveen , R Vishnurameshkumar
Published: May 2023

Abstract: This project aims to develop an online course application with certification and apply features using ReactJS for the frontend, NodeJS for the backend, and MySQL for the database. The application will have two main modules, one for the students and one for the admin. The student module will allow them to browse and apply for courses, view their course progress, and download their certificates upon completion. The admin module will enable the administrator to manage courses, approve student applications, view student progress, and generate certificates for completed courses. The project's primary objective is to provide an easy-to-use and efficient platform for students to apply and learn online and for the administrators to manage the system effectively.
Churn Prediction using Machine Learning Models
Authors: Bhoite Sayee N. , Gadekar Vaishnavi D. , Kapadnis Shashank V. , Ghuge Priyanka R.
Published: May 2023

Abstract: The market is expanding quickly across all sectors, giving service providers access to a larger user base. Better offers have led to increased competition, creative new business ideas, and rising costs for acquiring new customers. Service providers understand how crucial it is to keep clients on-site in such a brief setup. Service providers must therefore prevent churn, a condition that occurs when a customer decides not to use a company's services any longer. This study examines the most widely used machine learning algorithms for churn prediction, not just in the banking industry but also in other businesses that place a high value on customer engagement.
Experimental Investigation on Fly Ash Bricks using Industrial Waste
Authors: Sharmiladevi K. , A Ignashious Pinto , P Nimal Raj , M Priyaharun , S Veereswaran
Published: May 2023

Abstract: Although there are several benefits to using fly ash, its early lack of hydration results in low strength. In order to establish the appropriate fly ash brick mix percentage, an experimental investigation was carried out in the study. In brick specimens measuring 230mm by 110mm by 90mm, the compressive strength of various mix proportion of fly ash (14-30%), gypsum (5.5-8%), lime (14.5-30%), crusher waste (42-45%), cement (5.5%) was investigated. The objective is to find out the optimum mix design for making brick so as to achieve the maximum compressive strength.
New-Generation Drug Discovery using Machine Learning
Authors: Gupta Niharika , Khobragade Priya
Published: May 2023

Abstract: Finding innovative molecules with specific chemical properties to treat diseases is one of the goals of drug discovery. Recent years have seen the production of a sizable volume of biological data from many sources. These statistics and molecular analyses have been used to determine the most effective medications. Medical research often frustrates people and is far more expensive. The work at hand is made easier by having the ability to predict whether a medicine will be active or not. The information about the drug can also be used to develop other drugs. One application that makes use of machine learning to enhance decision-making in pharmaceutical data across numerous applications is quantitative structure activity relationship (QSAR) analysis. Machine learning-based predictive models have recently gained a lot of attention in areas outside of preclinical research. Costs and research times associated with finding new drugs are considerably decreased at this stage. Drug research is growing and more commonly utilising machine learning, algorithms for pattern recognition, knowledge of mathematical correlations, and knowledge of the chemical and biological characteristics of molecules. The necessity for a sizable volume of data, the incapacity to interpret the data, and other issues are further restrictions. Without the need for computational resources, massive amounts of data can be analysed using both physical models and machine learning approaches.
Food Detection and Calorie Estimation using Deep Learning
Authors: Deepika Allaboina , Sowmya Goriparthi , Susmitha Nemali , Kumar G. Sravan
Published: May 2023

Abstract: For the fight against obesity, precise food and energy intake measurement techniques are essential. One of the most important lessons for long-term prevention and effective treatment programmes is the provision of users and patients with practical and intelligent solutions that assist them in measuring their food intake and gathering dietary information. In this article, we suggest a calorie measurement technique to assist patients and medical professionals in their battle against dietrelated illnesses. In this document, we suggest a food identification system that, when given the appropriate quantity of data, can assist a user in keeping track of daily caloric consumption. Calorie estimation for the current method must be done by hand. The proposed model will use a deep learning algorithm to offer a special method of calculating calories. In the world of medicine, calorie calculations for food are crucial. because the calories in this food are beneficial to your health. This measurement is derived from photographs of various foods, including fruits and vegetables. Our suggested solution relies on cell phones, which enable the user to take a picture of the food and instantly calculate the number of calories consumed. We classify food photos for system training using deep convolutional neural networks to reliably identify the food in the system. In this study, we use a convolutional neural network (CNN) to detect and identify images of food. Given the huge range of food types, picture recognition of food products is frequently very difficult. Whatever the case, deep learning has recently been shown to be an incredibly innovative image identification approach, and CNN is the greatest way to use deep learning.
Social Media based Hate Speech Detection using Machine Learning
Authors: Auti Dr. Nisha , Ranaware Sumit , Ghadge Shreeraj , Jadhav Rajdatta , Jagtap Prajwal
Published: May 2023

Abstract: Hate speech is a crime that has been increasing in recent years, not only in person but also online. There are several causes for this. There is tremendous growth in social media that promotes full freedom of expression through anonymity features. Freedom of expression is a human right, but hate speech directed at individuals or groups on the basis of race, caste, religion, ethnicity or nationality, gender, disability, gender identity, etc. is a violation of that sovereignty. Freedom of expression is a human right, but hate speech directed at individuals or groups on the basis of race, caste, religion, ethnicity or nationality, gender, disability, gender identity, etc. is a violation of that sovereignty. It promotes violence and hate crimes, creates social imbalances, and undermines peace, trust and human rights. Revealing hate speech in social media discourse is a very important but complex task.
Investigation of the frequency and risk factors of pulmonary complications following cardiac surgery in the hospital
Authors: Salajegheh Shirin , Sharifzadeh Kermani Mahdieh , Naeimi Bafghi Naeimeh , Naeimi Bafghi Neda , Salehi Jafar , Nakhaei Zadeh Reza , Javid Mohammad Javad
Published: May 2023

Objective: The purpose of this study was to determine the frequency of pulmonary complications after heart surgery and to assess the pre-operative, intra-operative and post-operative risk factors.
Methods: This was a descriptive and analytical study that was conducted on 244 patients who underwent various cardiac surgeries from December 2021 to May 2022 in Shefa Kerman Hospital. This descriptive/analytical study on patients undergoing heart surgery at Shafa Hospital, Kerman, Iran, from December 2021 to May 2022. Pulmonary complications included atelectasis pneumonia, pleural effusion, long-term mechanical ventilation, and respiratory failure. The pre-operative, intra-operative and post-operative risk factors were investigated in the present study. SPSS software was used to analyze the data. Logistic regression analysis was employed to determine the relationship between risk factors and the incidence of lung complications.
Results: In the present study, 55 patients (22.5%) had pulmonary complications, followed by prolonged mechanical ventilation (13.1%), pneumonia (11.5%), respiratory failure (4.1%), pleural effusion (11.1%) and atelectasis (6.1%). Pulmonary complications after heart surgery were associated with days of ICU stay, post-operative stroke, post-operative acute kidney injury, emergency surgery, FFP injection, high drainage rate, and mitral valve replacement surgery (all p <0.001). 4% of patients died after surgery, which was statistically related to pulmonary complications (P<0.0001). The results of multivariable logistic regression test showed that FFP injection, type of heart surgery, hypertension, ICU stay days are capable of predicting pulmonary complications after heart surgery.
Conclusion: Mortality was found to be higher in patients with pulmonary complications. Based on the results of the regression analysis, FFP injection, type of surgery, history of hypertension and length of ICU stay were independent risk factors of pulmonary complications.
Physiological effects of Calprotectin and B Cell activating factor in COVID-19 Patients
Authors: Hazhar M. Balaky  , Akam Jasim Mustafa  , Parween Abdulsamad Ismail  , Araz Muhammad Yousif
Published: May 2023

Objectives: This study set out to determine how Calprotectin and B cell activating factor contributes to early COVID-19 patient severity prediction.
Methods: The study included 25 healthy controls and 52 patients with SARS-COV2 infection who were clinically diagnosed with COVID-19 illness and were between the ages of 23 and 35. The serum levels of CALP and BAFF were measured using the ELISA method. To gauge CRP levels, an immunoturbidometric assay was performed.
Results: Variations in serum levels of CALP and BAFF were found to be statistically insignificant in the study (P=0.7109 & P=0.7575, respectively). When compared to the control group (103.95±36.67 ng/mL; 403.03±1.03), COVID-19 patients had non-significantly raised levels of CALP and BAFF (106.5±4.67 ng/mL; 436.9±12.77 pg/mL, respectively). According to ROC curve analysis, the area under the receiver operating characteristics curve (AUC) for CALP and BAFF was (0.5170) and (0.5259), respectively. (r=0.6923; P=0.0001). There was a significant positive correlation between serum CALP and BAFF levels. The connection between serum CRP levels and CALP (r=0.3010; P=0.1271) and BAFF levels (r=0.2912; P=0.1406) was insignificantly positive.
Conclusion: The current study's findings suggested that serum CALP and BAFF concentrations were increased in COVID-19 patients, suggesting that these inflammatory markers may be helpful indicators of the severity of COVID-19.
Evaluation the effect of formulation made of Talh honey, whey protein and collagen on acute excisional skin wound healing in Wistar male rat
Authors: Yamani Hanaa Abbas , Fakiha Khloud
Published: May 2023

Objectives: This study evaluated the ability of using formulation contains Talh honey, whey protein and collagen on wound healing using animal model.

Methods: 24 Wistar male rats were divided into four groups of 6 rats each as follow; G1 (not treated), G2 (treated with Manuka honey), G3 (treated with Povidone iodine ointment 5%), and G4 (treated with tested formulation). Excisional wound was induced in rat’s dorsal skin. The duration of the study was 18 days. Morphological and histological examination was performed for all groups.

Results: The tested formula showed reduction in the duration of the inflammatory phase of wound healing when compared to other groups.

Conclusion: Results from this study indicated the therapeutic potential of the tested formula, which contains natural component, in wound healing as using other therapeutic products. The tested formula is affordable for wide range of patients. Further studies are required to investigate the different mechanisms behind the therapeutic properties of each treatment.
The impact of blood group phenotypes on COVID-19 severity and mortality in Duhok province: a prospective cross-sectional study
Authors: Rasho Fatima Jaafar , Aghali Merza Muayad
Published: May 2023

Objectives: This study aimed to determine the frequency of blood group types among COVID-19 patients and to investigate its potential association with disease severity and patient outcomes.

Methods: this prospective cross-sectional study was conducted from February to July 2022 in three different healthcare facilities in the Duhok region. All confirmed PCR confirmed COVID-19 patients were classified into: mild, moderate, severe, and critical cases. Information on demographic, clinical, and laboratory characteristics were collected using a standardized questionnaire. All patients were subjected to ABO blood grouping. The statistical calculations were performed by JMP Pro 14.3.0. A p value of < 0.05 was considered significant.

Results: the study comprised of 404 patients. The age range of the patients varied from 16 to 100 years with a male predominance (204, 50.5%). Out of the total patients, 250 (61.88%) had mild-moderate course, while 154 (38.12%) had severe-critical course. The most frequent blood group was O (164, 41.58%), followed by blood group A (121, 29.95%). There was no significant difference in the distribution of the Rh factor among the studied subjects (p=0.426). There was a significant increase in disease severity and worse outcome with increasing age (p=<0.0001). Considering blood group types, there were no significant differences between blood group types with COVID-19 severity and patients’ outcome.  

Conclusions: individuals with blood group O may have a higher risk of contracting COVID-19. Advanced age is a crucial predictor of disease severity and poor outcomes. There were no significant association between blood group types with COVID-19 severity and patients’ outcome. However, further research is needed to confirm these findings and determine the underlying mechanisms behind any potential association between blood groups and COVID-19 susceptibility, severity, and outcome.
Molecular Immuno-response Effects for Iraqi Lycium barbarm Carotenes upon Normal Human lymphocytes culture
Authors: Yaseen Mohammed Hasan Zainab , Alsamarrae Khulood W. , Rushdi Ahmed
Published: May 2023

Objectives: The study aimed to investigate the effects of Iraqi Lycium barbarm Carotene on normal human blood lymphocytes at molecular level.

Methods: The normal human blood lymphocytes culture was exposed to Carotene extracted from Iraqi Lycium barbarm to estimate the interleukins  expression in treated lymphocytes represented by IL-10 and TNF-α as a moderator of immune response at a molecular scale, and their CD markers changes expression (CD3, CD4&CD8) by  flow-cytometer apparatus.

Results: Total carotenes content was 0.33mg/g powdered dried fruit. Potent carotene effect was appeared at concentration of 500µg/ml for  treated lymphocytes with increasing CD3 level to get upper level after 2 hours interval, while after 4 hours exposure both CD4 and CD8 levels increased dramatically for lymphocytes treated with 125 µg/ml, and 250µg/ml Lycium carotene. An alteration in cytokines gene expression for IL-10 production in response to carotene treatments at (125,250,500) µg/ml for both intervals, with suppress in tumor necrosis factor (TNF-α) gene expression in relation to β-actin the internal control and the PHA mitogenic agent.

Conclusion: The study concluded that the carotenes extracted from Lycium barbarm fruits seemed to initiate the immune system toward Th2 cell activation rather thanTh1, besides the extract may potentiate IL-10 production.
Ekspresi Spiritualitas Kelompok Keagamaan di Beberapa Wilayah Provinsi Aceh
Authors: Saputra Hanif
Published: May 2023

This study aims to explore the existence of diverse religious groups in the province of Aceh and how they engage in religious activities alongside other groups. In collecting data, the researcher used the library research method to gather references from books, journals, and academic research reports related to the topic, as well as the Netnography method to gather public information through relevant social media. The results show that there are several different religious groups in Aceh with varying views and expressions of their rituals in different regions. The Tastafi group, Jama'ah Tabligh, and the T. Raja Ubiet community group have different characteristics and expressions in their spiritual activities. On the other hand, the Wahabi group shows a far different view from the local spiritual practices, causing them to be isolated from other religious groups. This study reinforces the reality that although Aceh has implemented Islamic law as positive law, religious groups can still thrive and not hinder the emergence of various religious expressions in the community.

Abstrak

Kajian ini bertujuan untuk mengeksplorasi tentang eksistensi beragam kelompok keagamaan di Provinsi Aceh dan bagaimana mereka melakukan aktivitas keagamaan secara berdampingan dengan kelompok lainnya. Dalam pengumpulan data, peneliti menggunakan metode library research yang mengumpulkan referensi dari buku, jurnal, dan laporan penelitian akademik yang berhubungan, serta metode Netnografi yang mengumpulkan informasi publik melalui media sosial yang relevan. Hasil penelitian menunjukkan bahwa terdapat beberapa kelompok keagamaan yang berbeda dalam pandangan dan ekspresi ritual mereka di beberapa wilayah Aceh seperti kelompok Tastafi, Jamaah Tabligh, dan kelompok masyarakat T. Raja Ubiet. Kajian ini mempertegas realitas bahwa meskipun Aceh telah menerapkan syariat Islam sebagai hukum positif, namun kelompok keagamaan tetap dapat berkembang dan tidak menghalangi lahirnya berbagai ekspresi keagamaan dalam masyarakat.