Volume 12 | Issue 3 |

 Abstract

This study explores the use of machine learning algorithms for crime prediction using historical data of public property crime in a large coastal city in southeast China. The comparative analysis focuses on the predictive power of several machine learning models. The findings indicate that the LSTM model outperformed other methods such as KNN, random forest, support vector machine, naive Bayes, and convolutional neural networks when solely using historical crime data. Furthermore, incorporating built environment data such as points of interest (POIs) and urban road network density into the LSTM model as covariates improved the prediction effect. These results have implications for the formulation of policing strategies and the implementation of crime prevention and control.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crime Detection, Crime Analysis, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

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The survey titled "Dental Telecare Insights: Exploring Viability and Patient Contentment in Virtual Consultations and Follow-ups" offers a meticulous examination of teledentistry, a revolutionary fusion of telecommunications and dentistry. With a primary focus on evaluating teledentistry's viability and patient satisfaction, the survey elucidates its roots, evolution, and diverse applications. Methodologically robust, the survey employs a cross-sectional study design among BDS college students and dental graduates in Pune, Maharashtra. Results highlight varied objectives, patient satisfaction nuances, and the impact on rural populations. Discussions encompass environmental concerns, cost implications, and the delicate balance between crisis management and preventive measures. The study underscores the paramount significance of maintaining patient confidentiality, ensuring secure data transmission, and reinforcing trust in telehealth platforms, echoing the imperative for standardized practices in the burgeoning field of dental telecare.

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 Keywords

Teledentistry,Patient satisfaction,Virtual consultations,Telehealth,Preventive dentistry,Cost-effectiveness,Environmental concerns,Patient confidentiality,Hybrid approach,Dental education.

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 Abstract

The "Underwater Tank Cleaning System" concept presents an innovative solution for effectively cleaning debris from the surface of underwater tank. The system utilizes a PMDC motor as its driving force, a diaphragms water pump and filtration bag is used to efficiently remove contaminants. A suction pipe is employed to facilitate the intake of debris into the system. Additionally, to ensure operational safety and longevity, a thermistor is integrated to monitor and regulate motor temperature underwater. To enhance user interaction and control, the system is equipped with a Cam Development Board (ESP32). This allows users to monitor and manage the cleaning process via wired connection, providing real- time feedback and control capabilities.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

PMDC Motor, Flow Meter, filtration Bag, SMPS, brush

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

What if one day u wake up and your application starts getting a lot of unexpected traffic? This is amazing, isn't it? But is your application ready for it? Can it handle so much traffic? In this project we propose a Elastic load balancer. ELB (Elastic Load Balancer) is a service provided by AWS (Amazon Web Services) which is used to balance the incoming load (traffic) on multiple EC2 instances which can be in multiple availability zones. Load balancing distributes the network traffic in such a manner that increases speed and the performance of web applications. Modern ELB uses "Round robin algorithm". The real time applications of ELB are high traffic websites, E- commerce applications, Media streaming, Gaming applications, Mobile applications. ELB improves scalability, availability and fault tolerance of web applications and services.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Elastic Load Balancer, Amazon Web Services, Elastic Compute Cloud, Round Robin, Scalability.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

To analyse the variation of cost between LGSF building and RCC building and time reduction in construction

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Light gauge steel frame,cost control, time reduction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A build-up of senile plaques (SPs) and neurofibrillary tangles (NFTs) in the brain is the pathological hallmark of Alzheimer's disease (AD), the primary cerebrovascular illness that causes dementia. Diabetes mellitus is a condition marked by improper carbohydrate metabolism and increased blood glucose levels. It is caused by a malfunction in the body's capacity to create or respond to the hormone insulin. There is growing recognition that cognitive impairment is a significant comorbidity of diabetes mellitus. There are many stages of diabetes-related cognitive impairment, each with unique cognitive characteristics, affected age groups and prognoses, and most likely distinct underlying processes. Additionally, mounting data points to a number of linkages between the neuropathology underlying DM and AD, and evidence even points to the possibility that experimental production of DM might result in cognitive failure, even in rodent animal models. Deficits in spatial learning are correlated with unique modifications in hippocampus synaptic plasticity in animal models of diabetes. Although the complex pathophysiology of diabetic encephalopathy is not fully known, it is evident that it has characteristics with the pathophysiology of diabetic neuropathy and brain aging. Chronic hyperglycemia-related alterations in metabolism and blood vessels are present, and there may also be abnormalities in the brain's ability to use insulin. Thus, insulin treatment may have a direct impact on the brain in addition to addressing hyperglycemia. Therefore, insulin therapy may have a direct impact on the brain in addition to treating hyperglycemia. It is not yet known why AD typically occurs in older people, despite genetic research demonstrating that the primary component of SPs, ?-amyloid peptide (A?), is the critical element causing AD pathogenesis.

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 Keywords

Senile plaques, Neurofibrillary tangles, Alzheimer's disease, Diabetes mellitus, Dementia, Synaptic plasticity, ?-amyloid peptide.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Horticulture stays significant in driving financial change, practical jobs, and advancement in emerging nations. This paper gives a far reaching examination and conversation of environmental change influences on water and horticulture areas and suggestions for the fulfillment of formative results like food security, destitution decrease, and practical improvement in Southern Africa. The audit gives strategy messages for adapting, adjusting, and fabricating flexibility of water and agrarian creation frameworks despite extended changes in environment and changeability. The point is to direct the district towards the accomplishment of the Supportable Improvement Objectives. Future projections for Southern Africa demonstrate decreased precipitation, expanded temperatures, and high inconstancy for most of the district with extreme decreases on the drier and minimal western parts. These effects have significant ramifications for farming execution and commitment to public and provincial formative objectives. The district is projected to encounter decreases of somewhere in the range of 15% and half in rural efficiency, a situation that would worsen food uncertainty in the locale. The test is to increment efficiency on ebb and flow arable land through productive and reasonable administration of accessible water and energy, and simultaneously decreasing tension on the climate. Reasonableness and availability of creative variation estimates on water assets stay basic and these systems ought to be important for more extensive manageable advancement endeavors. By and large, endeavors to improve agrarian efficiency need to underline interests in maintainable administration and utilization of water and energy assets in agribusiness to accomplish practical monetary development and jobs.

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 Keywords

Key Words: Environmental Change; Transformation; Flexibility; Water assets; Food Security; Manageability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The escalating prevalence of diabetes globally has positioned it as a significant contributor to mortality rates. Elevated blood glucose levels and insulin resistance are implicated in a spectrum of health complications, encompassing cardiovascular diseases, renal dysfunction, neuropathies, and diabetic retinopathy--a debilitating condition marked by vision impairment. Early detection serves as a pivotal determinant in mitigating the progression of diabetic retinopathy and averting irreversible visual impairment. Consequently, the imperative for a robust screening methodology becomes apparent. To this end, a comprehensive investigation into deep learning strategies has been undertaken. Leveraging publicly available datasets, our research ends have focused on the acquisition and reprocessing of data pertaining to diabetic individuals. Furthermore, the development of sophisticated machine learning algorithms, including deep neural networks such as Convolutional Neural Networks (CNNs), has been instrumental in refining our screening approach. The culmination of these efforts has yielded promising outcomes, as evidenced by the system's proficiency in accurately discerning normal retinal images from those indicative of aberrant pathology with a remarkable degree of certainty. In conclusion, the integration of advanced technologies, such as deep learning and machine learning, holds considerable promise in revolutionizing diabetic retinopathy screening protocols. By harnessing the power of these methodologies, we can enhance early detection, facilitate timely intervention, and ultimately ameliorate the burden of diabetic retinopathy on global visual health outcomes

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diabetic Retinopathy, Deep Learning, KNN, CNN

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's globalized world, effective cross-cultural communication is essential for success in various personal, academic, and professional endeavors. English language proficiency plays a significant role in facilitating communication across cultural boundaries. This paper explores the impact of English language proficiency on cross-cultural communication success, examining its influence on interpersonal interactions, academic achievements, and professional opportunities. By analyzing research findings and real-world examples, this paper highlights the importance of English language proficiency as a key determinant of success in cross-cultural communication.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

English language proficiency, cross-cultural communication, globalization, interpersonal interactions, academic achievements, professional opportunities.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Image manipulation and forgery present significant challenges across various domains, including forensics, security, and media authentication. This is a novel approach that integrates Error Level Analysis (ELA) with Convolutional Neural Networks (CNNs) to differentiate between authentic and tampered images. Using the Cassia v2 dataset containing both real and fake instances, diverse data augmentation techniques, such as flattening, resizing, and converting images to ELA format, are applied to enhance model robustness. The dataset is partitioned into 80% training and 20% validation sets to facilitate comprehensive model training and evaluation. Utilizing Keras, a Sequential model is developed, incorporating Conv2D, MaxPooling2D, Dropout, Flatten, and Dense layers for effective feature extraction and classification. Training utilizes the Adam optimizer for parameter optimization. Evaluation metrics, including loss, accuracy, and a confusion matrix, are employed to assess model performance. Results demonstrate promising accuracy, with the model achieving 98.8% training and 92.8% validation accuracy, showcasing the efficacy of the proposed methodology in accurately distinguishing between real and fake images. This approach holds potential for applications in image forensics, security, and authentication domains.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fake images, ELA, CNN, Sequential model, Adam optimizer

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Creative Commons Attribution 4.0 and The Open Definition