Effect of Financial Clusters on Startup Mergers and Acquisitions

The conventional wisdom has maintained that being in proximity to entrepreneurial ecosystems helps startups to raise financing, develop and grow. In this paper, we examine the effect of a major component of an entrepreneurial ecosystem-financial or venture capital clusters on the exit of a startup through mergers and acquisitions (M&A). We find that probability of successful exit through M&A increases if the venture capitalist invested in the startup is in a venture capital (VC) cluster. Location of the startup in a top VC cluster is not significant for success once we control for the location of the VC in a top VC cluster.Our results are robust to different specifications of the models that use different time periods, reputation of VC, industry, and the quality of the startup company. Our results provide evidence for VCs, startups and policy makers who want to better understand the components of entrepreneurial ecosystems and their relation to the M&A exits of startups.

Analysis of Relationship between Electroencephalograms and Subjective Measurements for In-Vehicle Information System: A Preliminary Study

In this study, we explored the relationship between objective and subjective measures for usability evaluation in in-vehicle infotainment systems (IVISs). As a case study, four displays were evaluated based on cluster location and display orientation (that is, front–horizontal, front–vertical, right–horizontal, and right–vertical). Thirty-six participants performed tasks to manipulate the functions of the IVISs and data were collected through an electroencephalogram (EEG) sensor and questionnaire items. We analysed a model that estimated EEG-based objective indicators from subjective indicators. As a result, the objective indicators reflected the subjective indicators and were considered to explain the driver’s cognitive state. Although EEG data were collected from only four participants, this study proposed an experimental design that could be applied to the analysis of the relationship between the subject’s evaluation and EEG signals, as a preliminary study. We expect the experimental design and results of this study to be useful in analysing objective and subjective measures of usability evaluation.

Estimating and evaluating the rice cluster distribution uniformity with UAV-based images

The uniformity of the rice cluster distribution in the field affects population quality and the precise management of pesticides and fertilizers. However, there is no appropriate technical system for estimating and evaluating the uniformity at present. For that reason, a method based on unmanned aerial vehicle (UAV images) is proposed to estimate and evaluate the uniformity in this present study. This method includes rice cluster recognition and location determination based on the RGB color characteristics of the seedlings of aerial images, region segmentation considering the rice clusters based on Voronoi Diagram, and uniformity index definition for evaluating the rice cluster distribution based on the variation coefficient. The results indicate the rice cluster recognition attains a high precision, with the precision, accuracy, recall, and F1-score of rice cluster recognition reaching > 95%, 97%, 97%, 95%, and 96%, respectively. The rice cluster location error is small and obeys the gamma (3.00, 0.54) distribution (mean error, 1.62 cm). The uniformity index is reasonable for evaluating the rice cluster distribution verified via simulation. As a whole process, the estimating method is sufficiently high accuracy with relative error less than 0.01% over the manual labeling method. Therefore, this method based on UAV images is feasible, convenient, technologically advanced, inexpensive, and highly precision for the estimation and evaluation of the rice cluster distribution uniformity. However, the evaluation application indicates that there is much room for improvement in terms of the uniformity of mechanized paddy field transplanting in South China.

Foreign high-end retailers in Canada, where next?

Foreign high-end retailers have started to establish their brands in Canada. There are several locations across Canada that contain a significant number of them. Using these existing established high-end retail locations, this paper presents potential new locations for these high-end retailers to expand into. The paper deals with six of the major census metropolitan areas (CMA) in Canada: Toronto, Montreal, Vancouver, Calgary, Edmonton, and Ottawa. The demographic and household spending data at the census tract level were used to represent potential customers. Trade areas were created for each of the existing established high-end retail locations using 15-min and 20-min drive times. K-means cluster analysis was used to determine the results. Using a combination of the trade area demographics and the target cluster location, this paper has confirmed that there are potential locations, apart from existing clusters of high-end retailers, for foreign high-end retailers to expand into.

Foreign high-end retailers in Canada, where next?

Foreign high-end retailers have started to establish their brands in Canada. There are several locations across Canada that contain a significant number of them. Using these existing established high-end retail locations, this paper presents potential new locations for these high-end retailers to expand into. The paper deals with six of the major census metropolitan areas (CMA) in Canada: Toronto, Montreal, Vancouver, Calgary, Edmonton, and Ottawa. The demographic and household spending data at the census tract level were used to represent potential customers. Trade areas were created for each of the existing established high-end retail locations using 15-min and 20-min drive times. K-means cluster analysis was used to determine the results. Using a combination of the trade area demographics and the target cluster location, this paper has confirmed that there are potential locations, apart from existing clusters of high-end retailers, for foreign high-end retailers to expand into.

A High Density WSN Cluster Positioning Approach

Node self-positioning is one of the supporting technologies for wireless sensor network applications. In this paper, a clustering localization algorithm is proposed for large-scale high-density wireless sensor networks. Firstly, the potential of the node is defined as the basis for the election of the cluster head. The distance between the nodes in the network is calculated indirectly by the relationship between the received signal strength and the communication radius. The topology information in each cluster is saved by the cluster head, and the linear programming method is used in the cluster head to implement the cluster internal relative positioning. Then, from the sink node, the inter-cluster location fusion is gradually implemented, and finally the absolute positioning of the whole network is realized. Compared with the centralized convex programming algorithm, the proposed algorithm has low computational complexity, small traffic, high positioning accuracy, and does not need to know the signal attenuation factor in the environment in advance, and there is anti-noise ability.

Geodynamics, diamondiferous system tectonics and minerageny

The paper presents a unique geodynamic evolution concept of all processes and structures ensuring carbon source formation and movement for diamond crystals growth in the mantle, and diamondiferous medium supply to the surface. Geodynamic basis for diamond formation is exogenetic source sinking in old subduction zones evolving along convection cell edges. The supply is ongoing in an advection system, with transtension combined with convection playing a key role. The paper shows periods of spatial pipe cluster location and tectonophysical pattern of this phenomenon. Based on geodynamics, the authors suggest improving a taxonomical scheme of the diamondiferous system due to its fractal structure, from a mineragenic province to a pipe cluster. Specific examples are presented to highlight major structural elements of diamondiferous taxons (systems) and their formation patterns. Debatable issues of kimberlite nature are discussed.

Occupational Competitiveness Analysis of the U.S. Transportation and Logistics Cluster

This paper explores occupational or human capital attributes of transportation and logistics clusters in the U.S., by analyzing logistics clusters, such as Memphis and uncovers the differences in occupations or knowledge and skill contents of the workforce. The research builds on previous studies funded by the U.S. Economic Development Administration on U.S. occupation clusters providing insights on logistics clusters from a human capital perspective. The study draws specifically from the industry-and-occupation cluster crosswalks building on previous research on occupation cluster industry cluster-location quotient (OCIC-LQ), and recent research on computerization and automation of occupations. The research questions include how knowledge occupation clusters differ in specialization within the select logistics clusters. How can occupation clusters inform the traditional cluster-based economic development policies in the U.S.? How might automation impact the logistics cluster? The findings show that transportation and logistics clusters are unique in knowledge-based occupations with some commonalities found in different locations. Based on occupational and staffing patterns, nearly 71% of occupations or tasks and activities within the transportation and logistics cluster in Memphis is at risk of automation. The research builds a case for place-based cluster development and people-based workforce development for transportation and logistics cluster in the U.S.

Identification of Leading Sector and Cluster Analysis of Regencies in Kalimantan

To achieve the purpose of regional economic development, there is a need for development policy that is based on the characteristics of the region. Kalimantan is the centre of development in Eastern Indonesia which has strategic position for cooperation region. This study aimed to identify the potential leading sectors to develop and determine the regencies grouping and the characteristics of each group based on welfare indicators. The secondary data were collected from socio-economic data of 56 regencies during 2010-2016. This study used descriptive quantitative method and several analysis theories namely Klassen’s Typology, factor and cluster, Location Quotient, Shift Share, and Overlay analysis. The results of study showed that: (1) the economic structure of Kalimantan had shifted because a change of economic contribution from agriculture to industrial sector; (2) the mining and quarrying, water supply, waste management and recycling sector were the leading sectors in Kalimantan; (3) Kalimantan was classified into four clusters based on 13 economic social indicators: agricultural, urban, disadvantaged, and wealth cluster; (4) the priority of development in each cluster were economic, social, and educational issues.

3-D attenuation tomography from microseismicity in a mine

SUMMARY We perform 3-D attenuation tomography using microseismic data recorded during an underground mine development. The whole path attenuation parameter t* is obtained by least-squares inversion of P-wave amplitude spectra of the events recorded by 7 monitoring wells each containing 4 3C geophones. The corner frequencies obtained during P-wave spectral inversion of the 488 identified events range from 140 to 220 Hz which are typical for microseismic events with a negative moment magnitude of around –1. The quality factor Q obtained from tomographic inversion varies between 9 and 72 with the event cluster location characterized by a low Q value of 10. Two high Q regions of 30–72 are located at depths of 0.45 and 0.5 km, one between 0–0.15 km east and 0.3–0.5 km north which correlate with the high-grade ore deposit, and another centred around 0.45 km east and 0.25 km north. The high (-low) Q values, in general, correlates with the high (-low) velocities present in the velocity tomography model. A joint interpretation of seismic attenuation and velocity models reveals the heterogeneity present in the mine which aids in delineating the ore body using seismic waves in addition to other measurements such as gravity inversion and direct sampling from drillholes.