A Simple Nonlinear Economic Models of Market Price; The Case of the Cobweb

We are studying how the presence of nonlinear terms in the supply and demand model changes the price behavior of the system. Our analysis focuses on discrete dynamical systems. We start with a simple linear supply and demand model of two markets interacting. Afterwards, we add nonlinear terms and observe the results. We hypothesize that the presence of nonlinearity in the supply and demand model, with two interrelated markets, will exhibit chaotic price behavior. Furthermore, we expect that the system will become chaotic via period-doubling bifurcations, and that all orbits will converge to a strange attractor

Simulation of Nonstationary Gaussian Process by Consecutive Conditioning

This thesis aims to develop the method of consecutive conditioning, which is used to directly simulate a stochastic process given an arbitrary covariance function. As a method for simulating stochastic processes, consecutive conditioning is useful in at least in three respects. While most methods require modeling of the covariance function prior to simulation, consecutive conditioning can be used with any arbitrary covariance function, thus introducing less error into the simulation than other methods. Second, consecutive conditioning allows us to perform very fast computations during simulation and can be used even by people who are not experts in modeling, unlike other methods which require substantial statistical work prior to simulation. Finally, this method can be used to simulate both stationary and nonstationary processes, which is particularly useful since the majority of real-world physical processes are nonstationary.With the Kullback-Leibler divergence in hand, we validate the consecutive conditioning method as follows. After executing our method on a simulated distribution, we compare the resulting distribution with the true distribution for calculating the KL values. Then, we demonstrate that the consecutive conditioning works well on different covariance functions by applying it to a different series of simulations. First, we use a consecutive conditioning with several different covariance functions to simulate two time points of a stochastic process, then compare the results to determine the best covariance function for our method. Finally, we use our method to generate five time points from a stochastic process in both uninitialized and initialized cases, then evaluate the results

When employees are ostracised, the whole organisation suffers

They stop helping colleagues, following the rules and offering ideas, write Chia-Huei Wu and colleague

SBTRec- A Transformer Framework for Personalized Tour Recommendation Problem with Sentiment Analysis

When traveling to an unfamiliar city for holidays, tourists often rely on guidebooks, travel websites, or recommendation systems to plan their daily itineraries and explore popular points of interest (POIs). However, these approaches may lack optimization in terms of time feasibility, localities, and user preferences. In this paper, we propose the SBTRec algorithm: a BERT-based Trajectory Recommendation with sentiment analysis, for recommending personalized sequences of POIs as itineraries. The key contributions of this work include analyzing users' check-ins and uploaded photos to understand the relationship between POI visits and distance. We introduce SBTRec, which encompasses sentiment analysis to improve recommendation accuracy by understanding users' preferences and satisfaction levels from reviews and comments about different POIs. Our proposed algorithms are evaluated against other sequence prediction methods using datasets from 8 cities. The results demonstrate that SBTRec achieves an average F1 score of 61.45%, outperforming baseline algorithms. The paper further discusses the flexibility of the SBTRec algorithm, its ability to adapt to different scenarios and cities without modification, and its potential for extension by incorporating additional information for more reliable predictions. Overall, SBTRec provides personalized and relevant POI recommendations, enhancing tourists' overall trip experiences. Future work includes fine-tuning personalized embeddings for users, with evaluation of users' comments on POIs,~to further enhance prediction accuracy

BTRec: BERT-Based Trajectory Recommendation for Personalized Tours

An essential task for tourists having a pleasant holiday is to have a well-planned itinerary with relevant recommendations, especially when visiting unfamiliar cities. Many tour recommendation tools only take into account a limited number of factors, such as popular Points of Interest (POIs) and routing constraints. Consequently, the solutions they provide may not always align with the individual users of the system. We propose an iterative algorithm in this paper, namely: BTREC (BERT-based Trajectory Recommendation), that extends from the POIBERT embedding algorithm to recommend personalized itineraries on POIs using the BERT framework. Our BTREC algorithm incorporates users' demographic information alongside past POI visits into a modified BERT language model to recommend a personalized POI itinerary prediction given a pair of source and destination POIs. Our recommendation system can create a travel itinerary that maximizes POIs visited, while also taking into account user preferences for categories of POIs and time availability. Our recommendation algorithm is largely inspired by the problem of sentence completion in natural language processing (NLP). Using a dataset of eight cities of different sizes, our experimental results demonstrate that our proposed algorithm is stable and outperforms many other sequence prediction algorithms, measured by recall, precision, and F1-scores.Comment: RecSys 2023, Workshop on Recommenders in Touris

Concentrated growth and spatial disparities in Korea

The purpose of this study is to analyze the conditions and change of spatial inequality of South Korea according to the spatial policy. For this, this study will characteristics of the spatial policies by Korean government for 20 years (1995~2014), and will analyze what effect the spatial policy had on the spatial inequality of South Korea. South Korea¡¯s spatial inequality is very severe in the world. For example, concentration of Seoul, Korea is much higher than London, England, Tokyo, Japan and Paris, France. Therefore, South Korea¡¯s top priority for sustainable development is to solve concentration to capital region and spatial inequality. However, South Korea has pushed forward alternately the growth policy and balance policy for 20 years. Spatial policy of South Korea had been carried forward by the growth policy till 1998, but it changed to the balance policy between 1998~2007. Since 2008, it has been being pushed forward by the growth policy again. As a result, spatial inequality of South Korea somewhat eased off between 2000~2005, but it rather has shown a tendency of being expanded since. Particularly, the spatial inequality is broadening in population, economic, industry, finance and the powers sectors. In addition, infrastructure, health and welfare, education sectors, whose spatial inequality is relatively low, the spatial inequality is being expanded

Genome-wide expression profiles of endogenous retroviruses in lymphoid tissues and their biological properties

AbstractEndogenous retroviruses (ERVs) constitute approximately 8–10% of the human and mouse genome. Some autoimmune diseases are attributed to the altered expression of ERVs. In this study, we examined the ERV expression profiles in lymphoid tissues and analyzed their biological properties. Tissues (spleen, thymus, and lymph nodes [axillary, inguinal, and mesenteric]) from C57BL/6J mice were analyzed for differential murine ERV (MuERV) expression by RT-PCR examination of polymorphic U3 sequences. Each tissue had a unique profile of MuERV expression. A genomic map identifying 60 putative MuERVs was established using 22 unique U3s as probes and their biological properties (primer binding site, coding potential, transcription regulatory element, tropism, recombination event, and integration age) were characterized. Interestingly, 12 putative MuERVs retained intact coding potentials for all three polypeptides essential for virus assembly and replication. We suggest that MuERV expression is differentially regulated in conjunction with the transcriptional environment of individual lymphoid tissues