Miracle-dz/UniFAR-FTUs huggingface dataset:
Free Vibration of Thin-Walled Cylindrical Shells

A method is presented for calculating the free vibr ations of an isentropic thin-walled circular cylindrical s hell with different boundary conditions. The method is b ased on Love’s theory of shells. An experimental study w as conducted on a circular cylindrical shell with simp ly supported boundary conditions. The objective was to evaluate the validity of the theory. To investigate the effects of a shell’s dimension and boundary conditi ons on its natural frequencies, various models were stu died. Shells with different lengths and radius/thickness ratios were compared. Moreover, shells with simply supported and clamped boundary conditions were modeled and analyzed. By comparing such varying terms interesti ng results were obtained, especially from designing po int of view.
Summary Maps for Lifelong Visual Localization

Robots that use vision for localization need to handle environments that are subject to seasonal and structural change, and operate under changing lighting and weather conditions. We present a framework for lifelong localization and mapping designed to provide robust and metrically accurate online localization in these kinds of changing environments. Our system iterates between offline map building, map summary, and online localization. The offline mapping fuses data from multiple visually varied datasets, thus dealing with changing environments by incorporating new information. Before passing these data to the online localization system, the map is summarized, selecting only the landmarks that are deemed useful for localization. This Summary Map enables online localization that is accurate and robust to the variation of visual information in natural environments while still being computationally efficient. We present a number of summary policies for selecting useful features for localization from the multisession map, and we explore the tradeoff between localization performance and computational complexity. The system is evaluated on 77 recordings, with a total length of 30 kilometers, collected outdoors over 16 months. These datasets cover all seasons, various times of day, and changing weather such as sunshine, rain, fog, and snow. We show that it is possible to build consistent maps that span data collected over an entire year, and cover day‐to‐night transitions. Simple statistics computed on landmark observations are enough to produce a Summary Map that enables robust and accurate localization over a wide range of seasonal, lighting, and weather conditions.
Holistic Performance Model for Cyber Security Implementation Frameworks

The performance measurement process identifies if an implementation process is within acceptable thresholds. Performance measures for cyber security implementation frameworks are considered strategic controls because it can guide the implementation process. Consequently, corrective or predictive actions could be applied to resolve a security issue early in the implementation process. However, to our knowledge, there are no performance measures designed to function at the country level for cyber security implementation frameworks. As a result, cyber security strategy implementation process is left uncontrolled. To resolve this issue, this article proposes a new holistic performance model that is based on the well-known balanced scorecard. It aggregates performance measures from various entities involved in executing cyber security strategies. The inception of the proposed model draws its applicability to address performance measurement of holistic cyber security implementation frameworks.
Beyond The Business Case and Sustainable chain management: Why Do We Need to Build a Theory of Interfirm Social Responsability?

The purpose of the present article is to demonstrate the necessity of focusing on interfirm interactions when analysing the rise of socially responsible practices. The first section highlights problems with the standard business case's explanations for the connection between economic and socio-environmental performance, highlighting the limitations of this approach's firm-centric reasoning. A similar critique is offered as regards studies that focus on green/sustainable supply chains – simply bringing suppliers into the analysis adds to the range of actors being covered but does little to identify existing gaps in the literature. Section 3 uses the example of the automotive industry to show how the inconsistency between corporate social responsibility (CSR) discourse and practice becomes clear when interfirm interactions are taken into account. The conclusion suggests that achieving real progress in the development of socially responsible practices requires the construction of a theory of interfirm social responsibility based on an institutionalist framework.
Assessing impacts of data volume and data set balance in using deep learning approach to human activity recognition

Over the past decade, deep learning developed rapidly and had significant impact on a variety of application domains. It has been applied to the field of human activity recognition to substitute for well-established analysis techniques that rely on handcrafted feature extraction and classification methods in recent years. However, less attentions have been paid to the influence of training data on recognition accuracy. In this paper, we assessed the influence factors of data volume and data balance in human activity recognition when using deep learning approaches. We evaluated the relationship between data volumes of training dataset and predict accuracy of deep learning algorithms. Given the impact of the data balance between activity categories on the recognition accuracy, we modified the SMOTE algorithm so that it can be applied to human activity recognition. Results show that when the data volume is small (<4M), the recognition accuracy increased quickly with the increase of the quantity of training data. However, the growth trend of recognition accuracy slows down when the data quantity reaches 4 million. Further increase the data volume does not significantly improve the activity recognition performance. So we can conclude that 4 million data volume can ensure a sufficient accuracy for human activity recognition. Meanwhile, the data set balance operation can not only improve the recognition accuracy of minority categories, but also helps to increase the overall accuracy.
Articulated Billboards for Video‐based Rendering

We present a novel representation and rendering method for free‐viewpoint video of human characters based on multiple input video streams. The basic idea is to approximate the articulated 3D shape of the human body using a subdivision into textured billboards along the skeleton structure. Billboards are clustered to fans such that each skeleton bone contains one billboard per source camera. We call this representation articulated billboards.
Value Chain Reconfiguration in Highly Disaggregated Industrial Systems: Examining the Emergence of Health Care Diagnostics

Many industries have witnessed the progressive disaggregation of their value chains as firms focus on internal advantages and exploit evolving external capabilities. While previous industry studies provide rich narratives on the changes to vertical scope, this study applies evolutionary and configuration theories to explore disaggregation in a subsector of health care, namely in vitro diagnostics, with its unique combination of multiple technology-intense platforms, distributed information and revenue models within a highly regulated environment. The research provides a framework for exploring value chain disaggregation by examining actor variation, selection, and retention patterns, and the reconfiguration of information, material, and revenue flows between industrial actors. Results suggest disaggregation is driven by fragmented operating models supporting novel capabilities in addition to efficiency-driven capability redistribution.
Force‐velocity relation in normal and nitrate‐treated frog single muscle fibres during rise of tension in an isometric tetanus.

1. The force‐velocity (P‐V) relation for normal or NO‐3 treated single fibres isolated from the semitendinosus muscle of the frog was determined at given times during the rise of tension and the plateau of isometric tetani. Experiments were made at about 2.25 micron sarcomere length and at constant temperatures, from 3 to 4.5 degrees C and from 19 to 21 degrees C. The controlled‐velocity release method was used. 2. During the rise of tension, at any initial tension higher than about 0.2 P0, the lowest release velocity required to drop the tension to zero was the same as at the tetanic plateau, independent of the temperature and the presence of NO‐3 ions in the bathing solution. 3. The degree of activation (measured by the steady force exerted at a given velocity of shortening lower than V0) increased with time, but attained its steady‐state level before isometric tension. 4. At about 20 degrees C, frog muscle fibres at about 2.2 micron sarcomere length were only partially activated after a single stimulus. 5. NO‐3 ions did not affect the steady‐state P‐V relation. At about 20 degrees C, NO‐3 ions increased the rate of development of activation. Potentiation of the twitch contraction was due at least in part to this mechanism. 6. The 'relative' P‐V relation appears to be independent of both the time after start of stimulation and the presence of NO‐3 ions in the bathing solution. 7. The results are discussed in terms of the sliding filament model of Huxley (1957), assuming that either the number of actin sites available for cross‐bridge formation, or the value of the rate constant for making of cross‐bridges, is time dependent.
Key points and the most significant documents in the production of the High Resolution Vector Data (HRVD) within the Multinational Geospatial Co-production Program (MGCP)

The United States Defense Mapping Agency formulated the need for digital data created in a multinational co-production covering the entire surface of Earth, at the end of the eighties. Hungary was not among the 20 executor states (18 NATO Members, New-Zealand and Australia) because of this our country can only acquire the (VMAP Level 1) parts of the 1:250.000 data providing full coverage with separate mutual agreements within the limits of responsibility of each party. In April 2003, the United States National Geospatial-Intelligence Agency initiated the foundation of a program providing closer co-operation of defense mapping agencies, to create a geoinformation database that can satisfy the altered needs, this program is called the MGCP (Multinational Geospatial Co-production Program). The aim of the program is to create high scale digital geoinformation database of strategically significant territories. In this article we will discuss the key points of producing High Resolution Vector Data within the Multinational Geospatial Co-production Program (MGCP), especially the importance of the order of the data evaluation.
Engineering supply chains to match customer requirements

Modern day market places are highly varied and cannot be serviced effectively by a single supply chain paradigm. Consequently products and services must be provided to the end consumer via tailored supply chain strategies. This article categorises consumer products and details the specific supply chain management tools and techniques required to service each. A comparison of lean and agile strategies is provided along with a detailed explanation of the integration of the two within a Leagile supply chain. The application of such a strategy for electronic products is provided via a four stage case study. A route map for engineering supply chains to match customer requirements is developed in order to avoid costly and ineffective mismatches of supply chain strategy to product characteristics.
An Integrated Perspective of Service Recovery: A Sociotechnical Systems Approach

This study examines service recovery from an internal, operations-oriented perspective. Specifically, a model grounded in sociotechnical systems (STS) theory is developed and tested to investigate the relationships between service recovery systems, recovery climates, employee abilities and actions, and recovery performance. A sample of 221 general service employees is used to empirically test the proposed model. Results support the STS perspective and suggest that an integrated recovery system is essential in establishing a recovery climate, which in turn enables employee efficacy and reduces avoidance behaviors. Additionally, employee efficacy has a positive effect on performance, while avoidance leads to ineffective failure correction. The results presented herein highlight the need for service practitioners to consider designing and implementing integrated recovery systems in order to enhance the abilities of employees, while heightening the likelihood of failure correction. Furthermore, this study provides an initial step in moving the recovery literature into a more theory-driven direction.
Bayesian estimation for Gini index and a poverty measure in case of pareto distribution using Jeffreys' prior

Bayes estimators are obtained in case of Pareto distribution for its shape parameter, mean income, Gini index and a Poverty measure for both censored and complete setup. The said estimators are obtained using Jeffreys’ non-informative invariant prior and the extension of Jeffreys’ prior information. Using simulation techniques, the relative efficiency of proposed estimators with the existing estimators using two-parameter exponential prior is obtained. It turns out that the Bayesian method with Jeffreys’ non-informative invariant prior results in smaller expected loss function as compared to existing estimators using two-parameter exponential prior.
Localized detection of speech recognition errors

We address the problem of localized error detection in Automatic Speech Recognition (ASR) output. Localized error detection seeks to identify which particular words in a user's utterance have been misrecognized. Identifying misrecognized words permits one to create targeted clarification strategies for spoken dialogue systems, allowing the system to ask clarification questions targeting the particular type of misrecognition, in contrast to the “please repeat/rephrase” strategies used in most current dialogue systems. We present results of machine learning experiments using ASR confidence scores together with prosodic and syntactic features to predict whether 1) an utterance contains an error, and 2) whether a word in a misrecognized utterance is misrecognized. We show that by adding syntactic features to the ASR features when predicting misrecognized utterances the F-measure improves by 13.3% compared to using ASR features alone. By adding syntactic and prosodic features when predicting misrecognized words F-measure improves by 40%.
Notice of RetractionAn empirical analysis of the financial distress prediction based on data mining

With 112 listed companies from A-share market in Chinese securities markets as research sample, authors selected 56 newly ST companies among 2007 and 2008 as distressed enterprises group, and other 56 non-ST companies as comparison group. 13 financial indicators of these companies at three year before being ST were screened out, and the factor analysis and logistic regression were conducted. It found that the effect of the regression as well as the prediction are quite good, so it should be useful as basic discrimination for investors, creditors and regulatory agencies.
Empirical Study of the State of the Practice in Alternative Technical Concepts in Highway Construction Projects

State departments of transportation (DOTs) are encouraging early involvement of contractors in highway design and construction through the solicitation of alternative technical concepts (ATCs) during procurement. This approach provides DOTs with the opportunity to tap industry experience and expertise for design alternatives. ATCs can improve constructability, enhance innovation, shorten schedules, reduce risk, and ultimately save costs. DOTs have documented significant cost savings from ATCs on a project-by-project basis. This paper provides an up-to-date perspective on the types of projects in which ATCs are used in U.S. highway construction, according to empirical data from a national study of 250 projects completed by DOTs and the Office of Federal Lands Highway. These projects were completed through design–build, construction manager–general contractor, and design–bid–build project delivery methods, and only 40 of the projects solicited ATCs during procurement. The quantitative findings presented in this paper were facilitated by the use of the project information from the national study and complimented by an extensive literature review on the use of ATCs in the U.S. highway construction sector. It was found that DOTs used ATCs on 51% of the 70 design–build projects procured by best-value selection in the study. Given that only 2% of the 116 design–bid–build projects and 5% of the 38 low-bid design–build projects in this study used ATCs and that no construction manager–general contractor projects used ATCs, there appears to be an opportunity to capitalize on the benefits of ATCs in projects using those delivery methods.
Acceptance by the Users of Services Integrated in the Home Environment

Whether or not ICT represents the most important vehicle to transform the society seems to be out of discussion. The point of interest diverts from how people do really feel with these services and from the way they perceive the advantages as acceptable to improve the quality of life and work. It is matter of fact that the technical innovation is characterized by a certain risk, the problem of how to implement the technology for sure and, ahead of this phase, the problem of predicting its influence on the social, working and private life in view of the high costs effort to produce. This study applies a predictive model for the acceptance to a services integrated home environment properly set-up in a special laboratory. A class of users was selected from the employees of the company which hosted the trial in order to participate at the evaluation sessions. The tasks were designed to point out the main innovative features of the services presented. The questionnaires were suitably designed and submitted to collect the end-users opinions. The analysis was carried out to assess the performance by the side of the real users and to predict their intentions of use.
Common Message Standards for Electronic Commerce in Wholesale Financial Markets

An important aspect of electronic commerce is the potential for market participants to automate transaction processing fully, from the point of trade to final settlement. Such 'straight-through processing' could make wholesale financial markets more efficient, and lower the costs and risks that participants face. But it requires participants to use common message standards to exchange transaction data electronically. Several market-led initiatives to develop common standards have made substantial progress. But many trade messages are still sent by fax or using incompatible electronic networks, which means that different participants may have to re-input the same data manually at various points during the trade process. This article describes some of the initiatives to establish common standards. It then looks to economic theory to explain why market participants may find it difficult to co-ordinate to introduce a single standard, in spite of the wider benefits. It discusses how such technological changes may affect market structure. Finally, it considers whether some recent technologies, in particular eXtensible Markup Language (XML), may make it easier for market participants to adopt common standards.
A systematic design automation approach for flash ADCs

This paper presents a simulation-based top-down systematic design procedure for flash ADCs. According to the developed design flow, an automated design tool is constructed for sizing flash ADCs in transistor level by consulting the circuit design experience. In addition to fulfill the user-defined specification, issues such as process variations and power consumption are also taken into consideration. The developed tool provides a fast and easy way for users to design a flash ADC without related experiences. Experimental results show the satisfactory performance flash ADCs can be obtained within ten minutes.
Combined Activity of Colloid Nanosilver and Zataria Multiﬂora Boiss Essential Oil-Mechanism of Action and Biofilm Removal Activity

Purpose: The aim of this study was to investigate antimicrobial and biofilm removal potential of Zataria multiflora essential oil (ZEO) and silver nanoparticle (SNP) alone and in combination on Staphylococcus aureus and Salmonella Typhimurium and evaluate the mechanism of action. Methods: The minimum inhibitory concentration (MIC), and optimal inhibitory combination (OIC) of ZEO and SNP were determined according to fractional inhibitory concentration (FIC) method. Biofilm removal potential and leakage pattern of 260-nm absorbing material from the bacterial cell during exposure to the compounds were also investigated. Results: MICs of SNP for both bacteria were the same as 25 μg/ mL. The MICs and MBCs values of ZEO were 2500 and 1250 μg/mL, respectively. The most effective OIC value for SNP and ZEO against Salm. Typhimurium and Staph. aureus were 12.5, 625 and 0.78, 1250 μg/ mL, respectively. ZEO and SNP at MIC and OIC concentrations represented a strong removal ability (>70%) on biofilm. Moreover, ZEO at MIC and OIC concentrations did a 6-log reduction of primary inoculated bacteria during 15 min contact time. The effect of ZEO on the loss of 260-nm material from the cell was faster than SNP during 15 and 60 min. Conclusion: Combination of ZEO and SNP had significant sanitizing activity on examined bacteria which may be suitable for disinfecting the surfaces.
The industry context of strategy, structure and performance: The U.K. brewing industry

This paper is concerned with identifying influences on the competitive performance of companies involved in the U.K. brewing industry. It seeks to identify key strategic characteristics, relate these to company performance and move towards an explanation of the influences that emerge as influencing competitive standing. It argues that diversification strategies must be studied as an aspect of industry structure, and shows that more focused, limited diversification and regional brewing strategies may be preferable in the context of the U.K. brewing industry. The research findings conflict with those of many previous studies which research the diversification strategies of primarily large firms (both in the U.S. and the U.K.) drawn from across-industry samples (e.g. the Fortune 500 firms) and which identify superior performance for related diversification strategies. The study therefore provides support for the hypothesis that there is an optimum level of diversification within an industry which balances economies of scope and diseconomies of organizational scale. In the context of the U.K. brewing industry the traditional single or dominant business brewers seem to have found the strategy which matches firms effectively with the important characteristics of industry structure.