Impact of combined uncertainty and portfolio’s correlations in evaluating its prioritization - Optimized ICT Project Selection Utilizing ROANP

Η μελέτη ασχολείται με την επιλογή και προτεραιοποίηση έργων τεχνολογίας επικοινωνιών πληροφοριών (ΤΠΕ) που μεγιστοποιούν το όφελος μιας επιχείρησης. Τα τελευταία μπορούν να θεωρηθούν ως προβλήματα λήψης αποφάσεων πολλαπλών κριτηρίων (MCDM) για την επίλυση των οποίων οι παραδοσιακές μέθοδοι επιλογής έργων συχνά αποτυγχάνουν, εφόσον δεν λαμβάνουν υπόψη τους τα ιδιαίτερα χαρακτηριστικά αβεβαιότητας και αλληλεπίδρασης μεταξύ των κριτηρίων αξιολόγησης ή/και των εναλλακτικών έργων. Για να αντιμετωπιστεί αυτό το πρόβλημα, προτείνεται ένα νέο μοντέλο που ενσωματώνει τη θεωρία των πραγματικών δικαιωμάτων προαίρεσης (Real Options) και τη διαδικασία δικτυακής ανάλυσης (Analytic Network Process – ANP). Συγκεκριμένα, τα πραγματικά δικαιώματα προαίρεσης χρησιμοποιούνται για να καταγράψουν την αβεβαιότητα που υφίσταται στην υλοποίηση ενός έργου, ενώ οι αλληλεπιδράσεις μοντελοποιούνται μέσω της διαδικασίας ΑΝΡ. Η δομή του μοντέλου δικτύου καλύπτει όλες τις πιθανές εξαρτήσεις και αλληλεπιδράσεις μεταξύ κριτηρίων και εναλλακτικών λύσεων. Το προτεινόμενο μοντέλο εξετάζεται ως προς τη δυνατότητα εφαρμογής του και την αποτελεσματικότητα των διαδικασιών μέσω ενός παραδείγματος. Η χρήση αυτού του μοντέλου οδηγεί σε νέα αποτελέσματα στην κατάταξη της επιλογής έργων ΤΠΕ, παρέχοντας έτσι μια καλύτερη εικόνα για τον αντίκτυπο της αβεβαιότητας των επενδύσεων και της αλληλεξάρτησης στην επιλογή των έργων.This study deals with the selection and prioritization of Information Communication Technology (ICT) projects that maximize the benefit of a business. The latter may be viewed as a Multi-Criteria Decision Making (MCDM) problem for which traditional project selection methods often fail to solve, as they do not take into account the specific characteristics of uncertainty and interactions between the evaluation criteria and/or different projects. To tackle this problem, a new model is proposed that incorporates Real Option (RO) theory and Analytic Network Process (ANP). In particular, ROs are used to capture project uncertainties, while interactions are modeled through the ANP. The structure of the network model covers all possible dependencies and interactions between criteria and alternatives. The proposed model is examined for its applicability and the effectiveness of procedures through an example. The utilization of this model leads to new results in the ranking of ICT project selection, thus providing further insight on the impact of investment uncertainty and interdependence on project selection

Reexamining low rank matrix factorization for trace norm regularization

Trace norm regularization is a widely used approach for learning low rank matrices. A standard optimization strategy is based on formulating the problem as one of low rank matrix factorization which, however, leads to a non-convex problem. In practice this approach works well, and it is often computationally faster than standard convex solvers such as proximal gradient methods. Nevertheless, it is not guaranteed to converge to a global optimum, and the optimization can be trapped at poor stationary points. In this paper we show that it is possible to characterize all critical points of the non-convex problem. This allows us to provide an efficient criterion to determine whether a critical point is also a global minimizer. Our analysis suggests an iterative meta-algorithm that dynamically expands the parameter space and allows the optimization to escape any non-global critical point, thereby converging to a global minimizer. The algorithm can be applied to problems such as matrix completion or multitask learning, and our analysis holds for any random initialization of the factor matrices. Finally, we confirm the good performance of the algorithm on synthetic and real datasets

Replication Based on Objects Load under a Content Distribution Network

Users tend to use the Internet for “resource-hungry” applications (which involve content such as video, audio on-demand and distributed data) and at the same time, more and more applications (such as e-commerce, e-learning etc.) are relying on the Web. In this framework, Content Distribution Networks (CDNs) are increasingly being used to disseminate data in today's Internet, providing a delicate balance between costs for Web content providers and quality of services for Web customers. The growing interest in CDNs is motivated by a common problem across disciplines: how does one reduce the load on the origin server and the traffic on the Internet, and ultimately improve response time to users? In this direction, crucial data management issues should be addressed. A very important issue is the optimal placement of the outsourced content to CDN’s servers. Taking into account that this problem is NP complete, an heuristic method should be developed. All the approaches developed so far either take as criterion the network’s latency or the workload. This paper develops a novel technique to place the outsourced content to CDN’s servers, integrating both the latency and the load. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed method can improve significantly the response time of requests while keeping the CDNs ’ servers ’ load at a very low level. 1

Mesothelial Cyst of the Round Ligament Misdiagnosed as Irreducible Inguinal Hernia

We report the case of a 36-year-old woman who presented with signs and symptoms of an irreducible inguinal hernia. Surgical exploration revealed a mesothelial cyst of the round ligament of the uterus. Mesothelial cysts of the round ligament are rare lesions, frequently masquerading as inguinal hernias, and should be included in the differential diagnosis of any inguinal mass. Clinical findings are those of a groin mass, discomfort, and bulging. Ultrasound and CT scans often demonstrate an aperistaltic cystic mass. Definitive diagnosis is usually made intraoperatively and confirmed histopathologically

A Latency-based Object Placement Approach

Content Distribution Networks (CDNs) are increasingly being used to disseminate data in today's Internet. The growing interest in CDNs is motivated by a common problem across disciplines: how does one reduce the load on the origin server and the traffic on the Internet, and ultimately improve response time to users? In this direction, crucial data management issues should be addressed. A very important issue is the optimal placement of the outsourced content to CDN’s servers. Taking into account that this problem is NP complete, an heuristic method should be developed. All the approaches developed so far assume the existence of adequate popularity statistics. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. This paper develops a network-adaptive, nonparameterized technique to place the outsourced content to CDN’s servers, which requires no a-priori knowledge of request statistics. We place the outsourced objects to these servers with respect to the network latency that each object produces. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed technique can yield up to 25 % reduction in user-perceived latency, compared with other heuristic schemes which have knowledge of the content popularity. 1

Transient Femoral Nerve Palsy Complicating “Blind” Transversus Abdominis Plane Block

We present two cases of patients who reported quadriceps femoris weakness and hypoesthesia over the anterior thigh after an inguinal hernia repair under transversus abdominis plane (TAP) block. Transient femoral nerve palsy is the result of local anesthetic incorrectly injected between transversus abdominis muscle and transversalis fascia and pooling around the femoral nerve. Although it is a minor and self-limiting complication, it requires overnight hospital stay and observation of the patients. Performing the block under ultrasound guidance and injecting the least volume of local anesthetic required are ways of minimizing its incidence

World Wide Web DOI 10.1007/s11280-007-0027-8 Prefetching in Content Distribution Networks via Web Communities Identification and Outsourcing

Abstract Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the “edge ” of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the “last mile ” latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop selfadaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of “correlated ” Web pages in a site, called Web site communities, and make thes

CDNsim: A Simulation Tool for Content Distribution Networks

Content distribution networks (CDNs) have gained considerable attention in the past few years. Hence there is need for developing frameworks for carrying out CDN simulations. In this article we present a modeling and simulation framework for CDNs, called CDNsim. CDNsim has been designated to provide a realistic simulation for CDNs, simulating the surrogate servers, the TCP/IP protocol, and the main CDN functions. The main advantages of this tool are its high performance, its extensibility, and its user interface, which is used to configure its parameters. CDNsim provides an automated environment for conducting experiments and extracting client, server, and network statistics. The purpose of CDNsim is to be used as a testbed for CDN evaluation and experimentation. This is quite useful to both the research community (to experiment with new CDN data management techniques), and for CDN developers (to evaluate profits on prior certain CDN installations)