On simultaneous diagonalization via congruence of real symmetric matrices

Simultaneous diagonalization via congruence (SDC) for more than two symmetric matrices has been a long standing problem. So far, the best attempt either relies on the existence of a semidefinite matrix pencil or casts on the complex field. The problem now is resolved without any assumption. We first propose necessary and sufficient conditions for SDC in case that at least one of the matrices is nonsingular. Otherwise, we show that the singular matrices can be decomposed into diagonal blocks such that the SDC of given matrices becomes equivalently the SDC of the sub-matrices. Most importantly, the sub-matrices now contain at least one nonsingular matrix. Applications to simplify some difficult optimization problems with the presence of SDC are mentioned

A novel autonomous wireless sensor node for IoT applications

A novel wireless sensor network node (WSNN) is presented in this paper where the solar energy harvester system is used as an autonomous power solution for endless battery lifetime. In this sensor node, the meander-line Inverted-F-Antenna (MIFA) is proposed and integrated in a single -CC2650 chip of Texas Instrument. The simple structure, low cost, compact size, high efficiency and low power consumption are advantages of this single-chip WSNN. The experimental results show that MIFA antenna is promising solution to enhance communication performance in WSN. In addition, the investigated single-chip WSNN with multi-wireless technologies including Bluetooth Low Energy and Zigbee as well as 6LowPAN is an attractive device for internet of thing (IoT) applications

Combining system dynamics and agent-based models to study transmission of healthcare-associated infections in long-term care facilities

Transmission of healthcare-associated infections (HAIs) in long-term care facilities (LTCFs) possesses many distinct characteristics that are not well understood. While HAIs are primarily disseminated via contacts between healthcare workers and patients in hospitals, patient-patient and patient-visitor contacts play an important role in spreading HAIs in LTCFs. The increased risk of transmission through these routes results from frequent aggregation of residents in common areas and family visitation. Additionally, the elderly population living in LTCFs who are frequently readmitted to a hospital might acquire colonization or infection of resistant organisms while being hospitalised and transmit these organisms to other residents when returning to the LTCF and vice versa. Systems simulation modelling methods including system dynamics (SD), discreteevent simulation and agent-based models (ABM) have long been used to study the problems of HAIs in hospitals. However, the existing models do not capture the impacts of patient-patient and patient-visitor contacts and frequent hospital readmission of residents upon transmission of HAIs in LTCFs. Therefore, we develop a hybrid simulation model that combines the methodological strengths of SD and ABM to address this gap. ABM is used to model the transmission of HAIs in LTCFs taking into account heterogeneous contacts between individuals. The spread of HAIs in a hospital whose patients are transferred to and from the LTCF is modelled using SD. Information exchange between the SD and ABM components includes data on the number of patients transferred from one setting to the other, and their status of infection

Malaysian Investment in Vietnam : The Case of Three Companies

Foreign direct investment has made a substantial contribution to the economic growth in Vietnam since its opening in the early of 1990s. Among five top investors in Vietnam in the period of 1990-2010, Malaysia has emerged as a potential investor which is in ASEAN group and at adjacent level of development. In the light of that fact, this dissertation examines the influencing factors to Malaysian investment in Vietnam and the justification for their entry mode choice in this market. A case study of three Malaysian companies who have investment in Vietnam in different industries is conducted to explore the two main issues mentioned above. The results of this paper will show that Malaysian firms are strongly motivated by the objective of market expansion and the size and potential of Vietnam market. In accordance with such motives, wholly-owned subsidiary and majority joint venture are the most selected modes by Malaysian companies

Banking Relationship Ties to Firm Performance: Evidence from Food and Beverage Firms in Vietnam

This paper is aimed at analyzing the effects of banking relationship on performance of Vietnamese firms in Food and Beverage (F&B), one of the highest potential sectors. Panel data of 170 observations covers 34 F&B firms listed in the Vietnam stock exchanges in the period 2014-2018. The fixed effect model (FEM) is applied. The key findings are: First, short-term loan financing, leverage, and fixed asset ratios all negatively impacted on F&B firm performance, while firm size and net profit margin had positive impacts. These findings were consistent with previous studies. Second, the opposite results with previous studies were: (i) negative corelation of ROE and number of banks firms working with, as F&B firms were inefficient in selecting bank partners; (ii) positive relation of short-term liabilities ratio and ROA/ROE, as F&B firms utilize other non-bank liabilities shortly; (iii) foreign ownership had negative relationship with ROA& ROE. Foreign investors did not have significant roles in most F&B firms. Third, long-term borrowing from banks, state ownership and ages all insignificantly correlated with firm performance. Recommendations to F&B firms include: (1) Reduce the short- term loans and fixed assets investment, while increase the cheap equity funding sources via shareholders (2) Be selective in working with banks to have better fees and interest saved with banks. (3) Utilize other short-term liabilities, including payables and advances – the low-cost funding sources. F&B firms have good bargaining powers in requesting advances from their clients. (4) Have smart buy-in strategies on foreign ownership

Open-Vocabulary Affordance Detection in 3D Point Clouds

Affordance detection is a challenging problem with a wide variety of robotic applications. Traditional affordance detection methods are limited to a predefined set of affordance labels, hence potentially restricting the adaptability of intelligent robots in complex and dynamic environments. In this paper, we present the Open-Vocabulary Affordance Detection (OpenAD) method, which is capable of detecting an unbounded number of affordances in 3D point clouds. By simultaneously learning the affordance text and the point feature, OpenAD successfully exploits the semantic relationships between affordances. Therefore, our proposed method enables zero-shot detection and can be able to detect previously unseen affordances without a single annotation example. Intensive experimental results show that OpenAD works effectively on a wide range of affordance detection setups and outperforms other baselines by a large margin. Additionally, we demonstrate the practicality of the proposed OpenAD in real-world robotic applications with a fast inference speed (~100ms). Our project is available at https://openad2023.github.io.Comment: Accepted to The 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023

EmbryosFormer: Deformable Transformer and Collaborative Encoding-Decoding for Embryos Stage Development Classification

The timing of cell divisions in early embryos during the In-Vitro Fertilization (IVF) process is a key predictor of embryo viability. However, observing cell divisions in Time-Lapse Monitoring (TLM) is a time-consuming process and highly depends on experts. In this paper, we propose EmbryosFormer, a computational model to automatically detect and classify cell divisions from original time-lapse images. Our proposed network is designed as an encoder-decoder deformable transformer with collaborative heads. The transformer contracting path predicts per-image labels and is optimized by a classification head. The transformer expanding path models the temporal coherency between embryo images to ensure monotonic non-decreasing constraint and is optimized by a segmentation head. Both contracting and expanding paths are synergetically learned by a collaboration head. We have benchmarked our proposed EmbryosFormer on two datasets: a public dataset with mouse embryos with 8-cell stage and an in-house dataset with human embryos with 4-cell stage. Source code: https://github.com/UARK-AICV/Embryos.Comment: Accepted at WACV 202