مطالب

The cybersecurity in the modern world has become global, and cyber attacks are becoming more complex and large-scale. In the system of civil and criminal justice, computer forensics helps to ensure the integrity of digital evidence presented in court cases. The purpose of this study is to develop scientifically sound proposals and recommendations for the implementation of tools for forensic research of computer tools and systems in the fight against cybercrime. The relevance of this study is due to the need to implement active ways to protect and combat cybercrime. To achieve the goal of the study, methodological principles and approaches of legal science were used. It is proposed to use computer forensic methods more widely research in the fight against cybercrime.This study identifies the types of computer forensics: forensics database; electronic forensics; malware forensics; criminology of memory; mobile forensics; network forensics. The authors foundlack of a regulatory mechanism to regulate cybersecurity, capture and use of digital evidence and the regulatory framework for international cooperation. To brought need in strengthening international cooperation and in developing appropriate policies and legislative initiatives of security and network and information systems, improvement legislation in the field countering cybercrime.

The rapid emergence and evolution of technology have greatly impacted the way people live their lives. The internet has become a vital part of our daily lives. E-commerce is a type of technology development that enables customers to buy and sell products online. It is a unique form of transaction that connects people from all around the world. Today, many consumers shop for products online and present their products along with their specifications. This is becoming more prevalent. This increases the number of consumers online, which can result in a drop in growth. This is one of the main factors that a company uses to measure its success. Growing business success is revealed with retained customers. Satisfied consumers are the assets for a growing business. The study investigates the factors that influence people's decisions when it comes to buying items online. It shows that the experiences they have while shopping online can affect their decisions. The following statistical tools were applied for this study: percentage analysis, mean score with rank correlation, and t-Test. The results reveal that the factors quality, cost, product variety, uniqueness, and safety payments were highlighted as important indicators of performance and that the companies that do online businesses had to take care of their main goal as per the proposal.

The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.

investors and managers are always faced with uncertainty in the information environment, which uncertainty can be due to factors such as the synchronization of stock returns, extraordinary fluctuations in stock returns and the number of equations. The purpose of this study is to investigate the political uncertainty caused by the size of the firm under the influence of risky information environment, the irregular behavior of accruals anomaly and the anomaly behavior of the cost of normal stock equity of companies. For this purpose, the data of 99 companies listed on the Tehran Stock Exchange and Iran TSETMC during the years 2009 to 2019 were examined and tested through combined data. The results showed that the political uncertainty caused by the firm size affected the concurrency stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. The results also showed that the political uncertainty caused by the firm size is affected by the extraordinary fluctuation of stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. In addition, the political uncertainty caused by the firm size is affected by the number of equations with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship.

Repetition in fiction is a very common device that many authors employ to bring forth motifs and themes into their works or as a means of creating emphasis. Therefore, it is quite expectable to observe many works with repeated sentences, phrases, and even words in various periods, which either are repetitions of a character’s own words or the repetitions of a character’s utterances by another character in the narrative in a small scale and the repetition of the whole work in larger scale. Through the use of Genettian repeating frequency type (nN/1S), authors are able to stress particular events, provide themes and motifs, and make use of prior narration, simultaneously. By means of scrutiny of repetitions in Mary Shelly’s Frankenstein; or, The Modern Prometheus, George Eliot’s The Mill on the Floss, and Charles Dickens’ Hard Times as three canonical works of British literature through Genettian nN/1S frequency type, this study could elaborate on the crucial emphatic role this frequency type plays in emergence of specific effects in these narratives.

Delving into the narration of Ian McEwan's Sweet Tooth (2012), this enquiry unravels the threads of conventional realistic narrative and avant-garde postmodernist one in the tapestry of the novel, arguing that through the miscibility of these two heterogeneous modes of narration McEwan constructs a narrative meta-design that innovatively adds an enigmatic dimension to the spy novel genre. In his dual narrative that depends on verisimilitude as well as self-conscious reflexivity, he once again, a decade after his Atonement (2002), demonstrates his literary taste for bridging the "past" and "present." Marinating his narrative in Cold War events, and adding a dash of what Linda Hutcheon calls "historiographic metafiction," he makes a postmodern signature dish that sustains its paradoxical hybridity: a representational self-reflexivity or an anti-representational reflexivity. Aligned with Monica Cojocaru's detection of a "metafictional twist" in the novel as a part of her comparative investigation, this study discusses that Sweet Tooth's dual narrative makes it eligible to wear the postmodern badge.