３回の対称性を持つ基板上に成膜したエピタキシャルフェライト薄膜の磁気特性

筑波大学 (University of Tsukuba)201

An Econometric Analysis of Bombay Stock Exchange: Annual Returns Analysis, Day-of-the-Week Effect and Volatility of Returns

This paper investigates the presence of day-of-the-week effect, returns volatility and analyzes the annual returns of Bombay Stock Exchange. A set of parametric and nonparametric tests is used to test equality of mean returns and standard deviations of the returns across the-days-of-the-week. To supplement this analysis, graphical representation of the index annual percentage changes was explored. The results contradict the presence of the-day-of-the- week but indicate insignificant daily returns volatility in most of these Markets. The stock exchanges experienced enormous growth between 2001 and 2010. The result of the Levenes test value for Bombay Stock Exchange was 0.847 which concludes that the daily return seasonalities are not accompanied by any volatility seasonality and investing on low (high) return weekday does not necessarily mean that risk is also low or high and Index that has marginally significant Levenes statistic. Key words: Volatility of Returns, Bombay Stock Exchange, Day-of-week effec

Effects of Web-Based Survey Tool and Public Health Services for Low-Cost Detection of Vulnerable Medication Errors Using Telepharmacy

Telepharmacy, in which prescription requests are reviewed and approved online by a pharmacist in a different geography, is an effective way to lower the number of mistakes made when giving medicines. However, not enough studies have been done on the benefits of error reduction and the possible cost savings that come with these teleservices. This paper discusses a study examining what happened when a web-based survey tool and telepharmacy solutions were used to find Vulnerable Medication (VM) errors and low-cost Public Health (PH) services. It is very important to get each patient\u27s drug records when they come into the Emergency Room (ER) so that any mistakes in their current medication record can be found. The trained pharmacists were interviewed after using a safe online tool to keep track of drug information. Details about each patient were gathered, along with the amount and type of VM and any PH errors found during the data-gathering procedure. From May 2022 to November 2022, 190 patient files were successfully filled up utilizing the survey instrument throughout the experimental period. Among the 1090 drugs documented, 41.38% were classified as drugs of high risk. 42.33% of possible prescription mistakes were categorized as VM errors. This online survey tool has enhanced the caliber and effectiveness of identifying possible errors during the gathering of medication records by pharmacists. This data may be readily accessed and contribute to debates about the reconciliation of drugs at the management level. It can also positively affect patient care outcomes by facilitating the development of virtual procedures that may reduce drug-related incidents

Behaviour based botnet detection with traffic analysis and flow intervals at the host level

A botnet is one of the most dangerous forms of security issues. It infects unsecured computers and transmit malicious commands. By using botnet, the attacker can launch a variety of attacks, such as distributed denial of service (DDoS), data theft, and phishing. The botnet may contain a lot of infected hosts and its size is usually large. In this paper, we addressed the problem of botnet detection based on network’s flows records and activities in the host. We proposed a host-based approach that detects a host, that has been compromised by observing the flow of in-out bound traffic. To prove the existence of command and control communication, we examine host network flow. Once the bot process has been identified in the host being monitored, this knowledge allows blocking any in/out traffic with the bot’s server. In addition to providing information about the compromised machine’s IP address and how it communicates with servers, the log file is generated, which can provide data about the command and control (C&C) servers. Most existing work on detecting botnet is based on flow-based traffic analysis by mining their communication patterns. Our work distinguishes itself from other methods of bot detection from its ability to use real-time host-related data for detection

A survey on enhancements of routing protocol for low power and lossy networks: focusing on objective functions

People live in the age of smart devices. The concept of the internet of things (IoT) needs to be brought up whenever smart gadgets are shown. Furthermore, every gadget is gradually turning into a mobile node. These devices are utilized in low power and lossy networks because of their characteristics. Numerous obstacles exist in this field, motivating academics to focus on routing, connections, data transfer, and communications between nodes. In relation to this, the internet engineering task force (IETF) group already created a routing protocol for low power and lossy network (RPL), which was suggested for static networks and has since undergone numerous improvements. This article introduces the low power wireless network (LPWN) with a detailed model of the RPL protocol. It has also been considered how the destination-oriented directed acyclic graph (DODAG) is formed, and control messages are used to communicate between nodes in the RPL. The objective function (OF) is the center of the RPL. The principal objective functions objective function zero (OF0) and minimum rank with hysteresis objective function (MRHOF), which IETF group suggested, cannot function in the existing mobile network due to node disconnection and intermittent connectivity. The authors have enumerated and briefly discussed numerous RPL enhancements with new OFs. Numerous problems that the RPL routing protocol faced with mobility have been resolved

Performance evaluation of botnet detection using machine learning techniques

Cybersecurity is seriously threatened by Botnets, which are controlled networks of compromised computers. The evolving techniques used by botnet operators make it difficult for traditional methods of botnet identification to stay up. Machine learning has become increasingly effective in recent years as a means of identifying and reducing these hazards. The CTU-13 dataset, a frequently used dataset in the field of cybersecurity, is used in this study to offer a machine learning-based method for botnet detection. The suggested methodology makes use of the CTU-13, which is made up of actual network traffic data that was recorded in a network environment that had been attacked by a botnet. The dataset is used to train a variety of machine learning algorithms to categorize network traffic as botnet-related/benign, including decision tree, regression model, naïve Bayes, and neural network model. We employ a number of criteria, such as accuracy, precision, and sensitivity, to measure how well each model performs in categorizing both known and unidentified botnet traffic patterns. Results from experiments show how well the machine learning based approach detects botnet with accuracy. It is potential for use in actual world is demonstrated by the suggested system’s high detection rates and low false positive rates

３回の対称性を持つ基板上に成膜したエピタキシャルフェライト薄膜の磁気特性

筑波大学 (University of Tsukuba)201

An Efficient Image Fusion of Visible and Infrared Band Images using Integration of Anisotropic Diffusion and Discrete Wavelet Transform

Image fusion is a technique that combines two source images to generate more informative target image. It plays a vital role in medical image investigation, military, navigation, etc. visible images offer efficient texture detail with high spatial resolution. In contrast, based on the radiation difference infrared images are able to differentiate target from their background. There are many algorithms that helps in preserving the edges of image like Bilateral filter, anisotropic diffusion (ADF). This paper integrates Anisotropic Diffusion and Karhunen-Loeve (KL)Transformation with discrete wavelet transform (DWT). In proposed Method, DWT decomposes into four sub-bands. ADF is applied on approximation sub-band and absolute maximum selection is applied on other three sub-bands. ADF decomposes the image into detailed layer and base layer. Base layer and Detailed layer are calculated using Kl- Transformation and linear combination respectively. Once fusion is done, inverse DWT is applied on all sub-bands. The experimental outcomes depict that the offered approach result with sharp edges of the image. The proposed algorithm is evaluated on standard dataset Like Duine_Sequence, Tree_sequence, Street dataset. Standard metrics like Average Gradients and Spatial Frequency metrics are used to evaluate the performance of the image

Seasonal Incidence of Stem Borer (Chilo partellus L.) on Maize (Zea mays)

The Field experiment was carried out at the Entomological experimental field, Diksha Bhawan, Institute of Agriculture and Natural Science, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur (Uttar Pradesh) during the Kharif season 2023 to study on “Seasonal incidence of stem borer (Chilo Partellus L.) on Maize (Zea mays). The pest activity was initially observed in the 32nd SMW and continued till the crop harvesting stage 43rd SMW. The recorded percentage of dead heart ranged from 0.33 to 3.27 per cent during the year, 2023. The percentage of dead heart formation was low from the first week of August to the end of August and varied from 0.33 to 1.67 per cent. The dead heart formation increased from the first week of September and reached its peak i.e. 3.27 per cent during the 39th standard week. It is evident from the correlation of per cent dead heart of stem borer, C. partellus was found positive with maximum (r= 0.371) and minimum (r= 0.34) temperature during, 2023. The correlation between dead heart with morning and evening relative humidity was found positive r= 0.07 and 0.221, respectively. While rainfall negative correlation r= -0.359 dead heart of C. partellus, respectively during the year 2023. The correlation coefficient between the larval population of C. partellus and weather parameters presented in the data revealed that the correlation of the larval population of C. partellus was found positive with maximum (r= 0.334) and minimum (r= 0.362) temperature during the year, 2023. The correlation between larval population with morning and evening relative humidity was found negative r= -0.092 and r= -0.304, respectively. While rainfall had negative correlation (r= -0.313) larval population

PULSATILE RELEASE OF KETOPROFEN FROM COMPRESSION COATED TABLETS USING EUDRAGIT® POLYMERS

Objective: The objective of the present research work is to develop compression coated tablet of ketoprofen as a pulsatile release system for treatment of rheumatoid arthritis.Methods: Core tablets of ketoprofen were prepared using the wet granulation method and evaluated for appearance, hardness, friability, weight variation, thickness, disintegration time and % drug release. Core tablets were coated with Eudragit S100 and Eudragit L100 by compression coating method to achieve desired lag time. The blends of core and coating materials were evaluated for bulk density, tapped density, Hausner's ratio, % Compressibility index and angle of repose. Compression coated tablets were evaluated for appearance, hardness, friability, weight variation, thickness and % drug release.Results: Core tablets, as well as compression coated tablets, showed acceptable Pharmaco technical properties. Optimized core tablets were disintegrated within 15s due to the effectiveness of super disintegrant, sodium starch glycolate. Dissolution studies of compression coated tablets in media with different pH (1.2, 6.8, and 7.4) showed that drug release could be modulated by changing the concentration of EudragitL100 and Eudragit S100. The optimized batch exhibited 80% drug release up to 6 h with a 4 h lag time. Stability study of the optimized formulation indicated no significant change in appearance, physical parameters, drug content and drug release profile at accelerated conditions for two months.Conclusion: compression coated tablet of ketoprofen was successfully developed to achieve burst drug release after specific lag time.Keywords: Chronomodulated drug delivery, Pulsatile release, Compression coated tablets, Lag tim