Set Of Matches Research Articles

Can older workers be retrained? Canadian evidence from worker-firm linked data

Our empirical analysis is based on Statistics Canada’s worker-firm matched data set, the 2003 Workplace and Employee Survey (WES). The sample size is substantial: about 4,000 workers over the age of 50 and 12,000 between the ages of 25 and 49. Training was a focus of the survey, which offers a wealth of worker-related and firm-related training variables. We found that the mean probability of receiving training was 9.3 percentage points higher for younger workers than for older ones. Almost half of the gap is explained by older workers having fewer training-associated characteristics (personal, employment, workplace, human resource practices and occupation/industry/region), and slightly more than half by them having a lower propensity to receive training, this being the gap that remained after we controlled for differences in training-associated characteristics. Their lower propensity to receive training likely reflects the higher opportunity cost of lost wages during the time spent in training, possible higher psychological costs and lower expected benefits due to their shorter remaining work-life and lower productivity gains from training, as discussed in the literature. The lower propensity of older workers to receive training tended to prevail across 54 different training measures, with notable exceptions discussed in detail. We found that older workers can be trained, but their training should be redesigned in several ways: by making instruction slower and self-paced; by assigning hands-on practical exercises; by providing modular training components to be taken in stages; by familiarizing the trainees with new equipment; and by minimizing required reading and amount of material covered. The concept of “one-size-fits- all” does not apply to the design and implementation of training programs for older workers.

Lattice-Point Mutually Guided Ground-to-Aerial Feature Matching for Urban Scene Images

Ground-to-aerial feature matching bridges information from cross-view images, which enables optimized urban applications, e.g., pixel-level geolocating and complete urban 3-D reconstruction. However, urban ground and aerial images typically suffer from drastic changes in viewpoint, scale, and illumination, together with repetitive patterns. Thus, direct matching of local features between ground and aerial images is particularly difficult because of the low similarity of local descriptors and high ambiguity in true–false match discrimination. For this challenging task, we propose a novel lattice-point mutually guided matching (LPMG) method in this article. We specifically address two key issues: 1) reducing descriptor variance and 2) enhancing true–false match discriminability. The former is solved by recovering the geometry and appearance of the underlying image region in 3-D through automatic view rectification on ground and aerial images. The latter is circumvented by replacing the conventional mismatch removal with an LPMG strategy. In this strategy, the topology structure of repeated façade elements (i.e., lattice), and the high reliable point matching seeds, are first extracted from the rectified ground and aerial images. Then, the point matching seeds guide the self-similar lattice tiles from two views to be precisely aligned, thereby estimating an accurate transformation model from lattice tile correspondences. Finally, the estimated model powerfully supervises the differentiation of true and false matches from the entire putative match set. Extensive experiments conducted on several datasets show that our method can obtain a considerable number of nearly pure correct matches from urban ground and aerial images, significantly outperforming those existing methods.

Task Allocation and On-the-Job Training

We study dynamic task allocation when providers' expertise evolves endogenously through training. We characterize optimal assignment protocols and compare them to discretionary procedures, where it is the clients who select their service providers. Our results indicate that welfare gains from centralization are greater when tasks arrive more rapidly, and when training technologies improve. Monitoring seniors' backlog of clients always increases welfare but may decrease training. Methodologically, we explore a matching setting with endogenous types, and illustrate useful adaptations of queueing theory techniques for such environments.

An Excerpt From Kin: A Memoir

An Excerpt From Kin: A Memoir Shawna Kay Rodenberg (bio) Grand Marais, Minnesota, 1978-1979 Most mornings, the first sound I heard was either a mosquito, tinny in my ear, or the rusty springs of the rough-hewn door as it closed behind my father when he left to stoke the stoves in the other buildings or to wait tables in town. The second sound was my sister's easy breath. She fell asleep rubbing my mousy, fine hair between her [End Page 48] fingers, a process she called fuzzying, so before I could move, I had to loosen her chubby toddler fingers from the tangled loops of my hair, and I did this as carefully as if I were untying a knot in a thin gold necklace, so she would keep sleeping. In Grand Marais, Minnesota, there were only a few weeks in summer when a fire in the stove was unnecessary. My father kept ours packed with wood and poked the coals regularly, but some mornings the heat seemed feeble against the cold, since the bare plywood walls of our room in the Bunk House were uninsulated, and I had to will myself to leave the pocket of warmth trapped beneath the heavy quilts. It felt like leaping into the northern shore of Lake Superior, which was just across the road and vast as an ocean, but visible only in winter when all but the pine trees were bare... The four of us shared half of the Bunk House, which was about the size and length of a singlewide trailer, and sometimes my mother divided it further by using an old bedsheet as a curtain, so she and Dad could have privacy. Despite our small living space, we weren't terribly crowded because we didn't have many possessions: Lay not up for yourselves treasures upon earth, where moth and rust doth corrupt. The Bible was clear that people who collected too much stuff on earth were idol-worshippers, in love with the carnal world and at best only halfway committed to the Kingdom of God. Misti and I had no toys or dolls because they were essentially idols, graven images. My mother disagreed with this idea because she thought little girls needed to practice if they were ever going to learn biblical woman- and motherhood, and I wholeheartedly agreed with her, but she said so only in private. I did have my complete set of the Little House on the Prairie series, which she chose for my birthday, a special edition so the spines and matching cardboard case were baby [End Page 49] blue instead of buttery yellow like the ones at the library. Dad made the gift even more special by hanging a small wooden shelf above my side of the bed I shared with Misti, and the matching set of books complete in their case on my very own shelf was my most prized possession. I never tired of reading those books, especially Little House in the Big Woods, because no matter which chapter I chose, I could see myself in the story. Laura Ingalls lived in the wilderness and, though she loved her father best, found being good impossible. Jealous of her sister's golden hair, Laura smacked her across the face hard and had to be spanked. She loved sugar and spoke out of turn. She played tricks on people who treated her badly because she was poor. She embarrassed herself by hoarding pebbles from the shores of Lake Pepin, tearing the pocket of her dress. I didn't tell anybody, but I thought about her like she was my best friend. And just like her, I was happy to play with wood chips and thimbles, thrilled to receive simple tokens for birthdays or Christmas, which, like all holidays, we were not supposed to celebrate, though each year my mother conspired to create our own secret Christmas celebration together. In the few private moments we had between our schedule of meals and women's Bible study, school, which was more Bible study, chores, and evening services, she'd gather Misti and me on her bed and retrieve a handful of treasures from the...

Voleibol de Praia: Análise Temporal e Respostas Endócrinas de Atletas de Nível Nacional

The aim of this study was to characterize temporal aspects and to verify the acute effect of a beach volleyball game on testosterone, cortisol and T:C ratio in young athletes. Participants were 16 male athletes (age= 17 ± 2,44 years, height= 1,84 ± 0,06 m, body mass 76,23 ± 9,54 kg, BMI 22,35 ± 1,92, number of training sessions per week 4 ± 1,20 days). Athletes made a match with official rules which was filmed for analysis. Saliva was used to measure testosterone and cortisol levels and testosterone/cortisol ratio (T:C ratio) was calculated. Hormonal analyzes were done in duplicate using ELISA method and comparisons between beginning of the match, end of the first set and end of the match using Anova one-way of repeated measures. Total match duration was 30 min and 49s (± 0.01s), with rallies of 6s (± 01s) and time between rallies of 20s (± 0.02s). Cortisol showed a linear tendency increasing over time and T:C ratio showed a quadratic tendency reducing at the end of first set and reestablishing at the end of the game. It is noteworthy that a beach volleyball match lasting approximately 30 minutes promotes enough stimulus to generate impact on endocrine markers. Keywords: Athletes, Biological markers, Biomarkers, Athletic performance.

Supervised learning for parameterized Koopmans–Beckmann’s graph matching

Abstract In this paper, we discuss a novel graph matching problem, namely the parameterized Koopmans–Beckmann’s graph matching (KBGMw). KBGMw is defined by a weighted linear combination of a series of Koopmans–Beckmann’s graph matching. First, we show that KBGMw can be taken as a special case of the parameterized Lawler’s graph matching, subject to certain conditions. Second, based on structured SVM, we propose a supervised learning method for automatically estimating the parameters of KBGMw. Experimental results on both synthetic and real image matching data sets show that the proposed method achieves relatively better performances, even superior to some deep learning methods.

Interpretable sports team rating models based on the gradient descent algorithm

We introduce several new sports team rating models based on the gradient descent algorithm. More precisely, the models can be formulated by maximising the likelihood of match results observed using a single step of this optimisation heuristic. The proposed framework is inspired by the prominent Elo rating system, and yields an iterative version of ordinal logistic regression, as well as different variants of Poisson regression-based models. This construction makes the update equations easy to interpret, and adjusts ratings once new match results are observed. Thus, it naturally handles temporal changes in team strength. Moreover, a study of association football data indicates that the new models yield more accurate forecasts and are less computationally demanding than corresponding methods that jointly optimise the likelihood for the whole set of matches.

A note on the lattice structure for matching markets via linear programming

Given two stable matchings in a many-to-one matching market with $ q $-responsive preferences, by manipulating the objective function of the linear program that characterizes the stable matching set, we compute the least upper bound and greatest lower bound between them.

Identifying Fintech risk through machine learning: analyzing the Q&A text of an online loan investment platform

Financial risks associated with Fintech have been increasing with its significant growth in recent years. Aiming at addressing the problem of identifying risks in online lending investment under a financial technology platform, we develop a Q&A text risk recognition model based on attention mechanism and Bi-directional Long Short-Term Memory. First, the Q&A pairing on the text data set is carried out, and the matching data set is selected for the next analysis. Secondly, the online loan investment platform is assessed by the named entity recognition of the question text. Finally, the risk level of the corresponding investment platform is evaluated based on the answer text. The experimental results show that the proposed model has achieved improved precision, recall, F1-score, and accuracy compared with other models. Our proposed model can be applied to identify the risks from the text posted on online loan investment platforms and can be used to guide investors’ investment and improve the management of financial technology platforms.

Mental toughness of first division women football players in Gauteng Province, South Africa

The mental preparation of woman athletes, including woman football players, have been neglected for quite some time. For woman football players to perform to their full potential, they need to know how to play under pressure, get out of difficulties effectively and maintain their good performance when faced with continuous challenges during the game. The aim of this study was therefore to determine the psychological profiles of woman football players in first division leagues in Gauteng Province of South Africa, with a specific focus on their mental toughness. A quantitative approach was used to gather and analyse both the descriptive and inferential data. A purposive sample of 148 participants (aged 20.2 ± 5.7 years) from both the Sasol and South African Football Association (SAFA) leagues were asked to complete the Mental Skills Inventory (MSI), Sport Mental Toughness Questionnaire (SMTQ), Sport Competition Anxiety Test (SCAT) and Rosenberg Self-esteem Scale (RSQ) to assess their mental toughness levels. The results indicated that woman football players in South African first division leagues have a moderate ability for all variables of mental toughness, and could benefit from a psychological skills training programme aimed at increasing their self-esteem and anxiety management. A number of woman football players (26.4%) had high anxiety levels, while 33.8% showed low self-esteem, which could have a negative impact on the players while in a match setting. Furthermore, the outcomes of the results showed that self-esteem and anxiety were inversely related to the mental toughness of the players (.625 and -.436, respectively). These are two of the most important mental skills required for improving performance in a football match. Improving the mental toughness of the players could lead to an increase in self-esteem thereby reducing their anxiety levels to perform better. The study recommended that mental preparation be included in team preparation to improve performance outcomes as indicated by the positive relationship between physiological skills, mental toughness and sport performance.

Training confounder-free deep learning models for medical applications

The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variables (e.g., diagnosis). Improper modeling of those relationships often results in spurious and biased associations. Traditional machine learning and statistical models minimize the impact of confounders by, for example, matching data sets, stratifying data, or residualizing imaging measurements. Alternative strategies are needed for state-of-the-art deep learning models that use end-to-end training to automatically extract informative features from large set of images. In this article, we introduce an end-to-end approach for deriving features invariant to confounding factors while accounting for intrinsic correlations between the confounder(s) and prediction outcome. The method does so by exploiting concepts from traditional statistical methods and recent fair machine learning schemes. We evaluate the method on predicting the diagnosis of HIV solely from Magnetic Resonance Images (MRIs), identifying morphological sex differences in adolescence from those of the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA), and determining the bone age from X-ray images of children. The results show that our method can accurately predict while reducing biases associated with confounders. The code is available at https://github.com/qingyuzhao/br-net.

The roommate problem with externalities

This paper extends the roommate problem to include externalities, allowing preferences for a partner to depend on the situation of others. Stability concepts for matchings and partitions of the set of agents are proposed and characterized, conditional on all agents having prudent expectations about other agents’ reactions to deviations. We prove that any roommate problem with externalities has a stable partition and that a stable matching exists if there is a stable partition without odd rings. These results allow us to find restrictions on the space of preferences ensuring the existence of a stable matching. We also show that some classical properties are lost in the presence of externalities: the existence of paths to stability from any unstable matching, the coincidence of the core with the set of stable matchings, and the invariance of the set of agents who are alone in a stable matching.

Automatic 3D point cloud registration algorithm based on triangle similarity ratio consistency

Three-dimensional (3D) point cloud registration is a fundamental key issue in 3D reconstruction, 3D object recognition and augmented reality. In this study, the authors propose a novel local feature descriptor called local angle statistics histogram (LASH) for efficient 3D point cloud registration. LASH forms a description of local shape geometries by encoding their properties on angles between the normal vector of the point and the vector formed by the point and other points in its local neighbourhood. In addition, they propose a 3D point cloud registration algorithm based on LASH. The registration algorithm firstly detects triangle matching points with consistent similarity ratios, and then aggregates each pair of triangular matching points into a set of matching points. They can use these matching sets to calculate multiple transformations between two point clouds. Finally, they use the error function to identify the best transformation and to achieve coarse alignment of the two point clouds. Experiments and comparisons with other global algorithms demonstrate that the proposed approach can be applied to register point clouds with considerable or limited overlaps and is robust to noise.

Allogeneic Hematopoietic Stem Cell Transplant Offer Good Outcomes in Pediatric Aplastic Anemia: Experience From Developing World.

Between 2014 and 2020, 31 patients with severe aplastic anemia (SAA) underwent full match allogeneic hematopoietic stem cell transplantation at our center. Of the 31 patients with SAA, 19 had acquired aplastic anemia, 2 had Diamond Blackfan anemia and 10 had Fanconi anemia. Donors were either matched sibling (n=29), related donors (n=2), or unrelated donors (n=3). Peripheral blood stem cells were the graft source in all the cases except 1. Fludarabine-based reduced intensity conditioning was used in all except for patients with a diagnosis of Diamond Blackfan anemia. All patients except 1 achieved hematologic recovery in the form of neutrophil engraftment at 13 days (range, 9 to 17), whereas platelet engraftment occurred at 14 days (range, 10 to 18). Graft versus host disease (GvHD) prophylaxis consisted of cyclosporine and methotrexate ±antithymocyte globulin (horse/rabbit). Acute GvHD developed in 12.9% patients, whereas no patients developed chronic GvHD till the time of last follow-up. The 2-year overall survival for the entire cohort was 93.21±4.6%. In patients with SAA, allogeneic stem cell transplant using fludarabine-based conditioning regimens are very well tolerated and have excellent outcomes in a full match setting.

Two-sided strategy-proofness in many-to-many matching markets

We study the existence of group strategy-proof stable rules in many-to-many matching markets under responsiveness of agents’ preferences. We show that when firms have acyclical preferences over workers the set of stable matchings is a singleton, and the worker-optimal stable mechanism is a stable and group strategy-proof rule for firms and workers. Furthermore, acyclicity is the minimal condition guaranteeing the existence of stable and strategy-proof mechanisms in many-to-many matching markets.

Improving solution times for stable matching problems through preprocessing

We present new theory, heuristics, and algorithms for preprocessing instances of the Stable Marriage problem with Ties and Incomplete lists (SMTI) and the Hospitals/Residents problem with Ties (HRT). Instances of these problems can be preprocessed by removing from the preference lists of some agents entries such that the set of stable matchings is not affected. Removing such entries reduces the problem size, creating smaller models that can be more easily solved by integer programming (IP) solvers. The new theorems are the first to describe when preference list entries can be removed from instances of HRT when ties are present on both sides, and also extend existing results on preprocessing instances of SMTI. A number of heuristics, as well as an IP model and a graph-based algorithm, are presented to find and perform this preprocessing. Experimental results show that our new graph-based algorithm achieves a 44% reduction in the average running time to find a maximum weight stable matching in real-world instances of SMTI compared to existing preprocessing techniques, and 80% compared to not using preprocessing. We also show that, when solving MAX-HRT instances with ties on both sides, our new techniques can reduce runtimes by up to 55%.

Matching with myopic and farsighted players

We introduce the new notion of the pairwise myopic-farsighted stable set to study stable matchings under the assumption that players can be both myopic and farsighted. For the special case where all players are myopic, our concept predicts the set of matchings in the core. When all players are farsighted, we provide the characterization of pairwise myopic-farsighted stable sets: a set of matchings is a pairwise myopic-farsighted stable set if and only if it is a singleton consisting of a core element. This result confirms the result obtained by Mauleon et al. (2011) with a completely different effectivity function and provides a new special case where the farsighted stable set is absolutely maximal (Ray and Vohra, 2019) and coincides with the Strong Rational Expectations Farsighted Stable Set (Dutta and Vohra, 2017). When myopic and farsighted players interact, matchings outside the core can be stable and the most farsighted side can achieve its optimal stable matching.

Matching with Myopic and Farsighted Players

We study stable sets for marriage problems under the assumption that players can be both myopic and farsighted. We introduce the new notion of the myopic-farsighted stable set, which is based on the notion of a myopic-farsighted improving path. A myopic-farsighted stable set is the set of matchings such that there is no myopic-farsighted improving path from any matching in the set to another matching in the set (internal stability) and there is a myopic-farsighted improving path from any matching outside the set to some matching in the set (external stability). For the special cases where all players are myopic and where all players are farsighted, our concept predicts the set of matchings in the core. When all men are myopic and the top choice of each man is a farsighted woman, we show that the singleton consisting of the woman-optimal stable matching is a myopic-farsighted stable set. The same result holds when all women are farsighted. We present examples where this is the unique myopic-farsighted stable set as well as examples of myopic-farsighted stable sets consisting of a core element different from the woman-optimal matching or even of a non-core element.

Research on Binocular Visual System of Robotic Arm Based on Improved SURF Algorithm

With the increasingly extensive application of robots in industrial production, visual of the robotic arm has become an important research direction in the field of robots, which is also recognized as believed to widely considered to the most vital directions of modern high-tech development. In the robot vision system, the binocular visual system is most widely applied. When the robotic arm based on binocular vision captures the object, SURF algorithm is adopted to realize feature point extraction and matching of images. Because of the influence of the objective factors, there is false match in the process of SURF matching of feature points. In this paper, SURF algorithm is improved and reverse feature vectors matching strategy is used to initialize the matching points set. Then the RANSAC algorithm is adopted to select the initial matching points set in accordance of the polar geometric model to get the final good match set. The experiment results show that the improved SURF algorithm has higher registration accuracy and faster speed than SURF.

Revisiting Complementarity between Japanese FDI and the Import of Intermediate Goods: Agglomeration Effects and Parent-firm Heterogeneity

This study revisits the nexus between foreign direct investment (FDI) and international trade in the dynamic perspective, focusing on intermediate goods imports of affiliates of Japanese firms operating in China. To examine the effect of the formation of the agglomeration and the recent FDI made by small firms, both of which have been overlooked in the literature, we construct a unique parent-affiliate matched panel data set of trade in intermediate goods, and estimate a discrete-time hazard model over the 2000–06 period. We found that affiliates owned by firms in agglomerated regions in Japan have a shorter duration of trade in intermediate goods compared with affiliates owned by smaller Japanese firms.