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In every network, traffic anomaly detection system is an essential field of study. In the communication system, there are various protocols and intrusions. It is still a testing area to find high precision to boost the correct distribution ratio. Many authors have worked on various algorithms such as simple classification, K-Means, Genetic Algorithm, and Support Vector Machine approaches, and they presented the efficiency and accuracy of these algorithms. In this article, we have proposed a feature extraction technique known as “k-means clustering,” which has its roots in signal processing and is employed to divide a set of n observations into k clusters, each of which has its origin from the observation with the closest mean. K-Means method is applied in this study to investigate the stream and its implementation and applications using Python and the dataset on the KDDcup99. The effectiveness of the outcome indicates the planned work’s efficiency in relation to other widely available alternatives. Apart from the applied method, a web-based framework is designed, which can inspect an actual network traffic packet for identifying network attacks. Instead of using a static file for testing the network attack, a web page-based solution uses database to collect and test the information. Real-time packet inspection is provided in the proposed work for identifying new attacks.

With the rapid increase in vehicle numbers, efficient traffic management has become a critical challenge for society. Traditional methods of vehicle detection and classification often struggle with the diverse characteristics of vehicles, such as varying shapes, colors, edges, shadows, and textures. To address this, we proposed an innovative ensemble method that combines two state-of-the-art deep learning models i.e., EfficientDet and YOLOv8. The proposed work leverages data from the Forward-Looking Infrared (FLIR) dataset, which provides both thermal and RGB images. To enhance the model performance and to address the class imbalances, we applied several data augmentation techniques. Experimental results demonstrate that the proposed ensemble model achieves a mean average precision (mAP) of 95.5% on thermal images, outperforming the individual performances of EfficientDet and YOLOv8, which achieved mAPs of 92.6% and 89.4% respectively. Additionally, the ensemble model attained an average recall (AR) of 0.93 and an optimal localization recall precision (oLRP) of 0.08 on thermal images. For RGB images, the ensemble model achieved mAP of 93.1%, AR of 0.91, and oLRP of 0.10, consistently surpassing the performance of its constituent models. These findings highlight the effectiveness of proposed ensemble approach in improving vehicle detection and classification. The integration of thermal imaging further enhances detection capabilities under various lighting conditions, making the system robust for real-world applications in intelligent traffic management. [ABSTRACT FROM AUTHOR]

The integration of closed-circuit television (CCTV) monitoring is crucial in the field of video processing, which provides an efficient method for comprehensive surveillance. However, a key challenge associated with this practice is its substantial demand for storage space. Typically, surveillance footage is stored in hard disk drives, and due to limited storage spaces, it is deleted after some time. To address this issue, an innovative method for compressing CCTV video, named object detection-based surveillance compression (ODSC), is introduced. Our ODSC model is divided into two steps: -i) depending upon the objects in the video, determine the significant and non-significant frames of surveillance video using the neural network approach YOLOv5s & YOLOv7-tiny and Yolov8s ii) construct the video of significant frames. Following a comprehensive analysis of the experimental outcomes, it is noted that YOLOv8s stands out with a remarkable detection accuracy of 99.7% on the COCO dataset. Our ODSC approach is reducing the storage space greatly and achieving an average compression ratio of up to 96.31% using YOLOv8s, which surpasses the existing state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Introduction: Methotrexate (MTX) has been the main drug that has been used worldwide for the treatment of Rheumatoid Arthritis (RA) either as a monotherapy or in combination with other Disease Modifying Antirheumatic Drugs (DMARD). Vitamin D deficiency has been shown to play an important role in the pathogenesis and progression of RA and its supplementation could have a promising role in management of RA. Aim: To evaluate the efficacy of vitamin D supplementation among newly diagnosed of RA cases scheduled for MTX monotherapy. Materials and Methods: This randomised controlled study was done at Era's Lucknow Medical College and Hospital, Lucknow, India from January 2016 to December 2017. A total of 100 newly diagnosed patients of RA (p<0.001) were randomised to two groups: group A (n=50) received MTX monotherapy supplemented with 400 IU 25 Hydroxy [25(OH)] vitamin D twice a day (case group) whereas group B (n=50) received MTX monotherapy with placebo. Serum 25 Hydroxy vitamin D (S. 25 OH), American College of Rheumatology (ACR) score, Erythrocyte Sedimentation Rate (ESR) and Serum C-Reactive Protein (S. CRP) were assessed at enrolment, 3 months and 6 months. Data was analysed using Statistical Package for Social Sciences software (SPSS) version 21.0 software. Chi-square and Independent samples t test were used to compare the data. Results: Overall majority of patients were females 57% and 43% were males with mean age 40.98±8.83 years (range 26-60 years). At baseline, mean vitamin D levels were 22.94±12.41 and 25.54±12.79 ng/mL in groups A and B respectively (p-value>0.305). Mean ACR scores at baseline, 3 months and 6 months were 7.06±0.77, 5.16±1.11 and 4.42±0.93 respectively in group A and 7.02±0.74, 5.78±0.98 and 5.11±1.11 respectively in group B. At final follow-up, mean reduction in ACR scores and S. CRP levels was significantly higher in group A as compared to that in group B (p-value<0.001). Simultaneously, there was a significantly higher increase in vitamin D levels in group A as compared to that in group B (p-value<0.001). Conclusion: Vitamin D supplementation helped to potentiate the efficacy of MTX monotherapy in RA. Vitamin D deficiency causes diffuse musculoskeletal pain and its supplementation is needed for osteoporosis prevention. [ABSTRACT FROM AUTHOR]

HTTP Adaptive Streaming (HAS) of video content is becoming an undivided part of the Internet and accounts for most of today’s network traffic. Video compression technology plays a vital role in efficiently utilizing network channels, but encoding videos into multiple representations with selected encoding parameters is a significant challenge. However, video encoding is a computationally intensive and time-consuming operation that requires high-performance resources provided by on-premise infrastructures or public clouds. In turn, the public clouds, such as Amazon elastic compute cloud (EC2), provide hundreds of computing instances optimized for different purposes and clients’ budgets. Thus, there is a need for algorithms and methods for optimized computing instance selection for specific tasks such as video encoding and transcoding operations. Additionally, the encoding speed directly depends on the selected encoding parameters and the complexity characteristics of video content. In this paper, we first benchmarked the video encoding performance of Amazon EC2 spot instances using multiple ×264 codec encoding parameters and video sequences of varying complexity. Then, we proposed a novel fast approach to optimize Amazon EC2 spot instances and minimize video encoding costs. Furthermore, we evaluated how the optimized selection of EC2 spot instances can affect the encoding cost. The results show that our approach, on average, can reduce the encoding costs by at least 15.8% and up to 47.8% when compared to a random selection of EC2 spot instances. [ABSTRACT FROM AUTHOR]

Homestays are a form of tourism experience itself, which allows tourists to experience the real culture and traditions of the host community very closely and get the opportunity to get involved with some. Homestays provide a diverse range of activities to give tourists a unique opportunity to experience the unique culture and traditions of the local people. The purpose of this paper is to analyze the prospects and problems in developing homestays in Ayodhya. Ayodhya is progressing toward massive inclusive tourism development, which includes accommodation, and the government's focus is also on Ayodhya's tourism expansion, which will create many opportunities for local communities to develop homestays as one of the economic sources and which will be the best alternative for budget travelers. This will bring light to the prospects and problems of developing homestays. [ABSTRACT FROM AUTHOR]

More than 185 countries get affected in the present SARS-COV-2 (aka COVID-19 or n-Corona virus) epidemic. Experts from different domains are contributing a lot to combat this pandemic effectively. Data analysts have made lots of efforts, IT experts also to forecast the severity of infected cases, the death rate, recovery rate, and other health indicators using various statistical and machine learning models. These forecasting models may motivate and help the policymakers to make the decisions based on these predicted results. Although any prediction on such a pandemic problem is non-monotonic and uncertain, these predictions may help us plan to take the needful actions while dealing with this tragic situation. Lots of symptomatic and asymptotic human behavior are observed while investigating the cases. Also, many countries are making dynamic changes in their policies to combat this pandemic. Therefore, such heterogeneous and dynamic changes in policies and human behavior make the problem of proposing an accurate predicting model more complex. We used machine learning methods to monitor the COVID-19 impact country-wise and developed a FOCOMO model to forecast the severity worldwide till the mid of Oct 2020. We referred to the COVID-19 dataset publicly shared by John Hopkins University. We proposed a purely predictive model to monitor the pandemic (without claiming it as perfect or accurate) into three Phases: i) categorization of countries based on the severity of COVID-19 cases, ii) prediction of daily case reporting, and iii) normalization of flattening the forecasting curve based on deaths and recovery rate. These forecasting models will help monitor and plan the human behaviors and severity of the pandemic country-wise and will provide an opportunity to take some corrective actions for shaping the future. [ABSTRACT FROM AUTHOR]

Machine Translation is an area of Natural Language Processing which can replace the laborious task of manual translation. Sanskrit language is among the ancient Indo-Aryan languages. There are numerous works of art and literature in Sanskrit. It has also been a medium for creating treatise of philosophical work as well as works on logic, astronomy and mathematics. On the other hand, Hindi is the most prominent language of India. Moreover,it is among the most widely spoken languages across the world. This paper is an effort to bridge the language barrier between Hindi and Sanskrit language such that any text in Hindi can be translated to Sanskrit. The technique used for achieving the aforesaid objective is rule-based machine translation. The salient linguistic features of the two languages are used to perform the translation. The results are produced in the form of two confusion matrices wherein a total of 50 random sentences and 100 tokens (Hindi words or phrases) were taken for system evaluation. The semantic evaluation of 100 tokens produce an accuracy of 94% while the pragmatic analysis of 50 sentences produce an accuracy of around 86%. Hence, the proposed system can be used to understand the whole translation process and can further be employed as a tool for learning as well as teaching. Further, this application can be embedded in local communication based assisting Internet of Things (IoT) devices like Alexa or Google Assistant. [ABSTRACT FROM AUTHOR]

Gangrene is a type of tissue death caused by lack of blood supply. Symptoms may include a change in skin color red or black, numbness, swelling, pain, ulceration and detachment of local skin. The feet and hands are most commonly affected. This condition may arise because of an injury, infection or other health conditions, majorly diabetes. Gangrene and its associated amputations are clinically challenging, but Ayurveda offers therapy options. In Ayurveda, gangrene can be considered as Kotha under Dushta Vrana due to Margavarana and Dhatu Kshaya. This case study aims to investigate whether Ayurvedic intervention can manage Kotha (gangrene) without amputation of the gangrenous part. A 45-year old woman came to the outpatient department (OPD) of Regional Ayurveda Research Institute for Drug Development, Gwalior, with clinical features indicative of dry gangrene. She was examined and diagnosis was confirmed by previous reports of X-ray and arterial color doppler. This case of dry gangrene was managed by Ayurvedic intervention of Kaishore Guggulu 1 g twice a day and Sanjivani Vati 250 mg thrice a day and Dashanga Lepa local application as a Lepa twice a day with lukewarm cow Ghrita for 2 months at OPD level. The response to the treatment was found highly effective. At the end of the treatment period of 2 months as compared with baseline, a highly significant change was observed. Kaishore Guggulu, Sanjivani Vati and Dashanga Lepa in the above-mentioned dose were found very effective and safe in a patient of dry gangrene. [ABSTRACT FROM AUTHOR]

Abstract We study constraints imposed by two proposed string Swampland criteria on cosmology. These criteria involve an upper bound on the range traversed by scalar fields as well as a lower bound on | ∇ ϕ V | / V when V > 0. We find that inflationary models are generically in tension with these two criteria. Applying these same criteria to dark energy in the present epoch, we find that specific quintessence models can satisfy these bounds and, at the same time, satisfy current observational constraints. Assuming the two Swampland criteria are valid, we argue that the universe will undergo a phase transition within a few Hubble times. These criteria sharpen the motivation for future measurements of the tensor-to-scalar ratio r and the dark energy equation of state w , and for tests of the equivalence principle for dark matter. [ABSTRACT FROM AUTHOR]

Introduction: Periodontitis and increased levels of Tumor Necrosis Factor-alpha (TNF-α) are considered as key factors contributing to the bone loss observed in oestrogen deficient post-menopausal women. Aim: The present study aimed at assessing the levels of salivary TNF-α in pre- and post-menopausal women with chronic periodontitis and evaluating its potential as a biochemical marker of periodontal disease in post menopausal women. Materials and Methods: A total of 80 female subjects, within the age range of 35-55 years, were divided into 4 groups of 20 subjects each, pre- and post-menopausal women with chronic periodontitis and pre- and post-menopausal periodontally healthy controls. After assessment of clinical periodontal status, unstimulated whole saliva was collected and levels of TNF-α were examined using ELISA. One-way ANOVA, posthoc Tukey's test, Student's unpaired t-test and Karl Pearson's co-efficient of correlation were used. SPSS version 17.0 and MedCalc version 10.2 were used to perform the data analyses. Results: The mean of salivary TNF-α levels in pre- and post-menopausal women with chronic periodontitis were 4.25±1.20 pg/mL and 5.13±1.35 pg/mL, respectively, whereas that in pre- and post-menopausal healthy controls were 2.05±1.11 pg/mL and 2.40±1.08 pg/mL, respectively. The levels of salivary TNF-α were significantly higher in the periodontitis groups than the controls and correlated positively with the assessed clinical parameters (p<0.001). Also the levels were significantly higher in post-menopausal women with chronic periodontitis than the pre-menopausal women with chronic periodontitis (p<0.05). Conclusion: Salivary levels of TNF-α were increased in both menopause and chronic periodontitis. This increased secretion of TNF-α could be implicated as a contributing factor in the progression of periodontal disease in post-menopausal women, suggesting that salivary TNF-α can act as a potential biomarker and a valuable adjunct for screening of periodontal disease in post-menopausal women. [ABSTRACT FROM AUTHOR]

This paper explains two approaches to develop transliteration tool which helps to convert text written in English language to equivalent Sanskrit language. First approach is through typing using computer keyboard while second approach explains typing through virtual keyboard method. Our objective is to implement a user friendly and robust tool that provides facility to users about to convert English text into Sanskrit language without any error. Major application of this tool is to train the students at school level and make them learnable. This tool promotes the use of native language among the users too. Another major application of this tool is to write govt notices, story writing, article writing etc. [ABSTRACT FROM AUTHOR]

Tetra-amelia is an extremely rare congenital anomaly. Here, we describe a liveborn neonate with the absence of all four limbs, exstrophy of bladder, cleft lip and palate, dysmorphic face, and other anomalies. This case is reported here because of its rare hereditary occurrence and association with other anomalies. [ABSTRACT FROM AUTHOR]

We study the phenomenology of a light stop NLSP in the presence of large mixing with either the first or the second generation. R-symmetric models provide a prime setting for this scenario, but our discussion also applies to the MSSM when a significant amount of mixing can be accommodated. In our framework the dominant stop decay is through the flavor violating mode into a light jet and the LSP in an extended region of parameter space. There are currently no limits from ATLAS and CMS in this region. We emulate shape-based hadronic SUSY searches for this topology, and find that they have potential sensitivity. If the extension of these analyses to this region is robust, we find that these searches can set strong exclusion limits on light stops. If not, then the flavor violating decay mode is challenging and may represent a blind spot in stop searches even at 13TeV. Thus, an experimental investigation of this scenario is well motivated. [ABSTRACT FROM AUTHOR]

The article describes a case of residual ridge resorption in a 77-year-old male patient presented with chief complaint of replacement of existing dentures. The old man was reported to be edentulous for the past 20 years and was wearing complete denture prosthesis since then. A resorbed maxillary ridge with sunken cheeks and deepening of nasolabial folds was revealed in the patient's clinical evaluation. Also noted is the challenge of treating alveolar ridges for prosthodontists.

The article offers information on electrical discharge machining (EDM) or the spark erosion process used in dentistry. It is described as the modern precision laboratory procedures by which a metal is contoured into a desired shape by erosion. The two types of EDM include wire and probe, the latter of which can be used in dentistry. The mechanics, history, scope and advantages and disadvantages of the spark erosion process are also discussed.

This article discusses the use of Computer-Aided Design (CAD)/Computer-Aided Manufacturing (CAM) technology for fabricating conventional complete dentures. The early uses of the technology in dentistry are cited including clinical dental restorations and tooth-colored restorations. The advantages of CAD-CAM dentures are listed such as reduction in chair time. The article also shows how the technology is used to produce maxillary and mandibular definitive impressions of edentulous arches.

This article provides information on the Eagle's syndrome. This syndrome is an aggregate of symptoms that are the direct result of an elongated styloid process or a calcified stylohyoid ligament. Its history, etiology and pathophysiology is discussed. Diagnostic tests for this syndrome include radiographic examination, three-dimensional computed tomography and infiltration test. Treatments available include non-surgical treatment and intraoral transpharyngeal approach.