EFFICIENCY, PRODUCTIVITY AND OUTPUT GROWTH: AN INTER-REGIONAL ANALYSIS OF GREEK AGRICULTURE

Output growth decomposition of the Greek olive-oil sector under technical and allocative inefficiencies, economies of scale and technical change, is performed. The stochastic production frontier model is extended to panel data and FGLS estimation. Conventional inputs are main source of growth: TFP increased in slow rate during the study period.Crop Production/Industries, Industrial Organization,

Measuring the Accountability of Advertising Expenses in the Presence of Sales Cost Inefficiency and Marketing Spillovers

This paper develops a tractable theoretical framework for analyzing the substitutability between different advertising media, the extent of marketing spillovers in the market, the allocative efficiency of advertising spending, and the sources of total advertising productivity and sales growth. Maintaining the separability assumption between sales and production technology, the proposed methodology relies on cost-function decomposition of total factor productivity and the duality between input distance and cost functions. Utilizing a flexible Translog advertising distance function, the methodology is applied to the advertising activity of meat processing firms in Greece during the period 1983-1997. Scale economies in advertising expenses turn out to be an important source of total advertising productivity changes in the Greek meat processing sector. Advertising spillovers are significant contributing to total advertising productivity observed. Our analysis also indicates that improvements in (technical and allocative) advertising efficiency are more important means of enhancing firm returns than improvements in advertising techniques.Advertising productivity, advertising direct distance function, media substitutability, processed meats industry, Greece

Dynamic Dominators and Low-High Orders in DAGs

We consider practical algorithms for maintaining the dominator tree and a low-high order in directed acyclic graphs (DAGs) subject to dynamic operations. Let G be a directed graph with a distinguished start vertex s. The dominator tree D of G is a tree rooted at s, such that a vertex v is an ancestor of a vertex w if and only if all paths from s to w in G include v. The dominator tree is a central tool in program optimization and code generation, and has many applications in other diverse areas including constraint programming, circuit testing, biology, and in algorithms for graph connectivity problems. A low-high order of G is a preorder of D that certifies the correctness of D, and has further applications in connectivity and path-determination problems. We first provide a practical and carefully engineered version of a recent algorithm [ICALP 2017] for maintaining the dominator tree of a DAG through a sequence of edge deletions. The algorithm runs in O(mn) total time and O(m) space, where n is the number of vertices and m is the number of edges before any deletion. In addition, we present a new algorithm that maintains a low-high order of a DAG under edge deletions within the same bounds. Both results extend to the case of reducible graphs (a class that includes DAGs). Furthermore, we present a fully dynamic algorithm for maintaining the dominator tree of a DAG under an intermixed sequence of edge insertions and deletions. Although it does not maintain the O(mn) worst-case bound of the decremental algorithm, our experiments highlight that the fully dynamic algorithm performs very well in practice. Finally, we study the practical efficiency of all our algorithms by conducting an extensive experimental study on real-world and synthetic graphs

Network Coding-based Routing and Spectrum Allocation in Elastic Optical Networks for Enhanced Physical Layer Security

In this work, an eavesdropping-aware routing and spectrum allocation approach is proposed utilizing network coding (NC) in elastic optical networks (EONs). To provide physical layer security in EONs and secure the confidential connections against eavesdropping attacks using NC, the signals of the confidential connections are combined (XOR-ed) with other signals at different nodes in their path, while transmitted through the network. The combination of signals through NC significantly increases the security of confidential connections, since an eavesdropper must access all individual signals, traversing different links, in order to decrypt the combined signal. A novel heuristic approach is proposed, that solves the combined network coding and routing and spectrum allocation (NC-RSA) problem, that also takes into account additional NC constraints that are required in order to consider a confidential connection as secure. Different routing and spectrum allocation strategies are proposed, aiming to maximize the level of security provided for the confidential demands, followed by an extensive performance evaluation of each approach in terms of the level of security provided, as well as the spectrum utilization and blocking probability, under different network parameters. Performance results demonstrate that the proposed approaches can provide efficient solutions in terms of network performance, while providing the level of security required for each demand

Measuring the Accountability of Advertising Expenses in the Presence of Sales Cost Inefficiency and Marketing Spillovers

This paper develops a tractable theoretical framework for analyzing the substitutability between different advertising media, the extent of marketing spillovers in the market, the allocative efficiency of advertising spending, and the sources of total advertising productivity and sales growth. Maintaining the separability assumption between sales and production technology, the proposed methodology relies on cost-function decomposition of total factor productivity and the duality between input distance and cost functions. Utilizing a flexible Translog advertising distance function, the methodology is applied to the advertising activity of meat processing firms in Greece during the period 1983-1997. Scale economies in advertising expenses turn out to be an important source of total advertising productivity changes in the Greek meat processing sector. Advertising spillovers are significant contributing to total advertising productivity observed. Our analysis also indicates that improvements in (technical and allocative) advertising efficiency are more important means of enhancing firm returns than improvements in advertising techniques

Kernel Graph Convolutional Neural Networks

Graph kernels have been successfully applied to many graph classification problems. Typically, a kernel is first designed, and then an SVM classifier is trained based on the features defined implicitly by this kernel. This two-stage approach decouples data representation from learning, which is suboptimal. On the other hand, Convolutional Neural Networks (CNNs) have the capability to learn their own features directly from the raw data during training. Unfortunately, they cannot handle irregular data such as graphs. We address this challenge by using graph kernels to embed meaningful local neighborhoods of the graphs in a continuous vector space. A set of filters is then convolved with these patches, pooled, and the output is then passed to a feedforward network. With limited parameter tuning, our approach outperforms strong baselines on 7 out of 10 benchmark datasets.Comment: Accepted at ICANN '1

Incremental Low-High Orders of Directed Graphs and Applications

A flow graph G = (V, E, s) is a directed graph with a distinguished start vertex s. The dominator tree D of G is a tree rooted at s, such that a vertex v is an ancestor of a vertex w if and only if all paths from s to w include v. The dominator tree is a central tool in program optimization and code generation, and has many applications in other diverse areas including constraint programming, circuit testing, biology, and in algorithms for graph connectivity problems. A low-high order of G is a preorder d of D that certifies the correctness of D, and has further applications in connectivity and path-determination problems. In this paper we consider how to maintain efficiently a low-high order of a flow graph incrementally under edge insertions. We present algorithms that run in O(mn) total time for a sequence of edge insertions in a flow graph with n vertices, where m is the total number of edges after all insertions. These immediately provide the first incremental certifying algorithms for maintaining the dominator tree in O(mn) total time, and also imply incremental algorithms for other problems. Hence, we provide a substantial improvement over the O(m^2) straightforward algorithms, which recompute the solution from scratch after each edge insertion. Furthermore, we provide efficient implementations of our algorithms and conduct an extensive experimental study on real-world graphs taken from a variety of application areas. The experimental results show that our algorithms perform very well in practice

TEACHING SUBJECTS AND PARTICIPATION RATES IN PHYSICAL EDUCATION COURSES AMONG CHILDREN AGED 10 TO 12 YEARS

Physical activity (PA) is a parameter of children's life that is straight connected to the benefits of their life (protection against obesity, better psychological profile, and predisposition for increased levels of PA as adult etc.). The purpose of the present study was to evaluate parameters of PA during Physical Education (PE) classes and to explore the subjects that the children participate in the PE course. PA, PE, and sedentary behaviors were assessed by a self-administrated PA checklist, proper for children. Body mass index (BMI) was calculated from measured body weight and height. A representative sample of Greek boys and girls aged 10 to 12 years (N=3195) participated in the study. Results showed that boys had higher levels of total and vigorous-intensity PA (VPA), than girls (all p-values<0.05), while girls presented higher light-to-moderate intensity PA as compared to boys. In those days that students participated in PE classes, total PA and VPA were higher in comparison with days didn't, in both sexes (p<0.001), while, a greater proportion of children met the current recommendations for PA (86.1% vs. 69.1% for boys and 68.4% vs. 53.5% for girls). During PE classes, boys participated in a greater proportion than girls in basketball and soccer (all p-values<0.05), while, more girls in comparison to boys participated in volleyball, dance, and jump-rope (all p-values<0.05). Stratified data analysis by BMI category among children who participated in PE classes did not reveal significant differences in time participated in PE components among categories, except for games (e.g. chase, tag) among boys. In conclusion, boys have higher levels of total PA than girls, while, it seems that school and PE classes play a significant role in students' levels of PA which could grow up further with interventions as the increase of hours in PE lessons.  Article visualizations