995 resultados para ownership cost


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Existing business models require RFID tag to transfer its ownership during its life cycle. As a result, a RFID tags might have many owners during its life cycle. However, the transfer of ownership should ensure that previous owners have no information about current owner's data. Physical ownership does not ensure digital ownership transfer given the wireless nature of communication with RFID tags. Most of the proposed protocol in this nature is implacable to address aU existing RFID tag ownership transfer scenarios. Moreover, they have many security concerns and vulnerabilities. In this paper, we have investigated and discussed all existing business cases and their transfer scenarios. To cover all ownership transfer scenarios, we have presented an ownership transfer protocol. The proposed protocol has used modified DiffieHellman algorithm to perform ownership request validation and authentication of involved parties. Performance comparison shows that our protocol is practical to implement passive low-cost RFID tags, securely performs tag ownership transfer and can be used for all existing ownership transfer scenarios.

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In this paper, we propose a novel approach to secure ownership transfer in RFID systems based on the quadratic residue property. We present two secure ownership transfer schemes-the closed loop and open loop schemes. An important property of our schemes is that ownership transfer is guaranteed to be atomic. Further, both our schemes are suited to the computational constraints of EPC Class-1 Gen-2 passive RFID tags as they only use operations that such passive RFID tags are capable of. We provide a detailed security analysis to show that our schemes achieve strong privacy and satisfy the required security properties of tag anonymity, tag location privacy, forward secrecy, and forward untraceability. We also show that the schemes are resistant to replay (both passive and algebraic), desynchronization, and server impersonation attacks. Performance comparisons demonstrate that our schemes are practical and can be implemented on low-cost passive RFID tags.

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In this paper we propose a secure ownership transfer protocol for a multi-tag and multi-owner RFID environment. Most of the existing work in this area do not comply with the EPC Global Class-1 Gen-2 (C1G2) standard since they use expensive hash operations or sophisticated encryption schemes that cannot be implemented on low-cost passive tags that are highly resource constrained. Our work aims to fill this gap by proposing a protocol based on simple XOR and 128-bit Pseudo Random Number Generators (PRNG), operations that can be easily implemented on low-cost passive RFID tags. The protocol thus achieves EPC C1G2 compliance while meeting the security requirements. Also, our protocol provides additional protection using a blind-factor to prevent tracking attacks.

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In this paper we propose a secure ownership transfer protocol for a multi-tag multi-owner RFID environment that provides individual-owner-privacy. To our knowledge, the existing schemes do not provide individual-owner-privacy and most of the existing schemes do not comply with the EPC Global Class-1 Gen-2 (C1G2) standard since the protocols use expensive hash operations or sophisticated encryption schemes that cannot be implemented on low-cost passive tags that are highly resource constrained. Our work aims to fill these gaps by proposing a protocol that provides individual-owner-privacy, based on simple XOR and 128-bit pseudo-random number generators (PRNG), operations that are easily implemented on low-cost RFID tags while meeting the necessary security requirements thus making it a viable option for large scale implementations. Our protocol also provides additional protection by hiding the pseudo-random numbers during all transmissions using a blind-factor to prevent tracking attacks.

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Mit dem zunehmenden Einsatz von E-Learning-Plattformen rücken verstärkt Wirtschaftlichkeitsaspekte in den Betrachtungsmittelpunkt, die Methoden zur Ermittlung systembedingter Kosten voraussetzen. Durch die zunehmende Serviceorientierung und Integration von LMS mit bestehenden Komponenten der Anwendungsarchitektur sind hierfür jedoch neue Methoden notwendig, welche die Defizite traditioneller Total Cost of Ownership-Modelle abbauen. Einen Ansatzpunkt hierfür bietet das ITIL-Referenzmodell, das einen Rahmen für taktische und operative IT-Services vorgibt und somit die Grundlage für eine serviceorientierte Gesamtkostenermittlung in Form der Total Cost of Services (TCS) liefert.

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The purpose of this research is to examine the relative profitability of the firm within the nursing facility industry in Texas. An examination is made of the variables expected to affect profitability and of importance to the design and implementation of regulatory policy. To facilitate this inquiry, specific questions addressed are: (1) Do differences in ownership form affect profitability (defined as operating income before fixed costs)? (2) What impact does regional location have on profitability? (3) Do patient case-mix and access to care by Medicaid patients differ between proprietary and non-profit firms and facilities located in urban versus rural regions, and what association exists between these variables and profitability? (4) Are economies of scale present in the nursing home industry? (5) Do nursing facilities operate in a competitive output market characterized by the inability of a single firm to exhibit influence over market price?^ Prior studies have principally employed a cost function to assess efficiency differences between classifications of nursing facilities. The inherent weakness in this approach is that it only considers technical efficiency. Not both technical and price efficiency which are the two components of overall economic efficiency. One firm is more technically efficient compared to another if it is able to produce a given quantity of output at the least possible costs. Price efficiency means that scarce resources are being directed towards their most valued use. Assuming similar prices in both input and output markets, differences in overall economic efficiency between firm classes are assessed through profitability, hence a profit function.^ Using the framework of the profit function, data from 1990 Medicaid Costs Reports for Texas, and the analytic technique of Ordinary Least Squares Regression, the findings of the study indicated (1) similar profitability between nursing facilities organized as for-profit versus non-profit and located in urban versus rural regions, (2) an inverse association between both payor-mix and patient case-mix with profitability, (3) strong evidence for the presence of scale economies, and (4) existence of a competitive market structure. The paper concludes with implications regarding reimbursement methodology and construction moratorium policies in Texas. ^

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This paper empirically estimates and analyzes various efficiency scores of Indian banks during 1997-2003 using data envelopment analysis (DEA). During the 1990s India's financial sector underwent a process of gradual liberalization aimed at strengthening and improving the operational efficiency of the financial system. It is observed, none the less, that Indian banks are still not much differentiated in terms of input or output oriented technical efficiency and cost efficiency. However, they differ sharply in respect of revenue and profit efficiencies. The results provide interesting insight into the empirical correlates of efficiency scores of Indian banks. Bank size, ownership, and the fact of its being listed on the stock exchange are some of the factors that are found to have positive impact on the average profit efficiency and to some extent revenue efficiency scores are. Finally, we observe that the median efficiency scores of Indian banks in general and of bigger banks in particular have improved considerably during the post-reform period.

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FDI plays a key role in development, particularly in resource-constrained transition economies of Central and Eastern Europe with relatively low savings rates. Gains from technology transfer play a critical role in motivating FDI, yet potential for it may be hampered by a large technology gap between the source and host country. While the extent of this gap has traditionally been attributed to education, skills and capital intensity, recent literature has also emphasized the possible role of institutional environment in this respect. Despite tremendous interest among policy-makers and academics to understand the factors attracting FDI (Bevan and Estrin, 2000; Globerman and Shapiro, 2003) our knowledge about the effects of institutions on the location choice and ownership structure of foreign firms remains limited. This paper attempts to fill this gap in the literature by examining the link between institutions and foreign ownership structures. To the best of our knowledge, Javorcik (2004) is the only papers, which use firm-level data to analyse the role of institutional quality on an outward investor’s entry mode in transition countries. Our paper extends Javorcik (2004) in a number of ways: (a) rather than a cross-section, we use panel data for the period 1997-2006; (b) rather than a binary variable, we use the percentage foreign ownership as continuous variable; (c) we consider multi-dimensional institutional variables, such as corruption, intellectual property rights protection and government stability. We also use factor analysis to generate a composite index of institutional quality and see how stronger institutional environment could affect foreign ownership; (d) we explore how the distance between institutional environment in source and host countries affect foreign ownership in a host country. The firm-level data used includes both domestic and foreign firms for the period 1997-2006 and is drawn from ORBIS, a commercially available dataset provided by Bureau van Dijk. In order to examine the link between institutions and foreign ownership structures, we estimate four log-linear ownership equations/specifications augmented by institutional and other control variables. We find evidence that the decision of a foreign firm to either locate its subsidiary or acquire an existing domestic firm depends not only on factor cost differences but also on differences in institutional environment between the host and source countries.

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There is lots of evidence that innovating firms are persistently more profitable than non-innovators, but little agreement on why this is the case. It may be because innovators are somehow able to protect their new products from the competition which normally erodes profits, or because innovating firms have superior capabilities and are able to introduce multiple innovations over time. And very little is known about the relationship between innovation, external ownership and profitability, despite the fact that foreign-owned firms are frequently highly innovative and very profitable. This paper considers the relationship between innovation, ownership and profitability for a panel of manufacturing plants in Ireland and Northern Ireland. We consider the link between innovation and profits separately for innovators and non-innovators, and for indigenous innovators and non-innovators and externally-owned plants. We also consider the determinants of innovation over the distribution of plant-level profitability, and find that the determinants of profitability – including innovation and external ownership – are quite different for low and high-profitability plants. We find support for the view that innovators and non-innovators have different profitability determinants, and that externally-owned plants have their profitability determined in a quite different way from indigenous enterprises. For indigenous non-innovators only the sector matters. Profitability in these enterprises is dictated largely by the industry they are in, with plants having virtually no means of differentiating their profitability from the norms of the industry. By contrast, indigenously-owned innovators are able to differentiate their profit performance from industry norms to some extent. Absolute size matters (negatively) and they get a strong boost from product innovation, but having a high market share does not matter for the profitability of indigenously-owned innovators. Externally-owned plants have a quite different set of profitability determinants from both of these groups. What matters for these plants is not the boost they get from innovating (there is none) but instead their position in the domestic market – a high market share boosts profitability. In policy terms our results suggest both optimistic and cautionary messages. On the positive side our results suggest that efforts to promote innovation activity among indigenously-owned plants are likely to have significant longer term benefits through their capability effects. For the development agencies in Ireland this is a reassuring result. On the more negative side, the lack of any relationship in our models between the innovation activities of externally-owned plants and their (profitability) performance raises potential concerns. This finding may reflect the lack of linkages between externally-owned plants and their Irish resource base, in turn raising some worrying issues about the ‘embeddedness’ of much FDI into Ireland and therefore its ‘stickiness’ in the face of Ireland’s increasing high relative cost base.

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This article examines cost economies, productivity growth and cost efficiency of the Chinese banks using a unique panel dataset that identifies banks' four outputs and four input prices over the period of 1995-2001. By assessing the appropriateness of model specification, and making use of alternative methodologies in evaluating the performance of banks, we find that the joint-stock commercial banks outperform state-owned commercial banks in productivity growth and cost efficiency. Under the variable cost assumption, Chinese banks display economies of scale, with state-owned commercial banks enjoying cost advantages over the joint-stock commercial banks. Consequently, our results highlight the ownership advantage of these two types of banks and generally support the ongoing banking reform and transformation that is currently taking place in China.

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Thesis (Master's)--University of Washington, 2016-06

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In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

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This thesis investigates the effectiveness of Corporate Governance (CG) reforms in Pakistan. Using a sample of 160 Pakistani firms from 2003 to 2013 and governance data collected manually from the annual reports, this thesis investigates seven closely related and important corporate issues that are related to the compliance of governance rules. Specifically, it aims to : (i) investigate the degree of CG compliance with 2002 Pakistani Code of CG (PCCG); (ii) determine whether the introduction of 2002 PCCG has improved Pakistani CG practices; (iii) investigate the determinants of CG compliance and disclosure for Pakistani listed firms; (iv) test the nexus between CG compliance with the 2002 PCCG and firms’ cost of capital (COC); (v) investigate the impact of different individual CG mechanisms on listed firms COC; (vi) examine how different ownership structures impact on firms’ COC; and (vii) analyse relationship between CG structures and Cost of Equity (COE) as well as Cost of Debt (COD) for Pakistani listed firms. These empirical investigations report some important results. First, the reported findings suggest that Pakistani firms have responded positively to governance disclosure requirements over the eleven year period from 2003 to 2013. The results also show that the introduction of the PCCG in 2002 has improved CG standards by Pakistani listed firms. Second, the reported results related to the determinants of CG compliance demonstrate that significant and positive association between institutional, government and foreign ownership with CG compliance. However, findings relating to the determinants of CG compliance show a negative and significant association between board size and block ownership with CG compliance and disclosure. The study finds no significant relationship between director ownership, audit firm size and the presence of female board members with the constructed Pakistan Corporate Governance Index (PCGI). Third, the investigation on the relationship between CG and COC report a significantly negative nexus between PCGI and firms’ COC. The investigation on the association between ownership structures and COC report a negative and significant nexus between block ownership with firms’ COC. Further, a number of robustness analyses performed in this study suggest that the empirical results reported in this study are generally robust to the alternative CG variables, alternative COC variables and potential endogeneity problems.