Music 2025 : The Music Data Dilemma: issues facing the music industry in improving data management

© Crown Copyright 2019Music 2025ʼ investigates the infrastructure issues around the management of digital data in an increasingly stream driven industry. The findings are the culmination of over 50 interviews with high profile music industry representatives across the sector and reflects key issues as well as areas of consensus and contrasting views. The findings reveal whilst there are great examples of data initiatives across the value chain, there are opportunities to improve efficiency and interoperability

Investigate waste management issue in Mexico Restaurant

Reliable data on waste management and controlling waste will be illuminated in an effective way to suggest better waste management practices in the hospitality industry in New Zealand. This research suggests effective steps to regain and minimize the waste produced in Mexico restaurant, which is located in Victoria Street, Hamilton. To obtain the data, interviews and observation were the preliminary methods used in this research to clearly understand the main cause of the problem by the organisation in terms of waste. This research has covered waste management issues faced in SMEs and steps to control food waste in restaurants. All the collected data are compared and analysed under a statistical result and these results are discussed on the basis of the current waste management practices of the business. The key findings recommend a possible method to control waste and implementing new software to monitor the waste. Further research will carry over under the same stream by influencing engineering methods and machines, which will be a positive deliverable for a sustainable environment and society

Architecture independent environment for developing engineering software on MIMD computers

Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

A need for an integrative security model for semantic stream reasoning systems

State-of-the-art security frameworks have been extensively addressing security issues for web resources, agents and services in the Semantic Web. The provision of Stream Reasoning as a new area spanning Semantic Web and Data Stream Management Systems has eventually opened up new challenges. Namely, their decentralized nature, the metadata descriptions, the number of users, agents, and services, make securing Stream Reasoning systems difficult to handle. Thus, there is an inherent need of developing new security models which will handle security and automate security mechanisms to a more autonomous system that supports complex and dynamic relationships between data, clients and service providers. We plan to validate our approach on a typical application of stream data, on Wireless Sensor Networks (WSNs). In particular, WSNs for water quality monitoring will serve as a case study. The paper describes the initial findings and research plan for building a consistent security model for stream reasoning systems

A need for an integrative security model for semantic stream reasoning systems

State-of-the-art security frameworks have been extensively addressing security issues for web resources, agents and services in the Semantic Web. The provision of Stream Reasoning as a new area spanning Semantic Web and Data Stream Management Systems has eventually opened up new challenges. Namely, their decentralized nature, the metadata descriptions, the number of users, agents, and services, make securing Stream Reasoning systems difficult to handle. Thus, there is an inherent need of developing new security models which will handle security and automate security mechanisms to a more autonomous system that supports complex and dynamic relationships between data, clients and service providers. We plan to validate our approach on a typical application of stream data, on Wireless Sensor Networks (WSNs). In particular, WSNs for water quality monitoring will serve as a case study. The paper describes the initial findings and research plan for building a consistent security model for stream reasoning systems

New Zealand freshwater management and agricultural impacts

In New Zealand, it is increasingly recognised, including by government, that water resource allocation and water quality are issues of national importance. Agriculture is frequently portrayed by public media as a major user of water and a major contributor to worsening water quality. We outline the water management systems in New Zealand, and the use of water by agriculture. Official reports on agriculture’s impact on New Zealand water availability and quality are summarised. We report how the New Zealand public perceive water, its management, and the roles of agriculture in water issues. Data from a nationwide mail survey were analysed to determine how New Zealanders assess the state of New Zealand lakes, rivers and streams, and aquifers, the performance of three agencies responsible for management of freshwater resources, and willingness to fund stream enhancement. We provide brief explanations for the failures of water resource management in New Zealand and report on options, including community-based responses that might address some of the mounting public, scientific, and government concerns about trends in water quantity and quality. A willingness to pay proposition, concerning riparian areas, included in the nationwide survey provides some evidence that the public are willing to pay for improved waterway management. Relevant non-market valuation studies also indicate that the public places considerable value on preservation values of water in New Zealand.agriculture, environmental economics, perceptions survey, water allocation, water quality, Resource /Energy Economics and Policy,

Big Data Management Challenges, Approaches, Tools and their limitations

International audienceBig Data is the buzzword everyone talks about. Independently of the application domain, today there is a consensus about the V's characterizing Big Data: Volume, Variety, and Velocity. By focusing on Data Management issues and past experiences in the area of databases systems, this chapter examines the main challenges involved in the three V's of Big Data. Then it reviews the main characteristics of existing solutions for addressing each of the V's (e.g., NoSQL, parallel RDBMS, stream data management systems and complex event processing systems). Finally, it provides a classification of different functions offered by NewSQL systems and discusses their benefits and limitations for processing Big Data