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The work presented in this paper is concerned with mathematical modeling and experimental validation of mono-tube shock absorber. This paper aims to create damper model to predict accurately damping force, and experimental analysis is done by varying the various parameters, such as flow area in bleed(Ab), mass (M) and operating frequency(?).

Here, input is given in the form of sinusoidal excitation, and the output is received as a numerical data of the displacement transmissibility. These data are then processed to get the values of transmissibility and magnification factor for various frequency ratios. They are then plotted to have transmissibility and frequency response curves, as it is a generally accepted measure of how well the system is isolated from its surroundings.

It is better to have low transmissibility (larger bleed area), for lower suspension velocity, as it will reduce maximum acceleration transmitted to the sprung mass. However, for higher suspension velocity, bleed area should be low (higher transmissibility) to reduce displacement of tyre from road.

The development of faster vehicles and also the requirements of smoother and more comfortable rides have led to the fitment of dampers on almost on all present day vehicles. Shock absorbers have a significant influence on handling performance and riding comfort. Shock absorber plays an important role not only for comfort of the riders of the vehicle but also in the performance and life of the vehicle. However, no further reduction of vehicle vibration can be expected for using the optimum values of damping coefficient and spring stiffness for the shock absorber. Thus, it is necessary to make modification to improve the functions of shock absorber.

In a virtual interconnected digital space, the metaverse encompasses various virtual environments where people can interact, including engaging in business activities. Machine learning (ML) is a strategic technology that enables digital transformation to the metaverse, and it is becoming a more prevalent driver of business performance and reporting on performance. However, ML has limitations, and using the technology in business processes, such as accounting, poses a technology governance failure risk. To address this risk, decision makers and those tasked to govern these technologies must understand where the technology fits into the business process and consider its limitations to enable a governed transition to the metaverse. Using selected accounting processes, this study aims to describe the limitations that ML techniques pose to ensure the quality of financial information.

A grounded theory literature review method, consisting of five iterative stages, was used to identify the accounting tasks that ML could perform in the respective accounting processes, describe the ML techniques that could be applied to each accounting task and identify the limitations associated with the individual techniques.

This study finds that limitations such as data availability and training time may impact the quality of the financial information and that ML techniques and their limitations must be clearly understood when developing and implementing technology governance measures.

The study contributes to the growing literature on enterprise information and technology management and governance. In this study, the authors integrated current ML knowledge into an accounting context. As accounting is a pervasive aspect of business, the insights from this study will benefit decision makers and those tasked to govern these technologies to understand how some processes are more likely to be affected by certain limitations and how this may impact the accounting objectives. It will also benefit those users hoping to exploit the advantages of ML in their accounting processes while understanding the specific technology limitations on an accounting task level.

The purpose of this paper is to provide a cost-effective foundation technique for the design of foundations of transmission towers, heavily loaded structures, etc.

Experimental model tests are conducted in a model test tank to find out the effect of length and diameter of geogrid encased granular pile anchors, the relative density of sand and the angle of inclination of the pile from the vertical on uplift behavior of granular pile anchors.

The uplift capacity of the geogrid encased granular pile anchor increased with increasing length and diameter of granular pile anchor. Further, increasing the relative density of surrounding soil increased uplift capacity of geogrid encased granular pile anchor system. Moreover, increasing the angle of inclination of loading also increased uplift capacity of whole system. Thus, the proposed system can be effectively used in field for further applications.

The paper is helpful for the engineers looking for cost-effective foundation techniques for heavily loaded structures.

The Olympic Gold Quest (OGQ) was founded as a Non-profit to support Indian athletes in their quest to win Olympic Gold medals by bridging the gap between the best athletes in India and in the world. The support from OGQ has been instrumental to India in winning its highest number of medals at any summer Olympics. Buoyed by this success, OGQ has set up a target of achieving eight Olympic medals at the 2016 Rio Olympic Games. With OGQ relying on donations to support the athletes, the challenge is to market the Olympic cause by creating, communicating, and delivering the right offering for its donors.