Revista Electronica de Veterinaria

Media Framing And Tourism Reporting In Jammu And Kashmir: A Content Analysis Of Newspaper Coverage

2024-06-26T06:14:51+00:00

This study provides a comprehensive analysis of the reporting on tourism topics in the Greater Kashmir and Daily Excelsior newspapers over a five-month period, guided by media framing theory to understand how different aspects of tourism are highlighted or modulated in media reports and their impact on public perception. A total of 926 articles were analysed using content analysis, categorized into ten major topics awards, individual personality, event or activity promotion, economic development, tourism authorities, economic indicators, health and safety, government policy, law and order, and statistics. The findings reveal a significant focus on health and safety (55.61%) and law and order (31.53%), reflecting the ongoing impact of the COVID-19 pandemic and security concerns in J&K, while event and activity promotion received minimal coverage (6.69%), indicating a missed opportunity for positive tourism marketing. The monthly distribution of stories showed that May had the highest number of articles (217), while June had the fewest (151). Addressing the research gap in understanding how newspapers in J&K report on tourism-related topics, this study highlights the predominance of negative frames which can deter potential tourists, highlighting the need for a balanced approach that includes more positive stories about tourism activities, cultural events, and government initiatives. The implications of this study are significant for tourism authorities, media outlets, and policymakers, as understanding the media's role in shaping public perception can help stakeholders develop strategies to enhance the region's tourism appeal and address imbalances in coverage. Recommendations include increasing the coverage of event and activity promotion, striving for balanced reporting, collaborating with tourism authorities, and providing training for journalists in tourism reporting. In conclusion, this study contributes to a better understanding of the relationship between media coverage and tourism development in politically and socially complex regions like Jammu and Kashmir.

An Analysis Of Improved Forensics Design Framework For Cloud Computing In Computer Reliability System Engineering

2024-06-26T06:24:31+00:00

The popularity of An Analysis of Improved Forensics design Framework for Cloud Computing in Computer Reliability System Engineering has been growing over the past decade due to the fact that cloud resources can be distributed as needed and are shared by numerous users. According to a recent poll, cybercriminals have been successful in by means of cloud computing skill for fraudulent tasks because of its fundamental features and the dearth of digital forensic methods that are appropriate for the cloud environment. Investigators who handle cloud forensics encounter a number of difficulties and problems while trying to prevent cloud crime. The difficulties that forensic investigators encounter have discussed in this essay. The majority of study work focuses on figuring out the problems with cloud forensics, and the solutions that have been recommended and published in the literature rely on the use of Cloud Service Providers (CSP) for forensic inquiry. Data gathering for the forensics process is one aspect of the reliance on the Cloud Service Provider (CSP), and there's a potential that data manipulation could have an impact on the entire scientific process. To reduce the reliance on CSP, a innovative technique aimed at obtaining forensic indication external of the cloud atmosphere is industrialized.

Digitalization Of Bengali Drama and Dramatic Approach Of Digitalised BengaliTelevision Programmes: A Comparative Study

2024-06-26T06:32:07+00:00

The digitalization of production as well as the commercialization of Bengali drama made two significant changes. One it cuts up the place and function of traditional programme format, Two, production of media content now uses more personal, like ‘U’-style (absolute intimation format). Extended the reach for traditional content but has also provided more touch point to engage with audiences regardless of niche, geography and tastes. Globalized television culture needs to be enhanced through diverse content as it is associated with profound cultural identity of the middle class Bengali families. Apart from the reality based show, on screen adaptations of literature, drama can also seen in the Bengali television channels which are widely accepted too. Diverse storyline with a mix twists and turns help in garnering TRPs for the television shows. In Indian thought, drama is not viewed with the same eyes, perhaps, or television programs based on the theatrical quality. A simple reason for this could be that the sound of the name of the drama conjures up the idea of a traditional and serious thing, while the television program may be hundreds of miles away from it. But it is difficult for many to accept that that particular television program also has a drama. Moreover, due to digitization, the theatrical effort is finally reaching millions of viewers. From a handful of captive viewers, drama is becoming entertainment for a large audience. In the proposed article, a material and content aspect of drama and television programs will be compared and their scope will be seen as a result of digitization

Using a Lightweight Convolutional Neural Network for Contactless Multispectral Palm-Vein Recognition

2024-06-26T06:45:40+00:00

Biometric recognition technology has advanced to the point of replacing traditional codes and credentials. One such technique gaining popularity is contactless palm vein verification, which is safe and sanitary. However, there are important issues to consider regarding system safety and scalability in deep learning (DL). Convolutional neural networks (CNNs) are among the most extensively studied deep learning algorithms, known for their ability to extract features. Nonetheless, training CNNs requires a significant intellectual effort and large sample sizes, resulting in higher hardware and software costs.To address the need for a substantial amount of palm-vein data, this research proposes to use a versatile Gabor filter with improved photographic characteristics and a triplet loss function.

This study used a multidimensional palm database from the CASIA accessible database to evaluate the suggested system. According to the study findings, the suggested approach only requires a small number of network configurations in a multispectral environment and has an average identification error rate of 0.0456%.

ZnO -Graphene Nanocomposites: Synthesis, Characterization, And Applications

2024-06-29T09:40:40+00:00

ZnO-graphene nanocomposites present a versatile and promising platform with numerous applications across various fields, including human and veterinary medicine. Their unique combination of properties, such as antibacterial activity, biocompatibility, electrical conductivity, and mechanical strength, makes them valuable in addressing a wide range of challenges and needs in healthcare and biomedicine.

In human medicine, ZnO-graphene nanocomposites have shown potential in areas such as drug delivery, wound healing, biosensing, cancer therapy, and biomedical imaging. They offer innovative solutions for improving treatment outcomes, enhancing diagnostic capabilities, and advancing medical device technologies.

Continued research and development in ZnO-graphene nanocomposites hold promise for further expanding their applications and optimizing their performance in both human and veterinary healthcare settings. As advancements continue, these nanocomposites are poised to play a significant role in advancing medical and veterinary treatments, improving patient outcomes, and contributing to overall health and well-being. The synthesis, characterisation, uses, and prospects for ZnO–Graphene nanocomposites in the future offer a constantly evolving field of scientific inquiry and technological advancement. This abstract highlights important elements that define the storey of these cutting-edge materials, thereby capturing the spirit of this complex journey.

The production of ZnO–Graphene nanocomposites is characterised by an ongoing pursuit of accuracy and consistency. To accomplish successful integration, researchers have used a variety of synthetic processes, such as sol-gel methods and chemical vapour deposition. A primary goal is to optimise these techniques in order to guarantee consistency in the properties of the nanocomposites and improve scalability. The synthesis procedure is the cornerstone upon which ZnO–Graphene nanocomposites' special qualities and capabilities are constructed.

When it comes to deciphering the complex structural features of ZnO–Graphene nanocomposites, characterization procedures are essential. Together, Fourier Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and X-ray Diffraction (XRD) provide a thorough understanding of the composition, shape, and internal structure of the nanocomposites. Researchers find these techniques to be quite useful since they offer valuable insights that help fine-tune the properties of nanocomposite materials for certain applications.

ZnO-Graphene nanocomposites have a wide range of applications, which demonstrate their adaptability and versatility. These nanocomposites have remarkable photocatalytic qualities that aid in the breakdown of contaminants in the air and water during environmental restoration. The special combination of graphene's conductivity and ZnO's semiconducting qualities makes for extremely sensitive and selective sensors in sensing technologies. The energy storage capacity of the nanocomposites is greatly increased, improving the efficiency of batteries and supercapacitors. They boost solar cell performance in photovoltaics, and their biocompatibility is utilised in biomedical applications for imaging and medication delivery.

ZnO-Graphene nanocomposites have an exciting trajectory of innovation ahead of them. Scientists are ready to further refine synthesis techniques such that they are repeatable and scalable. At the forefront of research are improved nanocomposite qualities designed for particular uses. The next stage of these materials' evolution will be defined by innovative uses, integration with cutting-edge technologies, and a dedication to sustainable methods.

“The Lumpy Skin Disease Burden In The Cattle Of Anakapalli District, Andhra Pradesh”

2024-07-02T11:21:37+00:00

Survey on the Lumpy skin Disease in the Anakapalli District of Andhra Pradesh conducted in the period of 2022 October to 2023 September. Results are shown below

RESULTS AND DISSCUSSION

From the present study and the data generated it is inferred from the survey that the estimates of percentage of animals which are suffering from LSD is 20.18 % in the Anakapalli District. In winter season 62 cows in 248 cows. So the prevalence rate in winter of this period is 25% (62/248). In summer season 36 positive cases were obtained in 229 animals. So the prevalence rate of the disease in the summer season of the study period is 15.72 % (36/229). The same in the case of the rainy season the positive cases are 51 among the 261 animals. So the prevalence rate in the rainy season of the study period is 19.5 % (51/261). Highest no. of positive cases were recorded in winter season which corresponds to months between October 2022 to January 2023.

Moderate cases were recorded in the rainy season which corresponds the months between June 2023 to September 2023. And low number of cases was identified in the summer season which corresponds the months between February 2023 to January 2023Different types of diseases are wide spread among the cattle of Anakapalli District in different seasons. Among them the Lumpsy Skin Disease, Babesiosis, Theleriasis, Foot and Mouth Disease, Haemorages septisimia, Basillus anthrax are the wide spread diseases. These diseases hamper the growth of the livestock sector and impose serious constraints on the health and productivity of domesticated cattle in tropical and sub-tropical regions of the world. So, It is very essential to have complete knowledge of this parasite prevalent in the area for developing an effective control measures and mass vaccination strategy.(Morris 1931) and it was restricted to sub-Saharan Africa until 1989 and later transboundary spread of the disease to the Middle East Asia (Israel) was observed (House et.al. 1990). In 2019, the LSD outbreak was reported for the first time in Bangladesh, India, China, and also re-emerged in Israel (Calistri et.al. 2020). The disease might have emerged in India from its neighboring countries (Kumar et.al. 2020) and is posing many outbreaks in the bovine population throughout the country. The occurrence of the disease was being observed from the year 2019 and was scientifically reported in the year 2020 (Kumar et.al. 2020; Sudhakar et.al. 2020). The disease is causing severe economic losses to the farmers in the present pandemic scenario directly in terms of loss of productivity, reduced milk production, temporary or permanent sterility in bulls,and loss of condition of hides and indirectly in terms of trade restrictions, costs of laboratory diagnosis, supportive treatment, disinfection of premises, and vaccination. The major route of transmission of the disease is by biting flies and ticks (Ali and Obeid 1977; Lubinga et.al. 2013a, 2013b; Lubinga 2014; Tuppurainen et.al. 2013a, 2013b). The first outbreak of LSDV in Israel in 1989 was thought to be due to the movement of infected Stomoxys Lumpy Skin Disease is caused by the lumpy skin disease virus (LSDV) that belongs to the genus Capri pox virus and Family Pox viridae. The disease was first observed in Zambia in the year 1931 (Morries 1931) and it was restricted to sub Saharan africa until 1989 and later transboundary spread of the disease to the Middle East Asia(Israel) was observed (House et al.1990). In 2019 the LSD out break was reported for the first time in Bangladesh, India, China and also re-emerged in Israel (Calistri et al. 2020) The disease might have emerged in India from its neighbouring countries (Kumar et.al. 2020) and is posing many out breaks in the bovine population throughout the country. The occurrence of the disease was being observed from the year 2019 and was scientifically reported in the year 2020 (Kumar et al. 2020: Sudhakar et al.2020) The major route of transmission of the disease is by biting flies and ticks (Ali and Obeid 1977: Lybinga et.al 2013a, 2013b: Lubinga 2014: Tippurainen et al.2013a.2013b). The first outbreak of LSDV in Israel in 1989 was thought to be due to the movement of infected Stomoxys calcitrans from Egypt (Yeruham et a.1995). Similarly, the risk of introduction of LSDV through Stomoxys calcitrans that were present in animal transport trucks was observed by Saegerman et al. 2018.

Age and Seasonal Impacts on Bull Semen Quality: Current Findings and Future Directions

2024-06-26T07:06:34+00:00

This review explores the intricate interplay between age, season, and semen quality in bull reproduction, emphasizing the need for standardized assessment protocols, and advanced molecular technologies. Age-related changes in semen parameters such as volume, concentration, motility, and morphology are driven by physiological, and hormonal factors. Seasonal variations, influenced by environmental conditions, further affect reproductive success. Despite extensive research, inconsistencies in findings persist, highlighting the need for deeper investigation into the underlying mechanisms. Recent advancements underscore the significance of hormonal and nutritional influences on semen quality, advocating for targeted interventions. Key challenges in assessing semen quality include genetic variability, inconsistent methodologies, and a lack of longitudinal studies. Future research should focus on elucidating molecular pathways, integrating advanced technologies, and developing predictive models to optimize artificial insemination programs. Addressing these gaps requires a multidisciplinary approach to enhance reproductive performance and genetic progress in the cattle industry. This review offers valuable insights into the complexities of age and seasonal effects on bull semen quality, calling for standardized methods ,and innovative strategies to advance the field

Incidence and Impact of Ventilator-Associated Pneumonia in ICU Patients with Severe Pneumonia and Respiratory Failure: A Prospective Study

2024-06-26T07:30:38+00:00

Ventilator-associated pneumonia (VAP) is a critical complication affecting intensive care unit (ICU) patients with severe pneumonia and respiratory failure, significantly impacting morbidity and mortality rates. This prospective study aims to investigate the incidence, clinical outcomes, and risk factors associated with VAP in this vulnerable patient population. Data were collected from ICU admissions at Tertiary Care Hospital in Central India between June 2023 and December 2023, focusing on patients diagnosed with severe pneumonia and requiring mechanical ventilation. The incidence of VAP, defined by clinical criteria and microbiological confirmation, was assessed alongside patient outcomes, including length of ICU stay, mortality rates, and antibiotic utilization. Multivariate analysis identified independent predictors of VAP occurrence and associated complications. Findings underscore the profound clinical implications of VAP in ICU settings, emphasizing the need for rigorous preventive strategies and optimized management protocols to improve patient outcomes.

Introduction: Ventilator-associated pneumonia (VAP) is a prevalent nosocomial infection among critically ill patients requiring mechanical ventilation in intensive care units (ICUs). It complicates the management of severe pneumonia and respiratory failure, posing substantial challenges due to its association with increased morbidity, mortality, and healthcare costs. The incidence of VAP varies widely, influenced by patient-specific factors, ICU practices, and antimicrobial resistance patterns. Early recognition and appropriate management are crucial to mitigate the impact of VAP on patient outcomes. This prospective study aims to explore the incidence, clinical impact, and risk factors associated with VAP specifically in ICU patients with severe pneumonia and respiratory failure at Chirayu Medical College & Hospital.

Methods: This prospective cohort study included ICU patients diagnosed with severe pneumonia and requiring mechanical ventilation, admitted to a Tertiary Care Hospital in Central India between June 2023 and December 2023. Data were collected prospectively from electronic health records, focusing on demographic characteristics, comorbidities, severity of illness scores, and microbiological profiles. VAP was diagnosed based on clinical criteria including new or progressive infiltrates on chest radiography, purulent respiratory secretions, fever, leukocytosis, and microbiological confirmation from lower respiratory tract specimens. Clinical outcomes such as ICU length of stay, duration of mechanical ventilation, mortality rates, and antibiotic utilization were analyzed. Multivariate logistic regression was performed to identify independent predictors of VAP occurrence and associated complications.

Results: Our study enrolled a total of 100 ICU patients, with 30 patients diagnosed with ventilator-associated pneumonia (VAP) and 70 patients without VAP (Non-VAP).

Synthesis And In Vitro Biological Evaluation Of Metal Complexes Of 2-Aminobenzothiazole

2024-06-26T07:40:33+00:00

Antibiotic resistance is a growing problem in today’s healthcare which increase the demand of heterocyclic compounds. Heterocyclic compound bears different biological activity, like anti-cancer, anti-inflammatory, anti-oxidant, antibacterial, etc. therefor its demand increase in development of new compounds to overcome microbial resistance. The coordination chemistry of 2-aminobenzothiazole, which possesses potential coordinating sites including one exocyclic (NH₂) and two endocyclic (N and S), has received significant attention in recent decades. The interest has led to the discovery of various transition metal complexes exhibiting diverse structures. 2-amino benzothiazole and substituted aldehyde (2,4 dichlorbenzaldehyde ,4-benzyloxybenzaldehyde) used as a reactant in synthetic organic chemistry and also used for making Schiff base ligand for increase the potency of the final product. The reaction of the Schiff bases (SB₁ and SB₂) with the core metals like Cobalt chloride, manganese chloride, nickel chloride, and copper (II) has produced metal complexes (MC_1-8) of Schiff bases. In our study, we employed the DPPH assay and the agar diffusion method to assess the anti-oxidant and antimicrobial characteristics of the synthesized ligands and their metal complexes

Synthesis And In Vitro Biological Evaluation Of Metal Complexes Containing 2-Aminothiazole

2024-06-26T10:33:36+00:00

In the present study, Schiff bases and metal complexes containing 2-aminothiazole have been synthesized and characterized by physicochemical and spectral means. Broth dilution assay (96 well microtiter plate method) was used to evaluate antimicrobial activity of the synthesized compounds against Gram positive bacteria (B. subtilis), Gram negative bacteria (E. coli) and fungal species (A. niger and A. terreus) using cefadroxil (antibacterial) and fluconazole (antifungal) as standard drugs. Among the synthesized derivatives, Schiff base EVL₁ showed good activity against A. niger, A. terreus, B. subtilis (MIC_an,at,bs = 3.12 µg/ml). Complex MV₁showed good antifungal activity against A. niger (MIC_an= 1.56 µg/ml) similarly complex MV₁showed significant activity against E. coli, B. subtilis and A. terreus (MIC_ec,bs,at= 3.12 µ/ml) and MV₅ against A. niger (MIC_an = 1.56 µ/ml). Antioxidant (DPPH assay) 1,1-Diphenyl-2-picrylhydrazyl assay activity of the synthesized derivatives was determined using weight loss method. Schiff base MV₁showed excellent antioxidant activity (IC₅₀ = 46.56).

Reverse Migration: Comparative Study Of Internal And International Migrant Workers And State Potential

2024-06-26T10:45:07+00:00

The primary factors influencing migration within and between India and other countries are the current unemployment rate, the level of competition in the job market, and the improved opportunities for a better livelihood in the destination state or country. Conversely, the enforcement of a countrywide lockdown and the shutdown of interstate and international borders as strategies to control the spread of the COVID-19 pandemic led to a decline in the movement of informal migrant workers. To successfully reintegrate individuals impacted by the COVID-19 pandemic into the economy after its conclusion, the central and state governments must collaborate and develop efficient strategies. This study examines the complexities of reverse migration among migrant workers from both domestic and international origins. It highlights the government's potential role in supervising and taking advantage of this migration trend. This research aims to evaluate the different approaches adopted by the Indian government towards its domestic and international refugees during the phases of reverse migration, repatriation, and reintegration that followed the declaration of the lockdown. The paper begins by conducting a comparative analysis of the difficulties encountered by domestic and foreign migrant workers during these stages and how different countries dealt with the situation through their policies, the existing data collected from social workers and migrants facilitates this comparison. Furthermore, it scrutinizes the obstacles encountered by Indian migrants during their economic reintegration to craft welfare policies specifically designed for this demographic and the government's different responses to repatriation.

Understanding Of Trypan Blue Cytological Staining Increment Due To Biological Membrane Peroxidation

2024-06-26T10:58:09+00:00

Trypan Blue is an azo dye that extensively uses a marker to distinguish between viable and dead cells. This is because the plasma membranes of viable or live cells remain intact to uptake the Trypan Blue molecules, whereas in the case of non-viable or dead cells, there is the occurrence of membrane pores which may often be due to alterations like Phosphatidyl Serine inversion to the outer leaflet of their plasma membranes. Besides this, microvesicles or apoptotic bodies are formed due to membrane budding, which ultimately leads to the entry of Trypan Blue molecules if these cells are exposed to Trypan Blue. Moreover, Hydrogen peroxide (H2O2) has a pivotal contribution in oxidative stress-mediated and redox signaling-mediated cytological mortality. Due to its hydrophilicity, it can impact the property of selective permeability of plasma membranes. Being an oxidizing agent, H2O2 initiates halting at times of the progression of the cell cycle. It is evident that H2O2 accumulation in the cytoplasm triggers apoptosis. Apart from this, H2O2 can cause lipid peroxidation, which is perhaps the most valid aspect of Trypan Blue entry when both Trypan Blue and Hydrogen peroxide are simultaneously introduced to the viable cells, leading to their death with the passage of time.

A Novel Approach For Identifying Speech In Computational Intelligence

2024-06-27T05:18:39+00:00

The article examines the development of technology that recognizes speech, which is an especially significant use of artificial intelligence. Because AI is frequently featured in science fiction films, where people communicate with devices just like they'd interact with ordinary people, the concept is widely known. The two primary ways that humans naturally relate to their fellow humans are speech and actions. Speaking to a computer is made feasible by speech recognition. The equipment that converts spoken words into typographic text and directional instructions is called speech recognition programming. Speech recognition is utilized in legal and medical transcribing as well as in broadcasting news broadcasts along with live sports programming to create subtitles. It is challenging for technology to work out the spaces between sounds because there do not exist any pauses in spontaneously spoken English. The technique by which a computer converts an auditory voice signal to text is called automatic speech recognition.

By approximately 2010, these fundamental behavioral patterns will force the next level of technological developments into mainstream culture.

Deep Learning In Image Processing For Object Recognition Using Various Techniques

2024-06-27T05:22:19+00:00

Due of the field's tight ties to both picture interpretation and video analysis, object detection has seen a sharp rise in study interest in recent years. Shallow trainable structures and handcrafted characteristics are the foundation of traditional object recognition methods. Their efficacy quickly bottoms out because they build intricate ensembles that integrate higher level input from the object identification systems and the scene classifiers with low-level image data. Deep learning is developing at a rapid pace, giving researchers more effective methods to tackle issues with conventional architectures. These instruments are able to pick up more complex, semantic data. The network design, training procedure, optimization function, and other components of these models vary. An overview of object identification techniques based on deep learning is provided in this study. First, let's review deep learning and the convolutional neural network (CNN), which is its primary tool.

Now next discussion is for common generic object detection architectures and provide some useful tips and adjustments to improve the detection performance for further tasks. Additionally, as many particular detection tasks have distinct features, such as salient object recognition, we briefly examine a few specific tasks, such as face and pedestrian identification. Additionally, experiments are provided in order to assess various strategies and derive some significant conclusions. A range of numerical values reflect all that is visible to a computer. Thus, in order to examine the data contained in images, they need image processing algorithms. In terms of efficacy and speed, You But Look Once (YOLO), More Quickly Region-based neural networks based on convolution (Faster R-CNNs), and Single Shot Detection (SSD) are the most popular computational processing of pictures algorithms. This essay examines these techniques. This evaluation looks at the performance of these three algorithms and looks at their individual benefits and drawbacks using metrics like F1 score, accuracy, and precision. The technology being used for data collection is Microsoft COCO (Common Object in Context). The experiment's findings show that each algorithm's predominant use cases over the other two determine its relative superiority. YOLO-v3, the most optimal algorithm out of the three, outperforms the SSD drive and Faster R-CNN networks under the same testing conditions. In conclusion, a number of fascinating opportunities and challenges are outlined as a basis for further research in the fields of relevant neural network-based learning systems and object identification.

An Analysis of Revolutionizing Human-Computer Interaction with Blue Eyes Technology Using Reliability Theory

2024-06-27T07:20:22+00:00

An analysis of revolutionary human computer interaction with Blue Eyes Technology using reliability theory, a paradigm in human-computer interaction, aims to develop systems capable of perceiving and responding to human emotions and behavior. While the potential applications of this technology are vast and promising, ensuring its reliability remains a critical challenge. This research paper investigates the reliability aspects of Blue Eyes Technology, examining the challenges faced in accurately interpreting human emotions and behaviors, as well as the implications of system inaccuracies. The study finds that sensor accuracy, data processing methods, and algorithm resilience are important aspects influencing the reliability of Blue Eyes systems through a detailed review of previous research and case studies. Furthermore, it explores emerging strategies and technologies for enhancing reliability, such as machine learning algorithms, multimodal sensor fusion, and real-time feedback mechanisms. By addressing these challenges and leveraging innovative approaches, this research contributes to advancing the reliability of Blue Eyes Technology, paving the way for its effective implementation in various domains, including healthcare, education, and entertainment.

Enhancing Online Education Through Machine Learning: A Comprehensive Review And Future Directions

2024-06-28T11:29:35+00:00

Online learning environments are gaining popularity as an alternative to traditional learning environments during times of global pandemic. The traditional classroom setting has given way to online learning in recent educational developments. To employ it as a classifier in online education, the goal of this work is to construct a real-time face emotion detection system that recognizes and categorizes emotions of a human. It uses machine learning to identify, forecast, and analyse a learner's facial expressions, and it further maps those expressions to a learning affect that categorizes the emotions of those who are seen on camera. Academic feelings can have a significant impact on learning outcomes. Students typically show their emotions through their facial expressions, voice, and behavior. A spontaneous facial expression database is created in light of the inference algorithm's lack of training samples. It consists of two subsets: a video clip database and a picture database, and it includes the typical emotional facial expressions. The database contains 1,274 video clips and 30,184 photos from 82 pupils. The parameters for student facial detection can be used to gauge each learner's rate of concentration. The performances of the SVM and RF classifier in facial expression for the image are presented. The results of testing this with the RF algorithm and a 90.14% accuracy rate produced extremely good results.

Deep Learning Approach For Handwritten Gujarati Script Recognition Using Convolutional Neural Network

2024-06-29T09:55:35+00:00

Handwritten character recognition, particularly in languages like Gujarati, poses both opportunities and challenges for technological advancement and cultural preservation. This paper explores the significance of handwritten character recognition in Indian languages, focusing on Gujarati script, which features a complex character set and intricate writing styles. The use of Convolutional Neural Networks (CNNs) in recognizing handwritten characters is discussed, highlighting their ability to extract hierarchical representations from input images and surpass traditional recognition techniques. The architecture and training process of CNNs for handwritten character recognition are detailed, emphasizing their effectiveness in capturing spatial dependencies and structural information in handwritten characters. Literature surveys further demonstrate the growing interest in CNNs for various natural language processing tasks, including sentiment analysis and text classification. The potential for CNN-based techniques to develop unified models for multilingual text processing and improve script identification accuracy is highlighted, suggesting promising directions for future research in artificial intelligence and language technologies.

The Individual Readiness On Workforce Agility Of Indonesian Military Reserve Components

2024-06-29T11:07:55+00:00

The aim of this paper is to analyze the relationship between readiness to change, perceived organizational support, and workforce agility in the Indonesian Military Reserve Components. This study utilized a quantitative approach using structural equation modeling (SEM). The population comprised 3,103 Indonesian Reserve Component, with a sample of 356 individuals determined using the Slovin formula. Data analysis was conducted using SmartPLS v.4, including inner and outer measurement model tests. The study provides several results, firstly, individual readiness to change has a positive and significant influence on workforce agility. This is because rapid changes occur frequently in the military, and the ability to effectively respond to environmental changes is crucial for operational success. Secondly, individual readiness to change also has a positive and significant influence on perceived organizational support. Individuals with a higher level of readiness are more open to change and will make efforts to adapt quickly. Thirdly, perceived organizational support has a positive and significant influence on workforce agility. This is because the support provided by colleagues, superiors, and organizational policies enables reserve TNI members to work effectively and adapt to changes.

Preliminary On Results Lattices

2024-06-29T12:20:40+00:00

In the Paper Mainly we have obtained certain Preliminary results on Lattices and also we obtain certain characterization

Properties Of Distributive, Neutral And Standard Elements Of A Lattice -

2024-06-29T12:30:31+00:00

In this paper mainly we have obtained important properties of Distributive, Neutral and standard elements of a lattice. And also we have obtained certain equivalent conditions for a Distributive lattice.

“Safety And Efficacy Of Cisplatin Combined With Chemoradiotherapy In Locally Advanced Cervical Cancer Patients in Tertiary Care Hospital”

2024-07-02T06:19:09+00:00

Background: The number of cases of cervical cancer has increased in India during the previous year. Cervical cancer is a disease that causes morbidity and mortality worldwide. Cervical cancer patients progressed daily as a result of inadequate knowledge about the illness. Therefore, patient education is essential for both cervical cancer treatment and prevention. This research was done to find out if patients knew about the benefits and safety of combination chemotherapy and radiation therapy, or if they had any excuses for not getting their cervical cancer screened.

Objective:

To evaluate the safety and efficacy of cisplatin in conjunction with radiation and chemotherapy for females suffering from locally advanced cervical cancer.
To investigate the early outcome of cisplatin combined with chemotherapy and radiotherapy for cervical cancer patients.

Method: The study ran from October 2023 to April 2024 over the course of 7 month. There are a total number of 100 samples based on inclusion and exclusion criteria, patient data were collected. The quality of the data was evaluated by doing a database search for the safety and efficacy of cisplatin with chemotherapy in patients with locally advanced cervical cancer in Bihar using a questionnaire methodology.

Statistical analysis: All the data were recorded and analyzed. Statistics were carried out using SPSS software.

Results: This study involved 100 individuals in total. There are now 45 cases of people with cervical cancer. Twenty cases were eliminated from the study, leaving the remaining 25 cases eligible for inclusion based on the inclusion and exclusion criteria. The results of the trial showed that cisplatin and chemoradiotherapy are a safe and efficient combination for treating locally advanced cervical cancer.

Conclusion: Our study's results indicate that cisplatin in combination with radiation and chemotherapy is a tolerated and potentially better choice for treating patients with locally advanced cervical cancer. For the treatment of locally advanced cervical cancer, cisplatin and chemoradiotherapy may be given at the same time.

Simultaneous Equations Modeling: Examining The Relationship Between Money Wages, Labor, And Gross National Income In Jordan (2006-2022).

2024-07-02T09:53:39+00:00

This study delves into the structural simulation equations influencing the interrelation between W (money wages) and GNU (Gross National Income) simultaneous equations. The variables encompassed in both models include W, GNU, P, R, L, M, and the unemployment ratio, with all variable data expressed in percentage ratios, except for GNU, which is in millions J.D. The dataset draws from various sources, primarily relying on the Central Bank of Jordan's annual reports and I.M.F. reports spanning 2006–2022. Employing weighted least squares, two-stage least squares, the instrumental method, and Anova, the study scrutinizes the simultaneous equation models to ensure their fit to the data.

In this analytical framework, the structural equations of GNU involve both current and ratio values of affected variables in the structural models of GNU, with predictors and instrumental explanations including W, P, unemployment ratio, R, M, and L. The R-squared value for this model is 97.6%, indicating strong explanatory power. However, despite the high R-squared value, it is noteworthy that not all explanatory variables exhibit complete utility. In the TSLS (two-stage least squares) model, where the dependent variable is W (money wages), the predictors include the Unemployment ratio, P, R, M, GNU, and L. The R-squared in this model is 93.8%, revealing significant relationships between W, P, Unemployment ratio, and M. Notably, we deem the impact of GNU as not significant, suggesting it does not exert a substantial influence on money wages.