Finding Stable Matchings That Are Robust to Errors in the Input

In this paper, we introduce the issue of finding solutions to the stable matching problem that are robust to errors in the input and we obtain the first algorithmic results on this topic. In the process, we also initiate work on a new structural question concerning the stable matching problem, namely finding relationships between the lattices of solutions of two "nearby" instances. Our main algorithmic result is the following: We identify a polynomially large class of errors, D, that can be introduced in a stable matching instance. Given an instance A of stable matching, let B be the instance that results after introducing one error from D, chosen via a discrete probability distribution. The problem is to find a stable matching for A that maximizes the probability of being stable for B as well. Via new structural properties of the type described in the question stated above, we give a polynomial time algorithm for this problem

Improving the health care response to gender-based violence: Phase II

In 2009, the Population Council/Vietnam in collaboration with the Hanoi Health Service carried out an evaluation survey among Duc Giang Hospital staff to assess the extent to which awareness and perceptions of gender-based violence (GBV) had changed since the project commenced in 2005. The survey also assessed the extent to which the response of the hospital and Women’s Center for Counseling and Health had been strengthened, and made recommendations on changes to improve the situation. Overall, this project has been effective in raising awareness and willingness to integrate GBV screening into health services. The project conducted its training program at a time when the community was also becoming increasingly aware, with the result that younger health practitioners are more sensitive to GBV issues. These two actions were complementary and reinforced one another. The result is that health staff are more willing to screen and help GBV victims. This final project evaluation report states that to map out where GBV is most prevalent, who is most vulnerable, and how can it be most effectively addressed, high-quality population-based GBV surveys should be a priority for Vietnam

Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion

Inspired by the work of Kempe et al. [Kempe, Kleinberg, Oren, Slivkins, EC 2013], we introduce and analyze a model on opinion formation; the update rule of our dynamics is a simplified version of that of [Kempe, Kleinberg, Oren, Slivkins, EC 2013]. We assume that the population is partitioned into types whose interaction pattern is specified by a graph. Interaction leads to population mass moving from types of smaller mass to those of bigger mass. We show that starting uniformly at random over all population vectors on the simplex, our dynamics converges point-wise with probability one to an independent set. This settles an open problem of [Kempe, Kleinberg, Oren, Slivkins, EC 2013], as applicable to our dynamics. We believe that our techniques can be used to settle the open problem for the Kempe et al. dynamics as well. Next, we extend the model of Kempe et al. by introducing the notion of birth and death of types, with the interaction graph evolving appropriately. Birth of types is determined by a Bernoulli process and types die when their population mass is less than epsilon (a parameter). We show that if the births are infrequent, then there are long periods of "stability" in which there is no population mass that moves. Finally we show that even if births are frequent and "stability" is not attained, the total number of types does not explode: it remains logarithmic in 1/epsilon

ONLINE SHOPPING TRENDS OF VIETNAMESE YOUNG PEOPLE

With the drastic development of the Internet and social media, online shopping gradually gains traction after being introduced to the market in the 1990s. Since the outbreak of Covid-19 in 2020, this trend has become more popular on a global scale. There are numerous benefits including the wide range of products, sales, and saving consumers' time, which attract more and more people, especially the youth. As far as the increasing importance of online shopping is concerned, our research team has a deeper insight into it through articles and research on Vietnamese Generation Z, who were born from 1995 to 2012 to understand more about the demands, time usage, advantages, and disadvantages of online shopping. From the results of the research, we put forward some solutions that consumers could implement to purchase things online more effectively

Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud

Several cloud-based applications, such as cloud gaming, rent servers to execute jobs which arrive in an online fashion. Each job has a resource demand and must be dispatched to a cloud server which has enough resources to execute the job, which departs after its completion. Under the `pay-as-you-go' billing model, the server rental cost is proportional to the total time that servers are actively running jobs. The problem of efficiently allocating a sequence of online jobs to servers without exceeding the resource capacity of any server while minimizing total server usage time can be modelled as a variant of the dynamic bin packing problem (DBP), called MinUsageTime DBP. In this work, we initiate the study of the problem with multi-dimensional resource demands (e.g. CPU/GPU usage, memory requirement, bandwidth usage, etc.), called MinUsageTime Dynamic Vector Bin Packing (DVBP). We study the competitive ratio (CR) of Any Fit packing algorithms for this problem. We show almost-tight bounds on the CR of three specific Any Fit packing algorithms, namely First Fit, Next Fit, and Move To Front. We prove that the CR of Move To Front is at most $(2\mu+1)d +1$, where $\mu$ is the ratio of the max/min item durations. For $d=1$, this significantly improves the previously known upper bound of $6\mu+7$ (Kamali & Lopez-Ortiz, 2015). We then prove the CR of First Fit and Next Fit are bounded by $(\mu+2)d+1$ and $2\mu d+1$, respectively. Next, we prove a lower bound of $(\mu+1)d$ on the CR of any Any Fit packing algorithm, an improved lower bound of $2\mu d$ for Next Fit, and a lower bound of $2\mu$ for Move To Front in the 1-D case. All our bounds improve or match the best-known bounds for the 1-D case. Finally, we experimentally study the average-case performance of these algorithms on randomly generated synthetic data, and observe that Move To Front outperforms other Any Fit packing algorithms.Comment: 24 pages, to appear at SPAA 202

LAPFormer: A Light and Accurate Polyp Segmentation Transformer

Polyp segmentation is still known as a difficult problem due to the large variety of polyp shapes, scanning and labeling modalities. This prevents deep learning model to generalize well on unseen data. However, Transformer-based approach recently has achieved some remarkable results on performance with the ability of extracting global context better than CNN-based architecture and yet lead to better generalization. To leverage this strength of Transformer, we propose a new model with encoder-decoder architecture named LAPFormer, which uses a hierarchical Transformer encoder to better extract global feature and combine with our novel CNN (Convolutional Neural Network) decoder for capturing local appearance of the polyps. Our proposed decoder contains a progressive feature fusion module designed for fusing feature from upper scales and lower scales and enable multi-scale features to be more correlative. Besides, we also use feature refinement module and feature selection module for processing feature. We test our model on five popular benchmark datasets for polyp segmentation, including Kvasir, CVC-Clinic DB, CVC-ColonDB, CVC-T, and ETIS-LaribComment: 7 pages, 7 figures, ACL 2023 underrevie

Insights into the magnetic origin of CunCr (n= 9÷11) clusters: A superposition of magnetic and electronic shells

Interests in Cu-Cr sub-nanometer systems have been increasing due to the recently-found icosahedral Cu12Cr cluster as a superatomic molecule, where the 3d-Cr and 4s-Cu electrons can phenomenologically form the 18-e molecular shell (1S21P61D10) of Cu12Cr. In this report, we set out to investigate the energetically-preferred geometries and stabilities of CunCr (n = 9÷11) clusters using the density-functional-theory calculations. It is found that not all of 3d-Cr electrons involve in the formation of the cluster shell and the remaining localized ones cause the magnetic moment of the clusters, which is different from what was believed