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To summarize the technical guidelines for complying with the final crowdfunding rules issued by the US Securities and Exchange Commission (“SEC”) after more than three years of consideration pursuant to the Jumpstart Our Business Startups Act (“JOBS Act”) to permit companies to offer and sell securities through crowdfunding.

Gives an overview of the JOBS Act and the proposed and final crowdfunding rules issued by the SEC; explains how start-ups and other companies can qualify under the final rules; summarizes the disclosure requirements for the issuers; explains the final rules regarding intermediary platforms; and summarizes the proposed rules to facilitate intrastate and regional securities offerings.

While new crowdfunding rules will enable start-up companies to raise money through the Internet in ways that were previously prohibited, the success of these rules in helping start-ups to raise capital easily and efficiently is still to be seen, as there are still significant restrictions and procedural hurdles for a would-be crowdfunding issuer, which makes crowdfunding costly, especially compared to other forms of capital raising.

Provides an overview and summary of the rules from experienced securities lawyers so that start-up companies and investors would be able to comply with the new rules.

This paper aims to propose a one-layer Mamdani hierarchical fuzzy system (HFS) to navigate autonomously an omnidirectional mobile robot to a target with a desired angle in unstructured environment. To avoid collision with unknown obstacles, Mamdani limpid hierarchical fuzzy systems (LHFS) are developed based on infrared sensors information and providing the appropriate linear speed controls.

The one-layer Mamdani HFS scheme consists of three fuzzy logic units corresponding to each degree of freedom of the holonomic mobile robot. This structure makes it possible to navigate with an optimized number of rules. Mamdani LHFS for obstacle avoidance consists of a number of fuzzy logic units of low dimension connected in a hierarchical structure. Hence, Mamdani LHFS has the advantage of optimizing the number of fuzzy rules compared to a standard fuzzy controller. Based on sensors information inputs of the Mamdani LHFS, appropriate linear speed controls are generated to avoid collision with static obstacles.

Simulation results are performed with MATLAB software in interaction with the environment test tool “Robotino Sim.” Experiments have been done on an omnidirectional mobile robot “Robotino.” Simulation results show that the proposed approaches lead to satisfied performances in navigation between static obstacles to reach the target with a desired angle and have the advantage that the total number of fuzzy rules is greatly reduced. Experimental results prove the efficiency and the validity of the proposed approaches for the navigation problem and obstacle avoidance collisions.

By comparing simulation results of the proposed Mamdani HFS to another navigational controller, it was found that it provides better results in terms of path length in the same environment. Moreover, it has the advantage that the number of fuzzy rules is greatly reduced compared to a standard Mamdani fuzzy controller. The use of Mamdani LHFS in obstacle avoidance greatly reduces the number of involved fuzzy rules and overcomes the complexity of high dimensionality of the infrared sensors data information.

During 2003, compensation practices for the retail sale of mutual funds came under fire. Recent revelations about failures in the processing of mutual fund breakpoints had triggered a more in‐depth investigation into mutual fund marketing and compensation practice by securities regulators, Congress, and the states. This article focuses on the regulation of sales compensation practices primarily as it affects a broker‐dealer selling mutual funds in the retail market. It addresses the regulatory framework for three key compensation practices: (1) the use of non‐cash compensation in connection with mutual fund sales; (2) marketing and compensation arrangements providing enhanced compensation to a selling firm as well as to its sales representatives for the promotion of certain fund securities over others, such as proprietary funds over non‐proprietary funds, preferred funds over non‐preferred funds, and Class B shares over Class A shares; and (3) the use of commissions for mutual fund portfolio trades as an additional source of selling compensation for selling firms, a practice sometimes referred to as ”directed brokerage.“

The purpose of this paper is to identify quality issues with using historical work order (WO) data from computerised maintenance management systems for reliability analysis; and develop an efficient and transparent process to correct these data quality issues to ensure data is fit for purpose in a timely manner.

This paper develops a rule-based approach to data cleansing and demonstrates the process on data for heavy mobile equipment from a number of organisations.

Although historical WO records frequently contain missing or incorrect functional location, failure mode, maintenance action and WO status fields the authors demonstrate it is possible to make these records fit for purpose by using data in the freeform text fields; an understanding of the maintenance tactics and practices at the operation; and knowledge of where the asset is in its life cycle. The authors demonstrate that it is possible to have a repeatable and transparent process to deal with the data cleaning activities.

How engineers deal with raw maintenance data and the decisions they make in order to produce a data set for reliability analysis is seldom discussed in detail. Assumptions and actions are often left undocumented. This paper describes typical data cleaning decisions we all have to make as a routine part of the analysis and presents a process to support the data cleaning decisions in a repeatable and transparent fashion.