Miracle-dz/UniFAR-FTUs huggingface dataset:
Sharing diseconomy: impact of the subsidy war of ride-sharing companies on urban congestion

ABSTRACT As a typical example of the sharing economy, ride-sharing, in theory, can improve market efficiency and enhance the welfare of consumers and service suppliers. However, negative externalities resulted from ride-sharing, such as quasi-public goods, are often overlooked. In this paper, we used AutoNavi’s big data to measure traffic congestion in cities, and built DID, PSM-DID and DDD models to analyse the impact of the subsidy war among ride-sharing companies on the traffic congestion in Shanghai. The subsidy war led to an increase in the congestion index of Shanghai by 0.068–0.077, which was equivalent to an increase in transit time by 3.51%–5.53%. Excessive subsidies offered by ride-sharing companies to vie for market share will eventually distort the market. As a result, increased social costs will ultimately harm the well-being of the entire society, leading to diseconomy.
Apprentissage de la qualité de service dans les réseaux multiservices : applications au routage optimal sous contraintes

La cohabitation de plusieurs services differents sur un meme reseau souleve de nombreux problemes pour la gestion et la conception de reseau de telecommunication. L'introduction de mecanismes "intelligents " dans les reseaux multiservices permet de surmonter la difficulte de mettre en place des methodes plus traditionnelles pour prendre en compte toute la complexite generee par la multiplication des services. Dans ce contexte, nous nous interessons au probleme de l'evaluation de performance dans les reseaux a l'etat stationnaire, et plus specifiquement l'evaluation des criteres de qualite de service (QoS). Au lieu d'essayer de modeliser tous les mecanismes d'un routeur pour formaliser certains criteres de QoS, nous proposons d'utiliser les capacites d'apprentissage et de generalisation des reseaux de neurones pour apprendre cette QoS a partir d'observations du systeme. Nous proposons ainsi des modeles neuro-mimetiques de differents criteres de la QoS d'un noeud du reseau qui s'appuient sur une description statistique relativement simple des trafics incidents. Nous avons etudie l'apprentissage de plusieurs criteres de qualite de service a partir de simulations a evenements discrets dans le cas de files d'attente elementaires et de files d'attente a serveur partage qui modelisent la differentiation de services dans les routeurs IP ou MPLS. Nous generalisons ensuite cette approche pour effectuer l'estimation de la QoS le long d'un chemin et proposons pour cela une cooperation distribuee de modeles neuronaux. Les reseaux de neurones sont charges d'estimer a la fois les criteres de qualite de service et une description du trafic de sortie. Ce schema couple a un protocole de type RSVP permettrait a terme de propager les estimations le long du chemin pour etablir une estimation de la QoS de bout en bout. Nous nous interessons enfin au probleme de routage optimal sous contraintes de QoS de bout en bout. Nous presentons une formalisation multiflot permettant de mettre en place une strategie de resolution de type deviation de flot qui s'appuie sur une approche de type lagrangien augmente pour relâcher les contraintes de QoS. Cette strategie permet d'obtenir un optimum local realisable. Nous proposons ensuite de remplacer l'approximation M/M/1 traditionnellement utilisee dans les modeles de multiflot par un modele par reseaux de neurones de la QoS, plus realiste notamment dans le cas de la differentiation de service. Toutefois il est necessaire de garantir la croissance des fonctions evaluations pour assurer la validite du schema d'optimisation. Cette monotonie peut etre imposee lors de l'apprentissage du modele neuronal par l'ajout de contraintes sur les derivees premieres. Nous avons developpe ainsi un algorithme d'apprentissage sous contraintes qui impose la monotonie dans les reseaux de neurones feed-forward en utilisant des methodes classiques de l'optimisation nonlineaire sous contraintes.
Digital transformation: harnessing digital technologies for the next generation of services

Purpose The purpose of this paper is to discuss digital transformation and its four trajectories – digital technology, digital strategy, customer experience and data-driven business models – that could shape the next generation of services. This includes a discussion on whether both the market and organizations are all ready for the digital change and what are the opportunities that will enable firms to create and capture value though new business models. Design/methodology/approach Providing services is a proven and effective way to secure a competitive position, deliver long-term stable revenues and open up new market opportunities. However, it is also clear that some organisations are struggling to digitally transform. Therefore, the commentary provides a brief insight into how firms explore the possibilities of digital transformation and navigate these uncharted waters. Findings Today’s digital technologies affect the organisation outside and in, enabling the creation of new business models and transforming the customer experience. The incumbents are acutely aware that they need to transform strategically – to build new networks and value chains. Originality/value This commentary extends earlier work exploring the digital disruption within services to highlight a number of connected areas: the challenges and opportunities of digital transformation at a strategic level, as well as understanding and enhancing the customer experience and seeing how new data-driven business models can underpin service transformation.
RLAR:Adaptive routing algorithm based onreinforcement learning

Aimed at the poor performance of the current various routing algorithms,due to the poor adaptability to various changing net-work topologies and loads,an adaptive routing algorithm called RLAR is proposed,and the algorithm is based on reinforcement learning which implemented by gradient ascent algorithm.Reinforcement learning means learning a policy that a mapping of states into actions which based on feedback from the environment.The learning can be viewed as browsing a set of policies while evaluating them by trial through interaction with the environment.Applying the reinforcement learning strategy to the research of routing,as a novel method,the theory is proved.The performance of RLAR and other routing methods is comprehensively compared,lots of simulation results show that RLAR can remarkably enhance the performance of network routing.
Multi-tags anti-colision algorithms in RFID system

In order to improve the effciency of single reader under multi-tags RFID system,a hybrid algorithm is proposed to use in a particular condition which tags number have the same prefix.In the first step of this algorithm,the Adaptive Slot-Count(Q)algorithm is used to adjust the frame size to approach the number of tags to achieve maximum efficiency and divide the collision tags into group.In the second step,the Query Tree with Reversed IDs(QTR)is used to identify collision tags grouop by group.According to EPC C1G1 Standrad,in the single reader and mulit-tags system enviroment,simulation is carried out with the size of tag number of 96 in two cases:complete random and same prefix of tag number.Result show when the tags number has a same prefix,compared to QT and Q algorithm,the hybrid algorithm could improve the throught rate and reduce the number of slots.
Non-GAAP Reporting: Evidence from Academia and Current Practice

The SEC, FASB, and IASB have expressed interest in the recent proliferation of non-GAAP reporting, raising questions about what this increasing reporting trend means for IFRS- and GAAP-based reporting. Our goal is (1) to inform standard setters and regulators about the current state of non-GAAP reporting and (2) explore how the discretion afforded in non-GAAP reporting influences earnings consistency and comparability, two tenets of IFRS- and GAAP-based earnings. We begin by providing an up-to-date discussion of the most common questions examined in the extant literature to provide insights on what academics have learned to date about non-GAAP reporting. Next, we utilize a novel dataset of detailed non-GAAP disclosures to provide in-depth descriptive evidence on the current state of non-GAAP reporting. We find that the frequency of non-GAAP reporting has increased by 35% in recent years, a trend that we find in every sector. We also provide evidence on how the frequency and magnitude of specific exclusions has changed over time. Of particular interest is the increasing frequency with which firms exclude items that are not commonly excluded by other firms, indicating that more idiosyncratic definitions of non-GAAP earnings are emerging in the marketplace. Finally, we examine how discretion in non-GAAP reporting affects earnings consistency and comparability. We find that the consistency with which firms exclude specific items varies across exclusion types. Importantly, we also find some evidence that inconsistent non-GAAP reporting is associated with lower quality non-GAAP metrics. In examining across-firm comparability, we find descriptive evidence indicating that within-sector performance rankings based on GAAP earnings better explains concurrent stock returns than comparisons based on non-GAAP earnings. However, our preliminary analyses indicate that these differences are not statistically significant.
The ePortfolio: constructing learning in translation technology

ABSTRACT The use of ePortfolios in higher education has experienced a rise with multiple experiences reported in different areas where student-centred methodologies are key. While these are not new in translator training, ePortfolios are still underused in this area, even if they provide an excellent framework for constructivist methodologies. In this article, I explain how ePortfolios are used in a course on translation technology with a view to implementing a learner-centred scenario. This is a course I have been teaching for some years, which has experienced, over time, a movement from traditional transmissionist techniques, where the teacher is the ‘possessor and distributor of knowledge’ to a transformationist position, as I realised that, in order for the course to be effective, students needed some form of empowerment and a more active role in their learning process. This article discusses the advantages of using ePortfolios for the learning of translation technology. It presents an experience in implementing a learning scenario based on the ePortfolio – course competences, content, resources and assessment – as a proposal for instructors wishing to adopt a similar approach. The article will end with a discussion on how these teaching practices relate to the principles of socio-constructivism.
What Engineers Know And How They Know It

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Performance Evaluation of Channel Propagation Models and Developed Model for Mobile Communication

Propagation models represent a solidifying of mathematical equations and algorithms that are used for radio signal propagation prediction in specific regions. In this research different propagation models are analyzed and compared. These propagation models have been proposed at the operating frequency of 3.8 GHz for different transmitter antenna heights in all types of terrain. These propagation models depend on location, frequency range and clutter type such as urban, suburban and countryside. We have to bear in mind that the results of the path loss estimation of Free Space model are identical and equal to (119 dB) for 18 m and 34 m transmitter antenna heights at 3.8 GHz in urban environment. It is obvious that Egli model shows the highest path loss values in rural environment as compared with the other models. By the end of this paper, a developed empirical radio propagation model is proposed to be appropriate in urban and rural environments.
State estimation of a cheetah spine and tail using an inertial sensor network

The cheetah (Acinonyx jubatus) is by far the most manoeuvrable and agile terrestrial animal [1]. Little is known, in terms of biomechanics, about how it achieves these incredible feats of manoeuvrability [2]. The transient motions of the cheetah all involve rapid flicking of its tail and flexing of its spine [3]. The aim of the research was to develop tools (hardware and software) that can be used to gain a better understanding of the cheetah tail and spine by capturing its motion. A mechanical rig was used to simulate the tail and spine motion. This insight may inspire and aid in the design of bio-inspired robotic platforms. A previous assumption was that the tail is heavy and acts as a counter balance or rudder [4] [5] [6] [7] [8], yet this was never tested. Contrary to this assumption, necropsy results determined that the tail was in fact light with a relatively low inertia value. Fur from the tail was used in wind tunnel experiments to determine the drag coefficient of a cheetah tail. No researchers have actively sought to track the motion of a cheetah’s spine and tail during rapid manoeuvres via placing multiple sensors on a cheetah. This requires the development of a 3D dynamic model of the spine and tail to accurately study the motion of the cheetah. A wireless sensor network was built and three different filters and state estimation algorithms were designed and validated with a mechanical rig and camera system. The sensor network consists of three sensors on the tail (base, middle and tip) as well as a hypothetical collar sensor (GPS and WiFi were not implemented). The raw sensor data was filtered using the kinematic and kinetic equations generated using Lagrange Dynamics by modelling the spine and tail as a system of interconnected rigid beams. The filters are in the form of the Extended Kalman Filter (EKF) and simulated in Matlab using a combination of analytical and numeric methods. The filters are advanced to include the torque generated by the tail on the body. This required modelling the drag effect of the cheetah’s tail. To conclude the research, initial investigation into a single beam tail as well as a position estimator were conducted. A single beam tail model results in fewer sensors being placed onto the cheetah and the position estimator enables the filter and state estimation algorithms to go from a stationary rig to a moving cheetah. ii
The Major Effects of BASEL II to Small and Mid-Sized Enterprises: An Empirical Work on Companies Quoted to KOSGEB

The major aim of this work is to analyze the effects of BASEL II regulations on the small and mid-sized enterprises (SME) in Turkey. It is accepted that there are still various shortcomings of BASEL II implementation regarding the corporate governance (CG) and regulations in Turkish economy. The companies which are classi ﬁ ed as SME and quoted to KOSGEB, i.e. a governmental organization supporting SMEs, are used in the empirical work. The empirical ﬁ ndings are discussed and compared with the major ﬁ ndings from other countries in the literature and also recommen-dations are made regarding BASEL II implementation and its effects on corporate governance and economic growth in Turkey.
Rebuilding a global brand under crisis – case of a global brand Maggi

Purpose The purpose of this paper is to study whether the controversy because of brand crisis based on quality had any impact on consumer brand equity, brand image, brand reliability, brand perception of quality, perceived value, brand sentiments and purchase behavior. Design/methodology/approach The research methodology consisted of two types of data: primary and secondary data. The secondary research consisted of social media brand sentiments and financial analysis. The primary research focused on perception study of brand quality, consumer brand equity, brand reliability, brand image, purchase and brand switch behavior. Findings Maggi used social media extensively to address the issue and re-build the brand reliability and confidence among its users. Communication strategy adopted by focusing on the past experience of consumers and using them as a spokesperson generated a positive sentiment towards the brand under crisis. Research limitations/implications While Maggi suffered the backlash because of the controversy across the length and breadth of India and was banned in a number of states, the author could conduct the primary research only in one city of the state of Maharashtra, Mumbai. The effectiveness of the survey was impacted because of the geographic limitations the author faced while collecting the responses. The survey would have definitely been more effective, with responses collected from different states and with more number of respondents. Fishbein is very old, from the 1980s, even though this theory has met the test of time. Application of the effect of experiences on experiential perceptions and how this influences value through networking could have been used to explain the same. Practical implications An important implication of this paper’s findings for practice, therefore, is that brands should incessantly strive to maintain the consumers’ level of trust, as it is essential for the preservation of the brand equity after a crisis. Crisis-stricken brands should safeguard their reputations from the negative effects of crises. It is even more important for any brand to act appropriately when the cause of the crisis is attributed to its actions and processes. Managers have to address the quality of products in case of brand crisis for restoring trust, image and reliability in the brand. Right type of communication to right targeted consumers will help in the restoration of the image, trust on the brand and bring back loyal customers. Managers have to build brand equity on a regular basis, as a strong brand can recover faster as seen from this paper. Originality/value This paper helps to upgrade the knowledge and understanding of the impact of the controversy on brand equity and image and how the crisis management strategy can be adopted to regain the mind share and equity. This paper will help the brands in the future to know how a crisis can be managed efficiently by drawing a cue from the strategies implemented by Maggi.
Multi Aspect Based Document LevelSentiment Analysis for Educational InstituteAnalysis

Sentiment Analysis is used to determine the attitude of a writer with respect to some topic or the overall contextual polarity of a document. The objective of our project is to build an interactive portal wherein the comparative analysis of various colleges can be visualized. In doing so ,instead of the basic factual information, analysis will be done based on the feedback and reviews acquired from various sources. In this approach , document level sentiment analysis will be done considering every aspect of the same using the techniques of natural language processing
A Study on the Compression of Voxel Simulation Results Using Tensor Decomposition

With the ever-growing trend of globalization, product design is often conducted collaboratively among several divisions, thus making it a huge challenge to transfer large CAE (Computer Aided Engineering) data between different locations. Our goal is to reduce the size of transfer data so that fast data transfer can be realized even when the network speed is slow. In this study, we have developed a data compression method based on TD (Tensor Decomposition). In this method, voxel simulation results data are represented as tensors and tensor decomposition based on HOOI (Higher-Order Orthogonal Iteration) algorithm is applied to the tensors. After tensor decompression, the original tensor is decomposed into a core tensor and a series of basis matrices, whose summed size is considerably smaller than that of the original tensor. As a result, a compression ratio of over 60:1 is achieved for steady flow simulation results data and the error is below 5%. A compression ratio of over 70:1 is achieved for unsteady flow simulation results data and the error is below 5%. We have confirmed that at 5% error, no significant information is lost during the data compression process. Tensor decomposition has been applied for image data compression, dimensionality reduction, and more recently for the compression of hexahedral mesh-based simulation result database. However, it is a first application of tensor decomposition to the data compression of voxel-based simulation results.
A Conceptual Study on Contingent Impact of External Integration on Innovation Sme Business Success Relationship

It is widely acknowledged in the existing studies that innovation has the critical role in firms’ performances. Moreover, it has been acknowledged that innovative activities are the main sources of growth, survivability, and success for SMEs firms. In the setting of entrepreneurship, earlier studies have claimed that innovation is the integrated element of entrepreneurship. However, the existing studies have also revealed inconsistent findings regarding the impacts of innovation on firm’s performances under various contexts. Thus, this study claims that there should be a moderator to facilitate the relationship between innovations and firm’s performances. Therefore, this study has introduced the external integration as a moderator to improve the relationship between types of innovations and firm’s performances. The main objective of the study is to identify the relationship between various types of innovations including process innovation, product innovation, marketing innovation, and organizational innovations and business success operationalized with four dimensions including perceived financial performance, perceived non-financial performance, perceived business growth, and perceived performance relative to competitors) under the moderating role of external integration. Three theories namely Strategic Contingency Theory (SCT), Resource Dependence Theory (RDT), and Resource Based View (RBV) have been integrated to develop the proposed theoretical framework. The recent literature has been taken to gather the information about the variables that helped current study to develop a theoretical frame work and then eight propositions have been developed based on proposed theoretical framework. The external integration as a moderator between innovations and business success is the main theoretical contribution of this study. Furthermore, limitations have been stated at the end and recommendations have been made for future research.