Hasil untuk "Manners and customs (General)"

Maqbool Dada, Brett Hathaway, Evgeny Kagan

Customer service has evolved beyond in-person visits and phone calls to include live chat, AI chatbots and social media, among other contact options. Service providers typically refer to these contact modalities as "channels". Within each channel, customer service agents are tasked with managing and resolving a stream of inbound service requests. Each request involves milestones where the agent must decide whether to keep assisting the customer or to transfer them to a more skilled -- and often costlier -- provider. To understand how this request resolution process should be managed, we develop a model in which each channel is represented as a gatekeeper system and characterize the structure of the optimal request resolution policy. We then turn to the broader question of the firm's customer service design, which includes the strategic problem of which channels to deploy, the tactical questions of at what level to staff the live-agent channel and to what extent to train an AI chatbot, and the operational question of how to control the live-agent channel. Examining the interplay between strategic, tactical, and operational decisions through numerical methods, we show, among other insights, that service quality can be improved, rather than diminished, by chatbot implementation.

Lidia PRISAC

Anchored to the interwar realities, Chișinău was marked by profound changes in its distinctive character, with a symbiosis between the old and the new, between the cultural heritage of the Tsarist period and the newly established, Romanian one. However, customs, mores and mentalities are the most difficult to change within a society. Deeply marked by the manners characteristic of the Russian world and the persistent multicultural amalgam, the behavioral traits of the Chișinău residents of the interwar period show tendencies to consolidate a regional specificity. Caught in a space of comfort, as a generator of a “daily drowsiness”, the inhabitants of Chișinău create the impression of passive, resigned, contemplative and calm-hearted people. At the same time, the locals seem to be of an unprecedented hospitality. Out of inertia, in the urban environment, the perpetuation of customs, traditions and family mores reported to high society, in accordance with the patriarchal Tsarist traditions, continues. Cultivated in the family, school and church, Chișinău society seems to perpetuate healthy moral principles and values, produced by a code of good manners based on common sense, mutual respect, fairness, honor, humanity, honesty, etc. At the same time, the conduct of the townspeople often gravitates between morality, religiosity and superstitions; the inhabitants being forced to choose between moral principles and existential “pleasures”.

Subhadip Nandi, Neeraj Agrawal, Anshika Singh et al.

Customer service chatbots are conversational systems aimed at addressing customer queries, often by directing them to automated workflows. A crucial aspect of this process is the classification of the customer's intent. Presently, most intent classification models for customer care utilise only customer query for intent prediction. This may result in low-accuracy models, which cannot handle ambiguous queries. An ambiguous query like "I didn't receive my package" could indicate a delayed order, or an order that was delivered but the customer failed to receive it. Resolution of each of these scenarios requires the execution of very different sequence of steps. Utilizing additional information, such as the customer's order delivery status, in the right manner can help identify the intent for such ambiguous queries. In this paper, we have introduced a context-aware NLU model that incorporates both, the customer query and contextual information from the customer's order status for predicting customer intent. A novel selective attention module is used to extract relevant context features. We have also proposed a multi-task learning paradigm for the effective utilization of different label types available in our training data. Our suggested method, Multi-Task Learning Contextual NLU with Selective Attention Weighted Context (MTL-CNLU-SAWC), yields a 4.8% increase in top 2 accuracy score over the baseline model which only uses user queries, and a 3.5% improvement over existing state-of-the-art models that combine query and context. We have deployed our model to production for Walmart's customer care domain. Accurate intent prediction through MTL-CNLU-SAWC helps to better direct customers to automated workflows, thereby significantly reducing escalations to human agents, leading to almost a million dollars in yearly savings for the company.

Honglin Liu, Chao Sun, Peng Hu et al.

Conventional representation learning methods learn a universal representation that primarily captures dominant semantics, which may not always align with customized downstream tasks. For instance, in animal habitat analysis, researchers prioritize scene-related features, whereas universal embeddings emphasize categorical semantics, leading to suboptimal results. As a solution, existing approaches resort to supervised fine-tuning, which however incurs high computational and annotation costs. In this paper, we propose Conditional Representation Learning (CRL), aiming to extract representations tailored to arbitrary user-specified criteria. Specifically, we reveal that the semantics of a space are determined by its basis, thereby enabling a set of descriptive words to approximate the basis for a customized feature space. Building upon this insight, given a user-specified criterion, CRL first employs a large language model (LLM) to generate descriptive texts to construct the semantic basis, then projects the image representation into this conditional feature space leveraging a vision-language model (VLM). The conditional representation better captures semantics for the specific criterion, which could be utilized for multiple customized tasks. Extensive experiments on classification and retrieval tasks demonstrate the superiority and generality of the proposed CRL. The code is available at https://github.com/XLearning-SCU/2025-NeurIPS-CRL.

Nupur Kumari, Grace Su, Richard Zhang et al.

Model customization introduces new concepts to existing text-to-image models, enabling the generation of these new concepts/objects in novel contexts. However, such methods lack accurate camera view control with respect to the new object, and users must resort to prompt engineering (e.g., adding ``top-view'') to achieve coarse view control. In this work, we introduce a new task -- enabling explicit control of the object viewpoint in the customization of text-to-image diffusion models. This allows us to modify the custom object's properties and generate it in various background scenes via text prompts, all while incorporating the object viewpoint as an additional control. This new task presents significant challenges, as one must harmoniously merge a 3D representation from the multi-view images with the 2D pre-trained model. To bridge this gap, we propose to condition the diffusion process on the 3D object features rendered from the target viewpoint. During training, we fine-tune the 3D feature prediction modules to reconstruct the object's appearance and geometry, while reducing overfitting to the input multi-view images. Our method outperforms existing image editing and model customization baselines in preserving the custom object's identity while following the target object viewpoint and the text prompt.

Linmi Tao, Ruiyang Liu, Donglai Tao et al.

Numerical difference computation is one of the cores and indispensable in the modern digital era. Tao general difference (TGD) is a novel theory and approach to difference computation for discrete sequences and arrays in multidimensional space. Built on the solid theoretical foundation of the general difference in a finite interval, the TGD operators demonstrate exceptional signal processing capabilities in real-world applications. A novel smoothness property of a sequence is defined on the first- and second TGD. This property is used to denoise one-dimensional signals, where the noise is the non-smooth points in the sequence. Meanwhile, the center of the gradient in a finite interval can be accurately location via TGD calculation. This solves a traditional challenge in computer vision, which is the precise localization of image edges with noise robustness. Furthermore, the power of TGD operators extends to spatio-temporal edge detection in three-dimensional arrays, enabling the identification of kinetic edges in video data. These diverse applications highlight the properties of TGD in discrete domain and the significant promise of TGD for the computation across signal processing, image analysis, and video analytic.

Elias José Torres Feijó

O presente trabalho propõe tomar em consideração a componente afetiva na construção identitária individual e coletiva. São formulados os conceitos de identidade afetivizada (a assunção sentimental de elementos identitários: o elemento identitário gera afetividade) e afetividade identitária (o resultado numa identidade a partir dum elemento ou duns elementos mediadores não necessariamente vinculados de modo linear com o objeto da identificação). Aplica-se em concreto à questão ortográfica no caso galego e como essas componentes podem incidir nas elaborações afetivas das pessoas em relação à conceção da língua, à literatura e aos afetos e orientações de leitura; e como essas orientações se relacionam com o próprio conceito de nação e das suas relações externas.

Jitendra Maan, Harsh Maan

It becomes a significant challenge to predict customer behavior and retain an existing customer with the rapid growth of digitization which opens up more opportunities for customers to choose from subscription-based products and services model. Since the cost of acquiring a new customer is five-times higher than retaining an existing customer, henceforth, there is a need to address the customer churn problem which is a major threat across the Industries. Considering direct impact on revenues, companies identify the factors that increases the customer churn rate. Here, key objective of the paper is to develop a unique Customer churn prediction model which can help to predict potential customers who are most likely to churn and such early warnings can help to take corrective measures to retain them. Here, we evaluated and analyzed the performance of various tree-based machine learning approaches and algorithms and identified the Extreme Gradient Boosting XGBOOST Classifier as the most optimal solution to Customer churn problem. To deal with such real-world problems, Paper emphasize the Model interpretability which is an important metric to help customers to understand how Churn Prediction Model is making predictions. In order to improve Model explainability and transparency, paper proposed a novel approach to calculate Shapley values for possible combination of features to explain which features are the most important/relevant features for a model to become highly interpretable, transparent and explainable to potential customers.

D. A. Christie, N. J. Mayne, R. M. Gillard et al.

We investigate the impact of clouds on the atmosphere of GJ~1214b using the radiatively-coupled, phase-equilibrium cloud model {\sc EddySed} coupled to the {\sc Unified Model} general circulation model. We find that, consistent with previous investigations, high metallicity ($100\times$ solar) and clouds with large vertical extents (a sedimentation factor of $f_\mathrm{sed} = 0.1$) are required to best match the observations, although metallicities even higher than those investigated here may be required to improve agreement further. We additionally find that in our case which best matches the observations ($f_\mathrm{sed}=0.1$), the velocity structures change relative to the clear sky case with the formation of a superrotating jet being suppressed, although further investigation is required to understand the cause of the suppression. The increase in cloud extent with $f_\mathrm{sed}$ results in a cooler planet due to a higher albedo, causing the atmosphere to contract. This also results in a reduced day-night contrast seen in the phase curves, although the introduction of cloud still results in a reduction of the phase offset. We additionally investigate the impact the the {\sc Unified Model}'s pseudo-spherical irradiation scheme on the calculation of heating rates, finding that the introduction of nightside shortwave heating results in slower mid-latitude jets compared to the plane parallel irradiation scheme used in previous works. We also consider the impact of a gamma distribution, as opposed to a log-normal distribution, for the distribution of cloud particle radii and find the impact to be relatively minor.

Sonam Singh, Anthony Rios

Customers are rapidly turning to social media for customer support. While brand agents on these platforms are motivated and well-intentioned to help and engage with customers, their efforts are often ignored if their initial response to the customer does not match a specific tone, style, or topic the customer is aiming to receive. The length of a conversation can reflect the effort and quality of the initial response made by a brand toward collaborating and helping consumers, even when the overall sentiment of the conversation might not be very positive. Thus, through this study, we aim to bridge this critical gap in the existing literature by analyzing language's content and stylistic aspects such as expressed empathy, psycho-linguistic features, dialogue tags, and metrics for quantifying personalization of the utterances that can influence the engagement of an interaction. This paper demonstrates that we can predict engagement using initial customer and brand posts.

Edma de Góis

No dossiê apresentado nesta edição, o tema Direitos humanos, leitura e literatura é abordado de diferentes perspectivas, teóricas e empíricas. O que pretendemos é que, em tempos de recrudescimento de forças contra a democracia e de questionamento dos parâmetros constitucionais, a leitura literária, especializada ou não, é também dispositivo de resistência e denúncia.

Leila Lehnen

Este ensaio aborda como duas crônicas de Eliane Brum sobre o exiliados de Belo Monte narram os conflitos entre o político-econômico e o social/ecológico no Brasil contemporâneo. Através da narrativa das tensões entre o socioambiental e o político-econômico, Brum revela a precariedade do modelo democrático brasileiro, baseado, nas palavras da autora, em uma "perversão": "a de viver numa democracia formal, mas submetido a forças acima da Lei" (Brum, 2015, s.p.). Propõe-se aqui que os dois textos de Brum expõem a anatomia "disjuntiva" (Holston, 2008) da democracia brasileira não somente no âmbito dos direitos sociais, mas também em relação aos "direitos" (no sentido de direitos negativos) do meio-ambiente e das populações (humanas e não-humanas) que seriam, em teoria, os beneficiários destes direitos.

Johannes Renner, Matthias Schmidt, Daniel de las Heras

Driving an inertial many-body system out of equilibrium generates complex dynamics due to memory effects and the intricate relationships between the external driving force, internal forces, and transport effects. Understanding the underlying physics is challenging and often requires carrying out case-by-case analysis. To systematically study the interplay between all types of forces that contribute to the dynamics, a method to generate prescribed flow patterns could be of great help. We develop a custom flow method to numerically construct the external force field required to obtain the desired time evolution of an inertial many-body system, as prescribed by its one-body current and density profiles. We validate the custom flow method in a Newtonian system of purely repulsive particles by creating a slow motion dynamics of an out-of-equilibrium process and by prescribing the full time evolution between two distinct equilibrium states. The method can also be used with thermostat algorithms to control the temperature.

Maureen Cohen, Massimo A. Bollasina, Paul I. Palmer et al.

Using a three-dimensional general circulation model, we show that the atmospheric dynamics on a tidally locked Earth-like exoplanet, simulated with the planetary and orbital parameters of Proxima Centauri b, support a longitudinally asymmetric stratospheric wind oscillation (LASO), analogous to Earth's quasi-biennial oscillation (QBO). In our simulations, the LASO has a vertical extent of 35--55 km, a period of 5--6.5 months, and a peak-to-peak wind speed amplitude of -70 to +130 m/s with a maximum at an altitude of 41 km. Unlike the QBO, the LASO displays longitudinal asymmetries related to the asymmetric thermal forcing of the planet and to interactions with the resulting stationary Rossby waves. The equatorial gravity wave sources driving the LASO are localised in the deep convection region at the substellar point and in a jet exit region near the western terminator, unlike the QBO, for which these sources are distributed uniformly around the planet. Longitudinally, the western terminator experiences the highest wind speeds and undergoes reversals earlier than other longitudes. The antistellar point only experiences a weak oscillation with a very brief, low-speed westward phase. The QBO on Earth is associated with fluctuations in the abundances of water vapour and trace gases such as ozone which are also likely to occur on exoplanets if these gases are present. Strong fluctuations in temperature and the abundances of atmospheric species at the terminators will need to be considered when interpreting atmospheric observations of tidally locked exoplanets.

Yoshiaki Inoue, Liron Ravner, Michel Mandjes

This paper studies a service system in which arriving customers are provided with information about the delay they will experience. Based on this information they decide to wait for service or to leave the system. Specifically, every customer has a patience threshold and they balk if the observed delay is above the threshold. The main objective is to estimate the parameters of the customers' patience-level distribution and the corresponding potential arrival rate, using knowledge of the actual queue-length process only. The main complication, and distinguishing feature of our setup, lies in the fact that customers who decide not to join are not observed, remarkably, we manage to devise a procedure to estimate the underlying patience and arrival rate parameters. The model is a multi-server queue with a Poisson stream of customers, enabling evaluation of the corresponding likelihood function of the state-dependent effective arrival process. We establish strong consistency of the MLE and derive the asymptotic distribution of the estimation error. Several applications and extensions of the method are discussed. The performance is further assessed through a series of numerical experiments. By fitting parameters of hyperexponential and generalized-hyperexponential distributions our method provides a robust estimation framework for any continuous patience-level distribution.

Sulman Khan

World of Warcraft is a massively multiplayer online video game released on November 23, 2004, by Blizzard Entertainment. In contrast with traditional games only having a single upfront fee to play, WoW also has a monthly subscription to play the game. With customer subscriptions in mind, we can apply the use of churn prediction to not only predict whether a customer will unsubscribe from the service but explore the user's playing behavior to obtain more insight into user playing patterns. The churn problem is somewhat complex due to the nature of not having a one size fits all solution, as different services define churn in a variety of ways. In this paper, we explore a dataset that focuses on one year from January 1, 2008, until December 31, 2008, as it highlights the release of a major content update in the game. Machine learning is used in two aspects of this paper: Survival Analysis and Binary Classification. Firstly, we explore the dataset using the Kaplan Meier estimator to predict the duration until a customer churns, and lastly predict whether a person will churn in six months using traditional machine learning algorithms such as Logistic Regression, Support Vector Machine, KNN Classifier, and Random Forests. From the survival analysis results, WoW customers have a relatively long duration until churn, which solidifies the addictiveness of the game. Lastly, the binary classification performed in the best performing algorithm having a 96% ROC AUC score in predicting whether a customer will churn in six months.

Michael Schröder, Jürgen Cito

The interactive command line, also known as the shell, is a prominent mechanism used extensively by a wide range of software professionals (engineers, system administrators, data scientists, etc.). Shell customizations can therefore provide insight into the tasks they repeatedly perform, how well the standard environment supports those tasks, and ways in which the environment could be productively extended or modified. To characterize the patterns and complexities of command-line customization, we mined the collective knowledge of command-line users by analyzing more than 2.2 million shell alias definitions found on GitHub. Shell aliases allow command-line users to customize their environment by defining arbitrarily complex command substitutions. Using inductive coding methods, we found three types of aliases that each enable a number of customization practices: Shortcuts (for nicknaming commands, abbreviating subcommands, and bookmarking locations), Modifications (for substituting commands, overriding defaults, colorizing output, and elevating privilege), and Scripts (for transforming data and chaining subcommands). We conjecture that identifying common customization practices can point to particular usability issues within command-line programs, and that a deeper understanding of these practices can support researchers and tool developers in designing better user experiences. In addition to our analysis, we provide an extensive reproducibility package in the form of a curated dataset together with well-documented computational notebooks enabling further knowledge discovery and a basis for learning approaches to improve command-line workflows.

Natália Gonçalves de Souza Santos

O ensaio "Literatura e civilização em Portugal", de Álvares de Azevedo, divide a história literária portuguesa em duas fases que já vêm designadas em seu próprio título: a heroica, dedicada a Ferreira e Camões, e a negra, circunscrita a Bocage. Porém, para além do cânone já estabelecido, Azevedo faz um importante comentário, embora panorâmico, sobre aquilo que havia de mais recente no cenário literário português em torno de 1850. E, para isso, recorre aos escritos também recentes de um crítico contemporâneo, Lopes de Mendonça, e seus Ensaios de crítica e literatura (1849), coligidos de uma publicação anterior no periódico A Revolução de Setembro. A leitura feita pelo ensaísta brasileiro sinaliza, em uma geração literária cujo interesse se voltava notadamente para França e Inglaterra, a manutenção dos diálogos entre portugueses e brasileiros, mesmo após a independência política do Brasil e a pretendida ruptura proveniente dela. Assim, este artigo pretende analisar pontos de contato e dissonância entre as posições dos dois autores diante do romantismo português, a partir da leitura que Azevedo faz de Mendonça, cujo pensamento crítico foi marcado por um socialismo exacerbado e pela condenação dos excessos do ultrarromantismo.

Yiannis Dimitrakopoulos, Antonis Economou, Stefanos Leonardos

Strategic customer behavior is strongly influenced by the level of information that is provided to customers. Hence, to optimize the design of queueing systems, many studies consider various versions of the same service model and compare them under different information structures. In particular, two extreme versions are usually considered and compared: the observable in which customers are informed about the number of customers in the system and the unobservable in which they are only informed about the system parameters, e.g., arrival and service rates. In the present work, we study a model that bridges these two versions. More concretely, we assume that the system alternates between observable and unobservable periods. We characterize and compute customer equilibrium joining/balking strategies and show that the present model unifies and extends existing approaches of both heterogeneously observable models and models with delayed observations. More importantly, our findings indicate that an alternating information structure implies in general higher equilibrium throughput and social welfare in comparison to both the observable and unobservable cases. We complement our results with numerical experiments and provide managerial insight on the optimal control of the system parameters.

Budimansyah Suwardi Suwardi

Talaga Rena Mahawijaya dan Bukit Badigul yang dibangun oleh Sribaduga Maharaja pada abad ke-16, merupakan danau buatan yang diperuntukkan sebagai tempat upacara srada. Namun jika dilihat dari sudut pandang yang berbeda, danau buatan ini memiliki banyak fungsi yang dampak positifnya sangat besar terhadap kesejahteraan masyarakat. Untuk meneliti dan mengkaji permasalahan ini harus ditinjau secara mendalam dan memerlukan analisis yang kuat, maka metode sejarah yang terdiri atas heuristik, kritik, interpretasi dan historiografi akan digunakan oleh penulis. Selain metode sejarah, teori-teori dan konsep ilmu-ilmu keteknikan akan digunakan pula sebagai pisau analisis, agar menghasilkan simpulan yang cukup kuat dan mendalam. Penelitian yang telah dilakukan oleh penulis, Talaga Rena Mahawijaya mempunyai fungsi utama sebagai area tangkapan air, yang kita kenal sebagai waduk atau embung, yaitu sebuah danau yang sengaja dibuat untuk memecah volume aliran air yang sangat besar, juga berfungsi sebagai cadangan air ketika musim kemarau. Simpulannya, Sribaduga Maharaja membuat Talaga Rena Mahawijaya untuk fungsi water catchment, water treatment, dan water supply.   Talaga Rena Mahawijaya and Bukit Badigul built by Sribaduga Maharaja in the 16th century, are artificial lakes designated as srada ceremonies. But when viewed from a different perspective, this artificial lake has many functions that have a very large positive impact on people's welfare. To investigate and examine these problems, the in depth and strong analysis is required. Thus, the historical method consisting of heuristics, criticism, interpretation and historiography are used by the author. In addition to historical methods, theories and concepts of engineering sciences are also used as analytical tools in order to produce the strong and deep conclusions. From this research, Talaga Rena Mahawijaya has a main function as a water catchment area, known as a reservoir or embung. It is a lake intentionally made to break down a very large volume of water, also serves as a water reserve during the dry season. In conclusion, Sribaduga Maharaja made Talaga Rena Mahawijaya as the water catchment, water treatment, and water supply.