scispace - formally typeset
Search or ask a question

When are the NBA Live 19 servers shutting down? 

Answers from top 7 papers

More filters
Papers (7)Insight
The results show that the continuous operation of the series-stacked servers can be maintained, while one of the servers is hot-swapped.
The results from a real-life NBA database highlight and reveal several expected and unexpected aspects of the database.
Because many NBA arenas are subsidized, the effect has public policy implications if revenue projections for a new arena ignore or overestimate the effect.
Open accessBook ChapterDOI
Pieter J. L. Cuijpers, Reinder J. Bril 
03 Oct 2007
12 Citations
We prove a scheduling theorem for deferrable servers, and as a corollary show that an earlier claim of Davis and Burns, that periodic servers dominate deferrable servers with respect to schedulability, no longer holds when the context of the comparison is slightly generalized.
Using 1990-2008 NBA data, the authors fail to find any evidence of either pay or exit discrimination in the NBA utilizing this new technique.
Complex network-based models present good results when compared to box score statistics, which underscore the importance of capturing network relationships in a community such as the NBA.
Using data on Nielsen ratings for locally televised NBA basketball games, we find strong evidence that viewership increases when there is greater participation by white players.

See what other people are reading

Can transfer learning be used to improve the efficiency and effectiveness of edge computing for face recognition?
9 answers
Transfer learning has emerged as a pivotal technique in enhancing the efficiency and effectiveness of edge computing for face recognition tasks. By leveraging pre-trained models and adapting them to new, but related tasks, transfer learning can significantly reduce the computational resources required, which is crucial for edge devices with limited processing capabilities. The EdgeFace network, inspired by the hybrid architecture of EdgeNeXt, demonstrates how combining CNN and Transformer models with a low-rank linear layer can achieve high face recognition accuracy optimized for edge devices, showcasing the potential of sophisticated model architectures in edge computing scenarios. Moreover, the practice of face recognition, which is widely applied in various sectors, benefits from deep learning advancements, particularly CNNs. The use of pre-trained CNN models like VGG16, ResNet-50, and MobileNet through transfer learning has shown promising results in face recognition, indicating the effectiveness of leveraging deep learning in edge computing environments. Additionally, the proposal of a face recognition-based video retrieval system for edge computing environments further underscores the practical applications of these technologies in real-world scenarios. The efficiency of transfer learning is highlighted by the ETL technique, which retains only cross-task aware filters from a pre-trained model, resulting in a sparse transferred model. This approach not only reduces the size and inference time of the model but also retains high accuracy, demonstrating the potential for lightweight yet effective face recognition models on edge devices. Similarly, incorporating transfer learning into vehicular edge networks has shown to improve the agility of environment construction for computation-intensive tasks, further validating the approach's utility in edge computing. Facial Expression Recognition (FER) systems also benefit from transfer learning, with the EfficientNet architecture achieving high accuracy on small datasets, showcasing the technique's power in enhancing model performance with limited data. Lastly, the application of transfer learning in a Siamese network for face recognition further illustrates its versatility and effectiveness in improving recognition rates, even in challenging conditions. In conclusion, transfer learning significantly enhances the efficiency and effectiveness of edge computing for face recognition by enabling the use of advanced deep learning models on devices with limited computational resources, thereby facilitating real-time, accurate, and efficient face recognition applications.
What is the importance of management support in IT integration post M?
4 answers
Management support plays a crucial role in IT integration post M&A activities. The success of post-merger information systems integration heavily relies on effective decision-making processes and management backing. Additionally, the provision of appropriate information systems and technologies is vital for the effectiveness and sustainability of standardized corporate management systems. Furthermore, monitoring and management support are essential for maintaining enterprise integration, especially in scenarios where different applications and services are involved, requiring comprehensive monitoring mechanisms. Moreover, a management support method involving the operation of reference servers and applications is highlighted as a key element in ensuring continuous operation and decision-making in IT management. Overall, top management team support is identified as a critical factor for the success of management control systems innovations, emphasizing the importance of TMT belief and participation in MCS innovations.
Security measures on mobile health application that will aggregate user data to provide fitness insights?
9 answers
To ensure the security of mobile health applications that aggregate user data to provide fitness insights, a multifaceted approach is necessary. Firstly, employing robust encryption algorithms like the Advanced Encryption Standard (AES) is crucial for protecting user data from unauthorized access and manipulation, as highlighted in the context of fitness mobile applications. Additionally, implementing comprehensive security and privacy criteria, including authentication, authorization, access management, data storage, integrity, encryption, and privacy policies, can guide developers in creating secure applications. The use of mobile security frameworks such as MobSF and MARA, which assess security levels based on established classifications and provide safety metrics, is essential for identifying vulnerabilities and enhancing the security posture of mobile health applications. Moreover, considering user-centric design principles can significantly improve the privacy and security aspects of these applications by addressing specific vulnerability issues and incorporating user feedback into the development process. Blockchain technology offers a promising solution for ensuring data confidentiality and secure access to electronic health records (EHRs) by leveraging distributed ledger technology for secure and authorized data sharing among stakeholders. Furthermore, a lightweight, sharable, and traceable secure mobile health system can facilitate efficient keyword search and fine-grained access control of encrypted data, supporting secure data sharing and user revocation. Adopting privacy models such as the Privacy Policy Model (PPM) can address inherent threats to user privacy by providing a fine-grained and expandable permission model, ensuring the responsible use of collected data. Lastly, empirical investigations into end-user security awareness can inform the development of guidelines for creating secure and usable mobile health applications, emphasizing the importance of balancing security features with usability. In conclusion, securing mobile health applications that aggregate user data for fitness insights requires a comprehensive strategy that includes robust encryption, adherence to comprehensive security criteria, user-centric design, blockchain for data confidentiality, lightweight security systems for data sharing, privacy models to protect user data, and an understanding of end-user security awareness.
What are some efficient computational methods that can be used to address scalability challenges in AI algorithms?
5 answers
Efficient computational methods to address scalability challenges in AI algorithms include secure multiparty computation (SMC), quasi-homomorphic encryption, federated learning (FL), and Graph Equilibrium Models (GEQs). While SMC and FL focus on secure distributed processing and data privacy, GEQs tackle long-range dependency issues in graph neural networks. To enhance scalability, a method called VEQ has been proposed, which optimizes the equilibrium finding process by utilizing virtual equilibrium and mini-batch training. These methods aim to balance computational complexity, confidentiality, and performance in large-scale AI applications, offering solutions to the challenges posed by the increasing size and complexity of modern AI algorithms.
Do body shapes and proportions affect an athlete's success in competition?
5 answers
Body shapes and proportions significantly impact an athlete's success in competition. Athletes in combat sports like judo, jiu-jitsu, karate, taekwondo, and fencing exhibit distinct physical characteristics tailored to their disciplines, optimizing body type through training and athlete selection processes. Elite athletes, such as NBA players, show differences in body size proportions, with taller individuals having wider arm spans, influencing their athletic success. Moreover, a study on anterior cruciate ligament reconstruction (ACLR) in athletes revealed that body shape index (ABSI) is linked to postoperative knee function, with higher ABSI posing a risk for poor outcomes. These findings underscore the importance of considering body shapes and proportions in talent identification programs and training optimization for enhanced athletic performance.
How does a proactive and data-driven approach to quality control impact the overall efficiency of industrial systems?
5 answers
A proactive and data-driven approach to quality control significantly enhances the efficiency of industrial systems by leveraging real-time data, machine learning techniques, and predictive analytics. By utilizing Industry 4.0 technologies, such as edge computing and wireless networks, industrial control systems can optimize control performance through dynamic edge offloading, ensuring stability under fluctuating cyber-physical conditions. Additionally, the integration of quality management key performance indicator visualization systems enables the quantification of relationships between IoT data and product quality, leading to integrated quality control and improved product quality. These approaches not only enhance process reliability, reduce downtime, and increase performance but also provide a user-friendly and intuitive method for quality management in manufacturing industries.
What are the factors that make an athlete successful besides having good anthropometrical characteristics?
5 answers
Successful athletes rely on various factors beyond anthropometric characteristics. Research by Giuriato et al. highlighted that in middle school students, anthropometric measurements like BMI, mass, and VO2 peak showed low correlation with athletic performance in the Cooper Run Test. Similarly, Brunkhorst and Kielstein found that elite triathletes and cyclists did not exhibit specific anthropometric profiles predictive of success, emphasizing discipline and talent over physical traits. Masanovic et al. emphasized the importance of suitable anthropometric characteristics in basketball and volleyball players for optimal performance, indicating that technical skills and body composition are crucial alongside physical traits. Pant and Parsekar's study on cricketers revealed that national level players demonstrated superior anthropometric characteristics and physical fitness compared to state-level players, indicating the role of overall fitness in enhancing performance. Joksimović et al. demonstrated in football that morphological characteristics like body height and weight significantly differed between player positions, influencing success in the game.
What are the specific anthropometric characteristics that are most important for athletes to succeed in playing sports?
5 answers
Anthropometric characteristics play a crucial role in determining the success of athletes in various sports. Specific parameters such as body composition, body mass, skeletal mass, body surface area, and frontal area are key factors that differ based on the athlete's specialty or position within the sport. Additionally, differences in body height, weight, and BMI have been noted between different player positions in sports like football, emphasizing the importance of morphological characteristics in athletic performance. Furthermore, optimal morphology, strength, and endurance are essential for athletes to meet the functional requirements of their respective sports, highlighting the significance of anthropometric features in sports success. Monitoring and interpreting body composition data, including skinfold thickness and muscle circumferences, are vital for assessing performance and training in elite athletes across various sports.
How does digitalization impact the sustainability of news media in terms of social responsibility and ethical standards?
5 answers
Digitalization significantly impacts the sustainability of news media concerning social responsibility and ethical standards. The transition to digital platforms has led to challenges in engaging online readers effectively, with newspapers struggling to establish sustainable business models. As digital practices evolve, the concept of Digital Social Responsibility (DSR) emerges as a subset of Corporate Social Responsibility (CSR), emphasizing data privacy, algorithm unbiasedness, digital inclusion, and combating fake news. Latin American news publishers are adapting their business models to sustain quality journalism, exploring diverse revenue sources like philanthropic funding and multi-revenue stream models. The digital era introduces new tools for enhancing media accountability and transparency, emphasizing the importance of utilizing these tools to uphold ethical standards in journalism. Algorithmic systems pose ethical challenges for journalists, especially in local newsrooms, necessitating a distributed responsibility model to ensure accountability for ethical standards in the algorithmic era.
What are the potential benefits and challenges of digitalization for the social sustainability of news media?
5 answers
Digitalization offers both benefits and challenges for the social sustainability of news media. On one hand, digitalization can enhance access to information, potentially benefiting society and business by strategically addressing sustainable development challenges. However, newspapers are facing challenges in engaging online readers effectively, with issues such as low loyalty, depth, and stickiness among digital readers. Furthermore, the transition to digital platforms has led to a reluctance among readers to pay for digital content, impacting the financial sustainability of news organizations and eroding media independence. To ensure the social sustainability of news media in the digital age, it is crucial to address these challenges while leveraging the opportunities presented by digitalization.
Can bus privacy?
4 answers
Bus privacy is a critical concern in various contexts such as in-vehicle networks, public WiFi systems, and customized-bus sharing services. In the realm of in-vehicle networks, the lack of authentication and encryption in Controller Area Network (CAN) buses poses a risk of compromise by untrusted agents. Similarly, public WiFi spots on buses raise privacy concerns due to open access, with studies showing high probabilities of users being uniquely re-identified from leaked information. Moreover, in customized-bus sharing services, ride clustering for optimal bus routes can inadvertently expose users' locations and travel patterns, necessitating privacy-preserving schemes like fog computing and cryptographic techniques to safeguard user data without compromising clustering quality. These diverse scenarios highlight the importance of addressing bus privacy to ensure data security and user confidentiality in various transportation settings.