Using Metadata to Analyze Trajectories of Finnish Newspapers

The National Library of Finland has digitized newspapers starting from late eighteenth century. Digitized data of Finnish newspapers is a heterogeneous data set, which contains the content and metadata of historical newspapers. This research work is focused to study this rich materiality data to find the data-driven categorization of newspapers. Since the data is not known beforehand, the objective is to understand the development of newspapers and use statistical methods to analyze the fluctuations in the attributes of this metadata. An important aspect of this research work is to study the computational and statistical methods which can better express the complexity of Finnish historical newspaper metadata. Exploratory analyses are performed to get an understanding of the attributes and extract the patterns among them. To explicate the attributes’ dependencies on each other, Ordinary Least Squares and Linear Regression methods are applied. The results of these regression methods confirm the significant correlation between the attributes. To categorize the data, spectral and hierarchical clustering methods are studied for grouping the newspapers with similar attributes. The clustered data further helps in dividing and understanding the data over time and place. Decision trees are constructed to split the newspapers after attributes’ logical divisions. The results of Random Forest decision trees show the paths of development of the attributes. The goal of applying various methods is to get a comprehensive interpretation of the attributes’ development based on language, time, and place and evaluate the usefulness of these methods on the newspaper data. From the features’ perspective, area appears as the most imperative feature and from language based comparison Swedish newspapers are ahead of Finnish newspapers in adapting popular trends of the time. Dividing the newspaper publishing places into regions, small towns show more fluctuations in publishing trends, while from the perspective of time the second half of twentieth century has seen a large increase in newspapers and publishing trends. This research work coordinates information on regions, language, page size, density, and area of newspapers and offers robust statistical analysis of newspapers published in Finland

Policies and Procedures for the Termination of War Contracts

The concept of recognition and biofunctionality has attracted increasing interest in the fields of chemistry and material sciences. Advances in the field of nanotechnology for the synthesis of desired metal oxide nanostructures have provided a solid platform for the integration of nanoelectronic devices. These nanoelectronics-based devices have the ability to recognize molecular species of living organisms, and they have created the possibility for advanced chemical sensing functionalities with low limits of detection in the nanomolar range. In this review, various metal oxides, such as ZnO-, CuO-, and NiO-based nanosensors, are described using different methods (receptors) of functionalization for molecular and ion recognition. These functionalized metal oxide surfaces with a specific receptor involve either a complex formation between the receptor and the analyte or an electrostatic interaction during the chemical sensing of analytes. Metal oxide nanostructures are considered revolutionary nanomaterials that have a specific surface for the immobilization of biomolecules with much needed orientation, good conformation and enhanced biological activity which further improve the sensing properties of nanosensors. Metal oxide nanostructures are associated with certain unique optical, electrical and molecular characteristics in addition to unique functionalities and surface charge features which shows attractive platforms for interfacing biorecognition elements with effective transducing properties for signal amplification. There is a great opportunity in the near future for metal oxide nanostructure-based miniaturization and the development of engineering sensor devices

Performance evaluation of wake-up radio based wireless body area network

Abstract. The last decade has been really ambitious in new research and development techniques to reduce energy consumption especially in wireless sensor networks (WSNs). Sensor nodes are usually battery-powered and thus have very limited lifetime. Energy efficiency has been the most important aspect to discuss when talking about wireless body area network (WBAN) in particular, since it is the bottleneck of these networks. Medium access control (MAC) protocols hold the vital position to determine the energy efficiency of a WBAN, which is a key design issue for battery operated sensor nodes. The wake-up radio (WUR) based MAC and physical layer (PHY) have been evaluated in this research work in order to contribute to the energy efficient solutions development. WUR is an on-demand approach in which the node is woken up by the wake-up signal (WUS). A WUS switches a node from sleep mode to wake up mode to start signal transmission and reception. The WUS is transmitted or received by a secondary radio transceiver, which operates on very low power. The energy benefit of using WUR is compared with conventional duty-cycling approach. As the protocol defines the nodes in WUR based network do not waste energy on idle listening and are only awakened when there is a request for communication, therefore, energy consumption is extremely low. The performance of WUR based MAC protocol has been evaluated for both physical layer (PHY) and MAC for transmission of WUS and data. The probabilities of miss detection, false alarm and detection error rates are calculated for PHY and the probabilities of collision and successful data transmission for channel access method Aloha is evaluated. The results are obtained to compute and compare the total energy consumption of WUR based network with duty cycling. The results prove that the WUR based networks have significant potential to improve energy efficiency, in comparison to conventional duty cycling approach especially, in the case of low data-reporting rate applications. The duty cycle approach is better than WUR approach when sufficiently low duty cycle is combined with highly frequent communication between the network nodes

Responding to Agency Avoidance of OIRA

Concerns have recently been raised that US federal agencies may sometimes avoid regulatory review by the White House Office of Information and Regulatory Affairs (OIRA). In this article, we assess the seriousness of such potential avoidance, and we recommend a framework for evaluating potential responses. After summarizing the system of presidential regulatory oversight through OIRA review, we analyze the incentives for agencies to cooperate with or avoid OIRA. We identify a wider array of agency avoidance tactics than has past scholarship, and a wider array of corresponding response options available to OIRA, the President, Congress, and the courts. We argue that, because the relationship between agencies and OIRA involves ongoing repeat player interactions, some of these avoidance tactics are less likely to occur (or to succeed) than has previously been alleged, and others are more likely; the difference depends significantly on how easy it is for OIRA to detect avoidance, and for OIRA, the courts, and others to respond. Further, we note that in this repeat player relationship, responses to agency avoidance tactics may induce further strategic moves and countermoves. Thus we further argue that the optimal response may not always be to try to eliminate the avoidance behavior; some avoidance may be worth tolerating where the benefits of trying to reduce agency avoidance would not justify the costs of response options and countermoves. We therefore conclude that responses to agency avoidance should be evaluated in a way similar to what OIRA asks of agencies evaluating proposed regulations: by weighing the pros and cons of alternative response options (including no action)

The Impact of Public Expenditure Components on Economic Growth in Pakistan.

This study examines the relationship between health expenditure, expenditure on education, Gross Fixed Capital Formation, Military Expenditure, Fiscal Balance (Deficit) and economic growth in Pakistan. The period of study is from 1972 to 2015. ARDL Bounds Testing approach for co-integration and ECM Technique were applied to study the long run and short run relationship among the above mentioned variables. “Granger Causality Test” was applied to find out the direction of causality. The results reveal a long run relationship between Military Expenditure, Gross Fixed Capital Formation, Fiscal Balance and Economic Growth. The results of “ECM” show the short run relationship among these variables. However, there is no long run relationship between Health Expenditure, Expenditure on Education and Economic Growth. The speed of adjustment is high which 62.28% is. “Granger Causality” test reveals that “causality runs from Military Expenditure to Economic Growth”. It further reveals causality from health expenditure to fiscal balance and from fiscal balance to Military Expenditure. It is concluded that fiscal policy has an important role in boosting economic growth

How Do The Relational Investments Affect Relational Outcomes?

The paper integrates insights from transaction cost economics and relational exchange theory to discuss the efficacy of value-creating relational investments in affecting certain relational outcomes in context of supplier-intermediate buyer dyadic relationships. After performing PLS path modelling on a data set of 284 dyadic relationships, it has been found that value-creating relational investments made by the focal suppliers in their (intermediate) buyers positively affect various facets of satisfaction, trust and commitment (altogether, the relationship quality) of the intermediate buyers. It has been further argued that an enhancement in the relationship quality ultimately translates into an enhancement in performance of the inter-firm relationships

Explaining Franchisors Tendency To Use Multi-Unit Franchising: Development Of A Theoretical Model

In this theoretical paper, we give an overview of the development of literature on multi-unit franchising, discuss the theoretical and methodological deficits, and develop a model for empirical test. The main focus of existing franchising research has been on single unit franchising. Although several empirical studies were published on multi-unit franchising in the last decade, the research deficit primarily results from the lack of theoretical foundation of this ownership strategy in franchising networks. As an attempt to address this research gap, we develop an integrative model.  The propositions explain the franchisor’s tendency to use multi-unit franchising in context of transaction cost theory (franchisee’s specific investments and market uncertainty), resource based view (financial resources scarcity), organizational capabilities view (local market know-how and system specific assets) and agency theory (behavioral uncertainty). We plan to empirically test the proposed model in the near future

The Impact of Public Expenditure Components on Economic Growth in Pakistan.

This study examines the relationship between health expenditure, expenditure on education, Gross Fixed Capital Formation, Military Expenditure, Fiscal Balance (Deficit) and economic growth in Pakistan. The period of study is from 1972 to 2015. ARDL Bounds Testing approach for co-integration and ECM Technique were applied to study the long run and short run relationship among the above mentioned variables. “Granger Causality Test” was applied to find out the direction of causality. The results reveal a long run relationship between Military Expenditure, Gross Fixed Capital Formation, Fiscal Balance and Economic Growth. The results of “ECM” show the short run relationship among these variables. However, there is no long run relationship between Health Expenditure, Expenditure on Education and Economic Growth. The speed of adjustment is high which 62.28% is. “Granger Causality” test reveals that “causality runs from Military Expenditure to Economic Growth”. It further reveals causality from health expenditure to fiscal balance and from fiscal balance to Military Expenditure. It is concluded that fiscal policy has an important role in boosting economic growth