Video frame feeding approach for validating the performance of an object detection model in real-world conditions

The challenge of evaluating deep learning-based object detection models in complex traffic scenarios, characterized by changing weather and lighting conditions, is addressed in this study. Real-world testing proves time and cost-intensive, leading to the proposal of a Video Frame Feeding (VFF) approach as a solution. The proposed Video Frame Feeding approach acts as a bridge between object detection models and simulated environments, enabling the generation of realistic scenarios. Leveraging the CarMaker (CM) tool to simulate realistic scenarios, the framework utilizes a virtual camera to capture the simulated environment and feed video frames to an object identification model. The VFF algorithm, with automated validation using simulated ground truth data, enhances detection accuracy to over 95% at 30 frames per second within 130 meters. Employing the You Only Look Once (YOLO) version 4 and the German Traffic Sign Recognition Benchmark dataset, the study assesses a traffic signboard identification model across various climatic conditions. Notably, the VFF algorithm improves accuracy by 2% to 5% in challenging scenarios like foggy days and nights. This innovative approach not only identifies object detection issues efficiently but also offers a versatile solution applicable to any object detection model, promising improved dataset quality and robustness for enhanced model performance

IoT–smart contracts in data trusted exchange supplied chain based on block chain

Internet of Things (IoT) assumes a critical part in the advancement of different fields. The IoT data trusted exchange in recent year extend of uses influence an awesome request and increasing scale. In such a platform, exchange the data sets that they require and specialist organization can search. However, the enough trust as the third-party mediators for data exchange in centralized infrastructure cannot provide. This paper proposes a blockchain for IoT data trusted exchange based on decentralized solution. In particular, the fundamental standards of blockchain in verify manner, individuals can communicate with each other without a confided in mediator intermediary. Blockchain enable us to have a distributed, digital ledger. IoT (Internet of Things) sensor devices (zigbee) utilizing blockchain technology to assert public availability of temperature records, tracking location shipment, humidity, preventing damage, data immutability. The sensor devices looking the temperature, location, damage of each parcel during the shipment to completely guarantee directions. In blockchain all data is got moved from one position to another, where a smart contract assesses against the product attributes. Ethereum blockchain and smart contracts atlast it gets through knowledge a design to be copied and presents its decentralized distributed digital ledger, auditable, transparent, features visually

An enhanced kernel weighted collaborative recommended system to alleviate sparsity

User Reviews in the form of ratings giving an opportunity to judge the user interest on the available products and providing a chance to recommend new similar items to the customers. Personalized recommender techniques placing vital role in this grown ecommerce century to predict the users’ interest. Collaborative Filtering (CF) system is one of the widely used democratic recommender system where it completely rely on user ratings to provide recommendations for the users.  In this paper, an enhanced Collaborative Filtering system is proposed using Kernel Weighted K-means Clustering (KWKC) approach using Radial basis Functions (RBF) for eliminate the Sparsity problem where lack of rating is the challenge of providing the accurate recommendation to the user.  The proposed system having two phases of state transitions: Connected and Disconnected. During Connected state the form of transition will be ‘Recommended mode’ where the active user be given with the Predicted-recommended items. In Disconnected State the form of transition will be ‘Learning mode’ where the hybrid learning approach and user clusters will be used to define the similar user models. Disconnected State activities will be performed in hidden layer of RBF and Connected Sate activities will be performed in output Layer. Input Layer of RBF using original user Ratings. The proposed KWKC used to smoothen the sparse original rating matrix and define the similar user clusters. A benchmark comparative study also made with classical learning and prediction techniques in terms of accuracy and computational time. Experiential setup is made using MovieLens dataset

Mobile Health Service Adoption: Reducing the Digital Gap and Age's Moderating Influence

In the past few years, mobile health services (MHS)—a growing topic in the healthcare sector—have received increasing attention. Technologies related to mobile health, or m-health, have several advantages for people, businesses, and medical professionals. Indeed, using m-health can help older people become more proactive patients and lessen the strain on health systems and financial resources. However, the potentially revolutionary impact of m-health is constrained since a large number of senior citizens oppose its adoption, which creates an age-based digital divide. Few studies have examined how public consumers of MHS adopt MHS, even though prior study on this topic is very substantial. We discover that user attitudes towards MHS are positively impacted by perceived benefits and usefulness, perceived barriers, and external cues. Perceived service availability also has a major impact on perceived benefits and usefulness, which, when combined with attitude, directly increases intention. Additionally, we discover that the MHS’s utilization intent has moderating effects. The final section discusses the implications for mobile health marketing. The results indicate that perceived ease of use, vulnerability, and severity are more significant factors for middle-aged and older users to use MHS. The moderator analysis confirmed that different age groups have specific moderating effects on the adoption of mobile health services

Quantum cryptography for secured communication networks

Quantum cryptography is a method for accessing data with the cryptosystem more efficiently. The network security and the cryptography are the two major properties in securing the data in the communication network. The quantum cryptography uses the single photon passing through the polarization of a photon. In Quantum Cryptography, it's impossible for the eavesdropper to copy or modify the encrypted messages in the quantum states in which we are sending through the optical fiber channels. Cryptography performed by using the protocols BB84 and B92 protocols. The two basic algorithms of quantum cryptography are Shor’s algorithm and the Grover’s’s algorithm. For finding the number of integer factorization of each photon, Shor’s algorithm is used. Grover’s’s algorithm used for searching the unsorted data. Shor’s algorithm overcomes RSA algorithm by high security. By the implementation of quantum cryptography, we are securing the information from the eavesdropper and thereby preventing data in the communication channel

Healthcare information exchange using blockchain technology

Current trend in health-care industry is to shift its data on the cloud, to increase availability of Electronic Health Records (EHR) e.g. Patient’s medical history in real time, which will allow sharing of EHR with ease. However, this conventional cloud-based data sharing environment has data security and privacy issues. This paper proposes a distributed solution based on blockchain technology for trusted Health Information Exchange (HIE). In addition to exchange of EHR between patient and doctor, the proposed system is also used in other aspects of healthcare such as improving the insurance claim and making data available for research organizations. Medical data is very sensitive, in both social as well as legal aspects, so permissioned block-chain such as Hyperledger Fabric is used to retain the necessary privacy required in the proposed system. As, this is highly permissioned network where the owner of the network i.e. patient holds all the access rights, so in case of emergency situations the proposed system has a Backup Access System which will allow healthcare professionals to access partial EHR and this backup access is provided by using wearable IOT device

FORMULATION AND EVALUATION OF MICROEMULSION GEL FOR TRANSDERMAL DELIVERY OF TRAMADOL

Objective: The present work was carried out to design microemulsion gel system for transdermal delivery of the drug to minimize the side effects and to reduce the frequency of administration and for prolonging the duration of action. Methods: Tramadol, an opioid analgesic drug, was mixed with various selected polymers such as sodium alginate (SA), acacia, hydroxypropyl methylcellulose (HPMC), and Eudragit in geometric mixing ratios. The drug, polymer, and other excipients were mixed thoroughly by trituration method and different formulations (F1-F8) were prepared the same quantity of all the ingredients excepting the polymers. Results: The different formulations prepared, studied, and showed that the formulation using SA as polymeric carrier had a better effect on the evaluated parameters. The drug-SA formulation exhibited better drug-polymer compatibility, optimal viscosity (2750 cps), zeta potential (−26.1 Mv), and particle size distribution (262.8 d.nm) values. The in vitro release studies also indicated that the drug-SA formulation was of desirable release pattern, thus indicating that SA to be a better choice in formulating a transdermal delivery gel system. Conclusion: Evaluated microemulsion gel formulation F2 of tramadol with polymeric carriers SA was much stable than other carriers used. Thus, it could be concluded that the gel formulation with SA can be taken as an ideal formulation

A time efficient and accurate retrieval of range aggregate queries using fuzzy clustering means (FCM) approach

Massive growth in the big data makes difficult to analyse and retrieve the useful information from the set of available data’s. Statistical analysis: Existing approaches cannot guarantee an efficient retrieval of data from the database. In the existing work stratified sampling is used to partition the tables in terms of static variables. However k means clustering algorithm cannot guarantees an efficient retrieval where the choosing centroid in the large volume of data would be difficult. And less knowledge about the static variable might leads to the less efficient partitioning of tables. Findings: This problem is overcome in the proposed methodology by introducing the FCM clustering instead of k means clustering which can cluster the large volume of data which are similar in nature. Stratification problem is overcome by introducing the post stratification approach which will leads to efficient selection of static variable. Improvements: This methodology leads to an efficient retrieval process in terms of user query within less time and more accuracy

BIO-ANALYTICAL METHOD DEVELOPMENT AND VALIDATION FOR THE SIMULTANEOUS ESTIMATION OF DECITABINE AND CEDAZURIDINE IN HUMAN PLASMA USING LC-MS/MS

Objective: The present work aimed to develop a novel, reliable and accurate Liquid Chromatography-Mass Spectrometry/Mass spectrometry (LC-MS/MS) method for the simultaneous quantification of Decitabine and Cedazuridine a combined medication used for the treatment of chronic myelomonocytic leukemia in human plasma. Methods: Talazoparib drug is used as an internal standard in the study. Both the analytes and internal standard were isolated from 100 ml plasma samples by liquid-liquid extraction and then chromatographed on Zorbax SB-CN (4.6 mm×75 mm, 3.5 µm) column with a mobile phase consisting of 0.1 % ammonium formate and methanol in the ratio of 65:45 (v/v) pumped at 0.5 ml/min. The method had a chromatographic total run time of 5 min. Results: The developed method gave a symmetric peak at a retention time of 1.7 min for Decitabine, 2.2 min for Cedazuridine, 3.5 min for Talazoparib and satisfied all the peak properties as per USP guidelines. The mass spectral characterization of separated analytes in the LC method was performed using a mass detector operated at Multiple Reaction Monitoring mode with precursor-to-product ion transitions at m/z of 229 to m/z of 114 as MH+ion for Decitabine, m/z of 269 to m/z of 118 as MH+ion for Cedazuridine. A very sensitive limit of detection of 0.3 ng/ml was observed and showed a calibration curve linear over the concentration range of LLOQ (lower limit of quantification) to 500 ng/ml. The other validation parameters were found to have acceptable accuracy, precision, linearity, and selectivity. The mean extraction concentration was acceptable and very high for both the analytes in HQC (high-quality control concentration), MQC (medium quality control concentration) and LLOQ levels. The peak area response ratio of Decitabine and Cedazuridine with the internal standard in freeze-thaw, short term and long term stability studies was found to be acceptable confirms that the method is stable. Conclusion: It can be concluded that the proposed method is specific, accurate, and precise and could be used for the simultaneous estimation of Decitabine and Cedazuridine in human plasma

Development And Evaluation Of Colon Targeted Drug Delivery For Mesalamine

The main objective of this study was to formulate mesalamine loaded alginate microspheres for local treatment of ulcerative colitis and optimized batch were then filled in capsules coated with Eudragit S 100. The microspheres were prepared by ionic gelation method. Box Behnken design using design expert software was employed in formulating and optimizing the microspheres. Microspheres were evaluated for particle size, shape and entrapment efficiency. The optimized batch was then filled in capsule coated with Eudragit S100.This encapsulated system released alginate microspheres at colon region in a sustained manner. The drug release of microspheres showed a longer residence time in the colon due to better mucoadhesion properties of sodium ALG. Therefore mesalamine-loaded alginate microspheres enteric coated in capsules can be potential delivery system for local treatment of ulcerative coliti