Miracle-dz/UniFAR-FTUs huggingface dataset:
The Dynamics of Family Systems: Lessons from Past and Present Times

The present paper surveys significant research dealing with some neglected roles of the family and its dynamics in the presence of changes in the economic environment. Attention is thus directed to the response of family systems to changes in resource endowments, outside economic opportunities, the development of markets, and surrounding institutions. Two other original features of our investigation deserve to be emphasized. First, unlike what is generally done in economics, we extensively draw from scholarly works of social scientists, family historians in particular. Second, in order to shed light on family dynamics in present-day developing countries, we assess the state of knowledge about the transformation of family patterns in Europe during a long period stretching back to the early Middle Ages and even earlier.
Antecedents and consequences of brand prestige of package tour in the senior tourism industry

ABSTRACT This study investigated how to form brand prestige of package tour in the senior tourism industry. A conceptual model was developed and tested using data collected from a sample of 331 senior tourists in Korea. The results indicated that four types of tour service performances (i.e. tourist attractions, tour guide services, food services, and accommodations) aid to enhance package tour prestige. It was also found that package tour prestige has a positive influence on well-being perception, which further positively affects brand attachment and brand loyalty. Furthermore, status consumption moderates the relationship between package tour prestige and well-being perception.
AUTOMATIC EXTRACTION OF A NAVIGATION GRAPH INTENDED FOR INDOORGML FROM AN INDOOR POINT CLOUD

Abstract. Indoor environments tend to be more complex and more populated when buildings are accessible to the public. The need for knowing where people are, how they can get somewhere or how to reach them in these buildings is thus equally increasing. In this research point clouds are used, obtained by dynamic laser scanning of a building, since we cannot rely on architectural drawings for maps and paths, which can be outdated. The presented method focuses on the creation of an indoor navigation graph, based on IndoorGML structure, in a fast and automated way, while retaining the type of walkable surface. In this paper the focus has been on door detection, because doors are essential elements in an indoor environment, seeing that they connect spaces and are a logical step in a route. This paper describes a way to detect doors using 3D Medial Axis Transform (MAT) combined with the intelligence stored in the path of a mobile laser scanner, showing good first results. Additionally different spaces (e.g. rooms and corridors) in the building are identified and slopes and stairs in walkable spaces are detected. This results in a navigation graph which can be stored in an IndoorGML structure.
Context-rich Urban Analysis Using Machine Learning A case study in Pittsburgh, PA

This paper reports on the analytical potential of machine learning methods for urban analysis. It documents a new method for data-driven urban analysis based on diagrammatic images describing each building in a city in relation to its immediate urban context. By statistically analyzing architectural and contextual features in this new dataset, the method can identify clusters of similar urban conditions and produce a detailed picture of a city's morphological structure. Remapping the clusters from data to 2D space, our method enables a new kind of urban plan that displays gradients of urban similarity. Taking Pittsburgh as a case study we demonstrate this method, and propose "morphological types" as a new category of urban analysis describing a given city's specific set of distinct morphological conditions. The paper concludes with a discussion of the implications of this method and its limitations, as well as its potentials for architecture, urban studies, and computation.
State owned enterprises and capital misallocation in Vietnam

Abstract This study uses the first comprehensive data on Vietnamese manufacturing firms and quantifies the allocative efficiency improvement due to massive entry of private firms amid a simultaneous contraction of state-owned enterprises (SOEs) in the period 2000–2008. It finds that allocative efficiency improvement contributes considerably to the sector’s annual Total Factor Productivity growth, and firm’s entry and exit exerts an increasingly important role in the second half of this period. The productivity dispersion within narrowly-defined industries remains, however, large and persistent. Such effect is attributed to the fact that SOEs disproportionately absorb credit in a period marked with unprecedented growth in domestic credit supply. This paper finds that commercial and subsidized credit per se exhibits a capital distortion reducing effect, but awarding more commercial and subsidized credit to the SOEs, in reference to the private counterparts, yields the anti-capital distortion reducing effect that intensifies with the distribution of higher quantiles.
How CEO Wealth Affects the Riskiness of a Firm

The objective of this paper is to analyze the relationship between the ownership level of managers and the risk averse behavior of the firm. We measure the ownership level of the managers by the ratio of their ownership of the company relative to their total wealth for a sample of 69 individuals from the Forbes 400 list of the wealthiest individuals in the world for the period from 2001-11 using an unbalanced panel data analysis. The dependent variable is the Altman Z-score of each firm and we further test these relationships using financial leverage. The independent variables are delta and Vega of the option portfolio of the manager, R&D for the firm, total assets, the age of the manager, the tenure of the manager, stock holding of the manager, CEO/Chair duality of the manager and firma age. The Z-score is statistically significantly related to size, CEO age, CEO wealth, and duality. Financial leverage is not statistically significantly related to any of the independent variables.
The use of genetic testing in insurance

Use of the genetic testing results by insurance companies for underwriting process has been a research topic for this paper. Defined that modern scientific developments give the opportunity for the insurance companies to implement genetic test as a new underwriting method. One of the biggest problem here is related to find the ways of genetic discrimination. Determined that main genetic tests realize for the Huntington’s disease, BRCA 1, BRCA 2, Myotonic dystrophy, Polyposis coli, Multiple endocrine neoplasia, Hereditary motor and sensory neuropathy, Monogenic form of Alzheimer’s disease.
Polyhedral Dataflow Graphs

This research presents an intermediate compiler representation that is designed for optimization, and emphasizes the temporary storage requirements and execution schedule of a given computation to guide optimization decisions. The representation is expressed as a dataflow graph that describes computational statements and data mappings within the polyhedral compilation model. The targeted applications include both the regular and irregular scientific domains. The intermediate representation can be integrated into existing compiler infrastructures. A specification language implemented as a domain specific language in C++ describes the graph components and the transformations that can be applied. The visual representation allows users to reason about optimizations. Graph variants can be translated into source code or other representation. The language, intermediate representation, and associated transformations have been applied to improve the performance of differential equation solvers, or sparse matrix operations, tensor decomposition, and structured multigrid methods.
Comparaison d’une approche miroir et d’une approche distributionnelle pour l’extraction de mots sémantiquement reliés (Comparing a mirror approach and a distributional approach for extracting semantically related words)

Dans (Muller & Langlais, 2010), nous avons comparé une approche distributionnelle et une variante de l’approche miroir proposée par Dyvik (2002) sur une tâche d’extraction de synonymes à partir d’un corpus en français. Nous présentons ici une analyse plus fine des relations extraites automatiquement en nous intéressant cette fois-ci à la langue anglaise pour laquelle de plus amples ressources sont disponibles. Différentes façons d’évaluer notre approche corroborent le fait que l’approche miroir se comporte globalement mieux que l’approche distributionnelle décrite dans (Lin, 1998), une approche de référence dans le domaine.
Race Matters in Coaching: An Examination of Coaches’ Willingness to Have Difficult Conversations with Leaders of Color

Race Matters in Coaching: An Examination of Coaches’ Willingness to Have Difficult Conversations with Leaders of Color Ariel Finch Bernstein Do executive coaches have the skill sets necessary for effective partnership with an increasingly diverse workforce? Such inquiry remains unexamined, yet research from similar disciplines casts doubt. Drawing on these findings, a between-subject experiment sampled 129 coaches and examined their willingness to have “difficult conversations” with Black clients. The study investigated two questions in particular: (1) Do coaches provide less critical feedback to Black clients than they do White clients? and (2) Do coaches engage in fewer diversity-based conversations with Black clients than with White clients? The study found that as hypothesized, Black clients received more support, yet less challenge, less constructive feedback, and less time devoted to areas of development than did otherwise identical White clients. Coaches were also twice as likely to provide diversity-related feedback to White executives than they were to Black executives. Put simply, coaches assigned to Black clients chose to sidestep conversations about diversity and development. Substantial implications hold for practitioners, clients, and the greater coaching community. Findings suggested that coaches’ reluctance to provide challenging crossracial feedback may stem from concern about appearing prejudiced. The result is that leaders of color who receive coaching may be robbed of developmental opportunities offered to White organizational leaders. Thus, the impact of racial dynamics should receive greater attention from U.S.-based coaching certification programs. In particular, institutes should consider mandating coaching supervision as well as incorporating diversity intelligence within their list of core competencies.
A Sequential Action Generation Framework for Intelligent Agents in Cyberspace

Intelligent agents learn their behaviors in games or crowd simulations for diverse behaviors. Given that iterative learning is required to generate behaviors by learning, programming by demonstration (PbD) can be applied to such intelligent agents for reducing learning time. One line of research has focused on how to define portions of sequential actions executed by a predecessor as building blocks of sequential actions to be executed by an intelligent agent. These studies face the following problems: first, the approach to divide collected actions using the variance of actions in consecutive order cannot derive consecutive actions in various ways; and second, the approach deriving consecutive actions in all cases increases the amount of calculation depending on the number of actions. This paper proposes a behavior generation framework that includes functions to reduce the amount of computation to generate a set of behaviors for an intelligent agent. In an experiment applying the framework to a driving simulation, the number of movements was reduced to 24% by filtering movements. In addition, the generated behaviors were reduced to 23% by quantization and filtering. Thus, the amount of calculation required to generate the behaviors was reduced.
USERS’ EXPERIENCE IN ROLE-PLAYING GAME: MEASURING THE PLAYER’S GAMEPLAY EXPERIENCE

This study is related to the users’ gaming experience which is gained through a set of users’ activities to play computer games. The activities are designed based on the features of games that are desired by the users. As a result, the RPG computer games have been designed and user gaming experience via questionnaire has been tested. There are seven constructs measuring the immersive, flow, competence, tension, challenge, positive affect and negative affect. The results showed the constructs that lead to positive values is indicated by the mean value for the user’s gaming experience is very good, and vice versa for the mean construct geared negative value
Calibrationless Oscar-Based Image Reconstruction in Compressed Sensing Parallel MRI

Reducing acquisition time is a crucial issue in MRI especially in the high resolution context. Compressed sensing has faced this problem for a decade. However, to maintain a high signal-to-noise ratio (SNR), CS must be combined with parallel imaging. This leads to harder reconstruction problems that usually require the knowledge of coil sensitivity profiles. In this work, we introduce a calibrationless image reconstruction approach that no longer requires this knowledge. The originality of this work lies in using for reconstruction a group sparsity structure (called OSCAR) across channels that handles SNR inhomogeneities across receivers. We compare this re-construction with other calibrationless approaches based on group-LASSO and its sparse variation as well as with the auto-calibrated method called $\ell_{1}$-ESPIRiT. We demonstrate that OSCAR outperforms its competitors and provides similar results to $\ell_{1}$-ESPIRiT. This suggests that the sensitivity maps are no longer required to per-form combined CS and parallel imaging reconstruction.
An Analytical Framework for Power Quality Monitoring in Enterprise-level Power Grid

Due to the high measuring cost, the monitoring of power quality is non-trivial. This work is aimed at reducing the cost of power quality monitoring in power networks. Using a real-world power quality dataset, this work adopts a learn-from-data approach to obtain a device latent feature model, which captures the device behavior as a power quality transition function. With the latent feature model, the power network could be modeled, in analogy, as a data-driven network, which presents the opportunity to use the well-investigated network monitoring and data estimation algorithms to solve the network quality monitoring problem in power grid. Based on this network model, algorithms are proposed to: 1) intelligently place measurement devices on suitable power links to reduce the uncertainty of power quality estimation on unmonitored power links, 2) estimate the power quality in unmonitored segments of a power network, using only a small number of measurement points, and 3) identify a potential malfunction device in the network. The meter placement algorithms use entropy-based measurements and Bayesian network models to identify the most suitable power links for power quality meter placement. Evaluation results on various simulated networks including IEEE distribution test feeder system show that the meter placement solution is efficient, and has the potential to significantly reduce the uncertainty of power quality values on
Effective parallel computation on workstation cluster with a user-level communication network

Leveraging the engineering effort in the microprocessor sector, massively parallel processing (MPP) systems have emerged as the leading supercomputing architecture in terms of price and performance. By using commercial workstations as processing nodes to further reduce engineering costs, workstation-based MPP systems promise to deliver truly affordable supercomputing performance. However, existing workstationbased parallel systems are confined to coarse-grained parallelization because of the large overhead of interprocessor communication over existing local area networks. To address this problem, this thesis proposes to augment a conventional LAN-connected workstation cluster with a Fast User-level Network (FUNet). Based on MIT's Arctic technology, FUNet provides a packet-switched routing network with an acknowledgment/retry end-to-end flow control protocol. A hardware Fast User-level Network Interface (FUNi) provides access to FUNet for both message passing and remote direct-memory-access (DMA) block transfer between parallel peer processes. The FUNi hardware mechanisms allow direct low-overhead user-level access to FUNet while maintaining secure and transparent sharing of FUNet among multiple parallel applications. FUNi can be realized as SBus peripheral cards to allow compatibility with a variety of workstation platforms. It takes advantage of SBus's Direct Virtual Memory Access (DVMA) to circumvent performance limitations imposed by existing workstation and microprocessor designs. Simulation results have shown that FUNet with FUNi, when coupled with latency-hiding software techniques, is effective in supporting fine-grained parallel processing on a workstation cluster. Thesis Supervisor: Gregory M. Papadopoulos Title: Associate Professor of Electrical Engineering and Computer Science
Improved 7-DOF Control of ISS Robotic Manipulators

Canada’s contribution to the International Space Station (ISS) is the Mobile Servicing System (MSS). Its first component, the 7-degree-of-feedom (7-DOF) robotic manipulator Canadarm2 has been used for ISS assembly since 2001, extracting and installing new components from the space shuttle. In mission planning, the robotics trajectories for assembly operations are extensively analyzed, with particular concern for proximity to structure. Even with prepared trajectories, however, there can be unexpected deviations, resulting from unplanned events, or the use of seven joints. Due to the extra (7th) DOF in Canadarm2, any tip pose (position and orientation) has an infinite number of joint solutions, (since only 6DOF are needed to resolve the position and orientation in space). In Canadarm2, this redundancy allows for a special maneuver called the Pitch Plane Change, where the tip maintains its pose, while the arm plane is rotated. Mission planners take advantage of the Pitch Plane Change feature by repositioning the arm to maximize distance from structure. For 7-DOF Manual-mode flying, when the tip is commanded in Cartesian space, Canadarm2 computes the joint trajectory based on the Pseudo-Inverse algorithm, which uses a “minimum-energy” criterion to resolve the kinematic redundancy. The disadvantage with this control algorithm is that the final joint solution depends on the input hand-controller profile, which is never identical for two operators. This lack of determinism is a safety concern, because unplanned arm trajectories can result in collision with structure. As a result, mission planning community has decided to always fly Canadarm2 with one joint locked during Manual operations. With this approach, it becomes a 6-DOF manipulator, and a unique joint solution exists for a given tip pose. This approach is acceptable for robotics assembly tasks, but problems remain with unscripted tasks, such as robot-assisted extravehicular activities (EVA), where an astronaut at the arm tip indicates the required motion. In fact, restricting Canadarm2 to 6-DOF during EVA tasks can cause the arm to swing worse than with 7-DOF control, creating more dangerous situations. This paper presents an alternate 7-DOF control strategy, which maintains both determinism and flexibility, for increased safety. In this solution, we resolve the kinematic redundancy, not by minimum-energy, but by simultaneously maintaining the arm’s Pitch Plane as the tip is commanded in free space. With this method, we control the arm configuration and minimize dangerous elbow swing, without sacrificing any determinism, all of which contributes to a safer operational environment. In this paper, we will present the circumstances leading to our search for improved 7-DOF control, as well as our implementation, testing and analysis of the Pitch Plane Control solution in the specific case of Canadarm2, using the real-time MSS Operations and Training Simulator (MOTS). In conclusion, we will extrapolate other 7-DOF solutions that could further improve collision avoidance management in Canadarm2 and in Dextre, the next MSS robotics component.
Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences

Nowadays, a hot challenge for supermarket chains is to offer personalized services to their customers. Market basket prediction, i.e., supplying the customer a shopping list for the next purchase according to her current needs, is one of these services. Current approaches are not capable of capturing at the same time the different factors influencing the customer's decision process: co-occurrence, sequentuality, periodicity, and recurrency of the purchased items. To this aim, we define a pattern Temporal Annotated Recurring Sequence (TARS) able to capture simultaneously and adaptively all these factors. We define the method to extract TARS and develop a predictor for next basket named TBP (TARS Based Predictor) that, on top of TARS, is able to understand the level of the customer's stocks and recommend the set of most necessary items. By adopting the TBP the supermarket chains could crop tailored suggestions for each individual customer which in turn could effectively speed up their shopping sessions. A deep experimentation shows that TARS are able to explain the customer purchase behavior, and that TBP outperforms the state-of-the-art competitors.
Green Marketing Mix as Strategy to Improve Competitive Advantage in Real Estate Developer Companies

This study examines the relationships among environmental orientation, green marketing mix strategy, and competitive advantage. Data collected from 72 real estate developer companies in East Java, Indonesia. The results indicated that environmental orientation has no positively influence on enhancing firm’s competitive advantage, but it has positive and significantly effect to the implementation of green marketing mix strategy. Moreover, green marketing mix strategy is revealed as an excellent strategy to enhance competitive advantage in term of company’s green image. These findings provide real estate developer company with useful insights for improving firm competitive advantage through implementation of green marketing mix strategy which strongly environmental orientation adopted.