Joint data rate and power allocation for lifetime maximization in interference limited ad hoc networks

In this paper, we consider the following problem in the wireless ad hoc network: Given a set of paths between source and destination, how to divide the data flow among the paths and how to control the transmission rates, times, and powers of the individual links in order to maximize the operation time of the worst network node. If all nodes are of equal importance, the operation time of the worst node is also the lifetime of the network. By solving the problem, our aim is to investigate how the network lifetime is affected by link conditions such as the maximum transmission power of a node and the peak data rate of a link. For the purpose, we start from a system model that incorporates the carrier to interference ratio (CIR) into a variable data rate of a link. With this, we can develop an iterative algorithm for the lifetime maximization, which resembles to the distributed power control in cellular systems. Numerical examples on the iterative algorithm are included to illustrate the network lifetime as a function of the maximum transmission power and the peak data rate.     

An alternate quantum adiabatic evolution for the Deutsch–Jozsa problem

Deutsch–Jozsa algorithm has been implemented via quantum adiabatic evolutions by Das et al. (Phys Rev A 65:062310, 2002) and Wei et al. (Phys Lett A 354:271, 2006). In the latter literature, the authors have shown a modified version of the adiabatic evolution which can improve the performance of the algorithm of S. Das et al’s to constant time. In this paper, we also improve the algorithm of S. Das et al’s in a constant time but by using a different construction of adiabatic evolution, i.e., adding ancillary qubits. The algorithm in this paper provides an alternative option to potential users.     

Optimality of partial adiabatic search and its circuit model

In this paper, we first uncover a fact that a partial adiabatic quantum search with \(O(\sqrt{N/M})\) time complexity is in fact optimal, in which \(N\) is the total number of elements in an unstructured database, and \(M\) ( \(M\ge 1\) ) of them are the marked ones(one) \((N\gg M)\) . We then discuss how to implement a partial adiabatic search algorithm on the quantum circuit model. From the implementing procedure on the circuit model, we can find out that the approximating steps needed are always in the same order of the time complexity of the adiabatic algorithm.     

Research on the group decision-making about emergency event based on network technology

In order to improve decision-making efficiency about emergency event, this paper proposes a novel concept, i.e., Agile-Delphi Method, which is an integration of agile decision and Delphi Method implicating that the decision-makers instantly deliver, respond, treat, and utilize information via Delphi process while conducting group decision-making about emergency event. The paper details the mechanism of group decision-making about emergency event based on network technology and Agile-Delphi Method. Finally, the paper conducts an empiric analysis taking the “111 event”, i.e., the liquid ammonia spill event happened on November 1, 2006 in a phosphorus chemical company in China, as an example.     

Extract conceptual graphs from plain texts in patent claims

This paper develops techniques to extract conceptual graphs from a patent claim using syntactic information (POS, and dependency tree) and semantic information (background ontology). Due to plenteous technical domain terms and lengthy sentences prevailing in patent claims, it is difficult to apply a NLP Parser directly to parse the plain texts in the patent claim. This paper combines techniques such as finite state machines, Part-Of-Speech tags, conceptual graphs, domain ontology and dependency tree to convert a patent claim into a formally defined conceptual graph. The method of a finite state machine splits a lengthy patent claim sentence into a set of shortened sub-sentences so that the NLP Parser can parse them one by one effectively. The Part-Of-Speech and dependency tree of a patent claim are used to build the conceptual graph based on the pre-established domain ontology. The result shows that 99% sub-sentences split from 1700 patent claims can be efficiently parsed by the NLP Parser. There are two types of nodes in a conceptual graph, the concept and the relation nodes. Each concept or relation can be extracted directly from a patent claim and each relation can link with a fixed number of concepts in a conceptual graph. From 100 patent claims, the average precision and recall of a concept class mapping from the patent claim to domain ontology are 96% and 89%, respectively, and the average precision and recall for Real relation class mapping are 97% and 98%, respectively. For the concept linking of a relation, the average precision is 79%. Based on the extracted conceptual graphs from patents, it would facilitate automated comparison and summarization among patents for judgment of patent infringement.     

Joint Learning in Innovative R&D Collaboration

The present study analyzes the mechanisms and facilitators behind joint learning in R&D collaborations by way of a qualitative comparative case study analyzing three supplier relationships and three internal R&D partnerships of the focal organization. The results suggest a single joint learning process for internal and external relationships in which the role of the customer and the facilitation of the joint learning process vary depending on the context. Whereas the role of motivation is central for joint learning in the internal relationships, mutual trust is important to the external relationships.     

A network approach to overcoming barriers to market engagement for SMEs in energy efficiency initiatives such as the Green Deal

The Green Deal (GD) was launched in 2013 by the UK Government as a market-led scheme to encourage uptake of energy efficiency measures in the UK and create green sector jobs. The scheme closed in July 2015 after 30 months due to government concerns over low uptake and industry standards but additional factors potentially contributed to its failure such as poor scheme design and lack of understanding of the customer and supply chain journey. We explore the role of key delivery agents of GD services, specifically SMEs, and we use the LoCal-Net project as a case study to examine the use of networks to identify and reduce barriers to SME market engagement. We find that SMEs experienced multiple barriers to interaction with the GD such as lack of access to information, training, and confusion over delivery of the scheme but benefited from interaction with the network to access information, improve understanding of the scheme, increasing networking opportunities and forming new business models and partnerships to reduce risk. The importance of SMEs as delivery agents and their role in the design of market-led schemes such as the GD are discussed with recommendations for improving SME engagement in green sector initiatives.     

A Comparision of the Number of Rational Places of Certain Function Fields to the Hasse-Weil Bounds

We give explicitly the number of rational places of certain function fields in terms of the reciprocals of the zeros of the function fields in question. The results are then compared with the Hasse-Weil bounds by using the approximation theorems of Dirichlet and Kronecker and it turns out that in many of these function fields the number of rational places is near the upper Hasse-Weil bound. Keywords:Function fields, Diophantine approximation, Exponential sums.     

Digital innovations-driven business model regeneration: A process model

The traditional ways of doing business have changed dramatically with the emergence of new digital technologies. Firms can stay competitive using the benefits of digital technologies, such as the Internet of Things, social computing, Cloud computing, cyber-physical systems, big data and analytics, wireless networks, artificial intelligence, robotics, simulation, etc. The spread of the coronavirus disease in 2019 (COVID-19) all over the world has created a better understanding of the importance of organizations’ ability to keep up with digital innovations. Therefore, the regeneration of business models is becoming an increasingly crucial factor for survival in the digital age. This study develops a process model for digital innovations-driven business model regeneration based on the design science research approach. For this purpose, the existing models and cases in the business model innovation (BMI) literature are examined and the empirical data are collected using semi-structured interviews to complement and validate this knowledge. The collected data are then analyzed and a digital innovations-driven business model regeneration method is developed. The proposed model is demonstrated with a real case. This study extends the BMI literature. The proposed process model can be used by strategic managers to analyze the impacts of potential digital innovations on their current business models and regenerate their business model. Therefore, it can help companies to be able to gain a competitive advantage over their competitors or sustain their business against technological developments.     

Improvement of fuel economy of an indirect injection (IDI) diesel engine with two-stage injection

This paper focuses on the effects of early stage injection and two-stage injection on the combustion characteristics and engine performances of an indirect injection (IDI) diesel engine. In a direct injection (DI) diesel engine, HC emission increases with early stage injection because some of the fuel spray adheres to the cylinder wall and burns in the gap between the piston and the cylinder. On the other hand, since the fuel spray of early stage injection in an IDI diesel engine is injected into an auxiliary combustion chamber such as a swirl chamber, the IDI diesel engine could reduced the HC emission produced from the gap compared with a DI diesel engine. In a two-stage injection IDI diesel engine, NO and smoke emissions are improved when the amount of fuel in the first stage injection is small and the first stage injection timing is advanced over −80° TDC. And 20% improvement in fuel consumption is achieved when the first stage injection timing is advanced over −80° TDC. Conversely, HC and CO emissions of two-stage injection increases compared with that of conventional injection of an IDI diesel engine. However, CO emission can be improved a little when the first stage injection timing is advanced over −100° TDC and the second stage injection timing is retarded over TDC.