With the rapid development of China’s economy and society, the reform of talent training mode for business administration has become the most concerned and valued issue in the current teaching work in colleges and universities. From the current situation of undergraduate education curriculum system construction in vocational colleges, the traditional teaching methods of higher English still occupy the majority. The all English bilingual course for the undergraduate major of business administration takes the basic knowledge of language and the theory of natural science as the core content. Therefore, this paper will focus on how to build a perfect talent training mode for business administration majors that meets the actual needs and employment direction of students, and put forward specific teaching strategies in order to provide more application-oriented and professional development platforms for business administration students.

With the popularization of the Internet and the rapid development of computer network technology, human beings have entered a brand new era - the information age. This kind of network technology beyond space not only brings well-being to people, but also subtly affects the ideas and behaviors of teenagers. It not only changes their lifestyle and values, but also quietly makes them mentally ill, resulting in an endless series of problems of juvenile cybercrimes. For the purpose of promoting the governance of Internet crimes among young people effectively and avoiding crimes among special groups of young people, this paper plans to base on the concept of Internet crimes of teenagers, summarize the characteristics of youth crimes in our country, analyze its influence factors and propose the measures to deal with it.

This paper discusses the dawn of cognitive neuroscience in management and organizational research. The study does that in two tiers: first, it reviews the interdisciplinary field of organizational cognitive neuroscience, and second, it analyzes the role organizational cognitive neuroscience (OCN) could play in reducing counterproductive workplace behaviors (CWB). Theoretically, the literature has established the benefits of a neuro-scientific approach to understanding various organizational behaviors, but no research has been done on using organizational neuroscience techniques to study counterproductive work behaviors. This paper, however, has taken the first step towards this research avenue. The study will shed light on this interdisciplinary field of organizational cognitive neuroscience (OCN) and the benefits that organizations can reap from it with respect to understanding employee behavior. A research agenda for future studies is provided to scholars who are interested in advancing the investigation of cognition in counterproductive work behaviors, also by using neuroscience techniques. The study concludes by providing evidence drawn from the literature in favor of adopting an OCN approach in organizations.

Online transportation is a new type of service equipped with an internet network, and its presence in Indonesia is considered a service that disrupts the transportation sector. The government is faced with a complex policy problem to regulate online transportation. This article aims to reveal the role of policy actors in the media regarding policy issues and online transportation policy solutions. This article used qualitative analysis and the NPF policy narrative framework approach. This study found that licensing issues and Permenhub were problems that the DIY and Riau governments shared. More specific problems in Riau Province are related to violence issues, and that in DIY are related to congestion problems. The policy solution recommended by policy actors to the media is to make regional level regulations that technically regulate online transportation according to the area conditions.

This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.

The study focused on investigating the effects of varying levels of HA (HA₁ = 0, HA₂ = 25, HA₃ = 50, HA₄ = 75, and HA₅ = 100) on Red Dragon, Red Prince, and Red Meat varieties of red radish. This analysis aimed to unravel the relationship between different levels of HA and their impact on the growth and productivity of red radish genotypes. The findings revealed that the Red Prince genotype attained the utmost plant height of 24.00 cm, an average of 7.50 leaves per plant, a leaf area of 23.11 cm², a canopy cover of 26.76%, a leaf chlorophyll content of 54.60%, a leaf fresh weight of 41.16 g, a leaf dry weight of 8.20 g, a root length measuring 9.73 cm, a root diameter of 3.19 mm, a root fresh weight of 27.60 g, a root dry weight of 6.75 g, and a remarkable total yield of 17.93 tons per hectare. The implications of this study are poised to benefit farmers within the Dera Ismail Khan Region, specifically in the plain areas of Pakistan, by promoting the cultivation of the Red Prince variety.