Persistence, capital account openness, and financial sector health in exchange rate regime choice

This paper investigates empirically the persistence in exchange rate regimes as well as the role of capital account openness and financial sector health (measured by financial development and financial sector fragility) in exchange rate regime determination for a panel of 143 countries covering the post-Bretton Woods period. The results demonstrate that while low- and high-income countries exhibit highly persistent exchange rate regimes, middle-income countries display relatively lower persistence. For middle-income countries, capital account openness and the level of financial development play important roles in exchange rate regime choice. The fragility of the financial sector does not affect the exchange rate regime determination.

Secure object tracking protocol for networked RFID systems

Networked systems have adapted Radio Frequency identification technology (RFID) to automate their business process. The Networked RFID Systems (NRS) has some unique characteristics which raise new privacy and security concerns for organizations and their NRS systems. The businesses are always having new realization of business needs using NRS. One of the most recent business realization of NRS implementation on large scale distributed systems (such as Internet of Things (IoT), supply chain) is to ensure visibility and traceability of the object throughout the chain. However, this requires assurance of security and privacy to ensure lawful business operation. In this paper, we are proposing a secure tracker protocol that will ensure not only visibility and traceability of the object but also genuineness of the object and its travel path on-site. The proposed protocol is using Physically Unclonable Function (PUF), Diffie-Hellman algorithm and simple cryptographic primitives to protect privacy of the partners, injection of fake objects, non-repudiation, and unclonability. The tag only performs a simple mathematical computation (such as combination, PUF and division) that makes the proposed protocol suitable to passive tags. To verify our security claims, we performed experiment on Security Protocol Description Language (SPDL) model of the proposed protocol using automated claim verification tool Scyther. Our experiment not only verified our claims but also helped us to eliminate possible attacks identified by Scyther.

A novel approach to maximize the sum-rate for MIMO broadcast channels

This paper considers the sum-rate of wireless broadcast systems with multiple antennas at the base station. In a conventional MIMO-BC system with a large number of users, selecting an optimal subset of users to maximizing the overall system capacity is a key design issue. This paper presents a novel approach to investigate the sum-rate using Eigen Value Decomposition (EVD). Particularly, we derive the lower bound on sum-rate of a conventional MIMO-BC using a completely different approach compared to the existing approaches. The paper formulates the rate maximization problem for any number of users and any number of transmitting antennas using EVD approach of the channel matrix. This also shows the impact of channel angle information on the sum-rate of conventional MIMO-BC. Numerical results confirm the benefits of our technique in various MIMO communication scenarios.

Connected P-percent coverage in wireless sensor networks based on degree constraint dominating set approach

In this paper, we propose an algorihm for conneced p-percent coverage probem in Wireless Sensor Networks(WSNs) to improve the over netork life time. In this work, we invstigae the p-pernt coverage problem(PCP) in WSNs which require % of n area should be monitored correctl and to find ou ny additional requirements of the connec p-percent coverge prom. We prose pDCDS algorith which is a learnin autmaton basd algorithm fr PCP pDCDS is a Degreconsained Connected Domining Se based algoithm whch detect the minimum numbe of des to monitor an area. The simulation results demonstrate hat pDCDS can remarkably improve the network lifetime.

Effect of twinning on microstructural evolution during dynamic recrystallisation of hot deformed as-cast austenitic stainless steel

An as-cast austenitic stainless steel was hot deformed at 1173 K, 1223 K, and 1373 K (900 °C, 950 °C, and 1100 °C) to a strain of 1 with a strain rate of 0.5 or 5 s⁻¹. The recrystallised fraction is observed to be dependent on dynamic recrystallisation (DRX). DRX grains nucleated at the initial stages of recrystallization have similar orientation to that of the deformed grains. With increasing deformation, Cube texture dominates, mainly due to multiple twinning and grain rotation during deformation.

Defence against code injection attacks

Code injection attacks are considered serious threats to the Internet users. In this type of attack the attacker injects malicious codes in the user programs to change or divert the execution flows. In this paper we explore the contemporary defence strategies against code injection attacks (CIAs) and underline their limitations. To overcome these limitations, we suggest a number of countermeasure mechanisms for protecting from CIAs. Our key idea relies on the multiplexing technique to preserve the exact return code to ensure the integrity of program execution trace of shell code. This technique also maintains a FIFO (first in first out) queue to defeat the conflict state when multiple caller method makes a call simultaneously. Finally, our technique can provide better performance, in terms of protection and speed, in some point compared to the CFI (control flow integrity) as well as CPM (code pointer masking) techniques.

Securing sensor networks by moderating frequencies

Security of Wireless Sensor Network (WSN) is a key issue in information security. Most existing security protocols exploit various Mathematical tools to strengthen their security. Some protocols use the details of the geographical location of the nodes. However, to the best authors’ knowledge, none of the existing works exploit the constraints faced by the adversary, specifically, tracing a particular frequency from a large range of unknown frequency channels. The current work uses positional details of the individual nodes. Then the aim is to exploit this weakness of tracing frequencies by assigning a wide range of frequency channels to each node. Experiments using Magneto Optic Sensors reveal that any change of the parametric Faraday’s rotational angle affects the frequency of the Optical waves. This idea can perhaps be generalized for practically deployable sensors (having respective parameters) along with a suitable key management scheme.

Enhancing predictive accuracy of cardiac autonomic neuropathy using blood biochemistry features and iterative multitier ensembles

Blood biochemistry attributes form an important class of tests, routinely collected several times per year for many patients with diabetes. The objective of this study is to investigate the role of blood biochemistry for improving the predictive accuracy of the diagnosis of cardiac autonomic neuropathy (CAN) progression. Blood biochemistry contributes to CAN, and so it is a causative factor that can provide additional power for the diagnosis of CAN especially in the absence of a complete set of Ewing tests. We introduce automated iterative multitier ensembles (AIME) and investigate their performance in comparison to base classifiers and standard ensemble classifiers for blood biochemistry attributes. AIME incorporate diverse ensembles into several tiers simultaneously and combine them into one automatically generated integrated system so that one ensemble acts as an integral part of another ensemble. We carried out extensive experimental analysis using large datasets from the diabetes screening research initiative (DiScRi) project. The results of our experiments show that several blood biochemistry attributes can be used to supplement the Ewing battery for the detection of CAN in situations where one or more of the Ewing tests cannot be completed because of the individual difficulties faced by each patient in performing the tests. The results show that AIME provide higher accuracy as a multitier CAN classification paradigm. The best predictive accuracy of 99.57% has been obtained by the AIME combining decorate on top tier with bagging on middle tier based on random forest. Practitioners can use these findings to increase the accuracy of CAN diagnosis.

A clustering-based multi-layer distributed ensemble for neurological diagnostics in cloud services

This paper investigates the problem of minimizing data transfer between different data centers of the cloud during the neurological diagnostics of cardiac autonomic neuropathy (CAN). This problem has never been considered in the literature before. All classifiers considered for the diagnostics of CAN previously assume complete access to all data, which would lead to enormous burden of data transfer during training if such classifiers were deployed in the cloud. We introduce a new model of clustering-based multi-layer distributed ensembles (CBMLDE). It is designed to eliminate the need to transfer data between different data centers for training of the classifiers. We conducted experiments utilizing a dataset derived from an extensive DiScRi database. Our comprehensive tests have determined the best combinations of options for setting up CBMLDE classifiers. The results demonstrate that CBMLDE classifiers not only completely eliminate the need in patient data transfer, but also have significantly outperformed all base classifiers and simpler counterpart models in all cloud frameworks.

Secure object tracking protocol for the internet of things

In this paper, we propose a secure object tracking protocol to ensure the visibility and traceability of an object along the travel path to support the Internet of Things (IoT). The proposed protocol is based on radio frequency identification system for global unique identification of IoT objects. For ensuring secure object tracking, lightweight cryptographic primitives and physically unclonable function are used by the proposed protocol in tags. We evaluated the proposed protocol both quantitatively and qualitatively. In our experiment, we modeled the protocol using security protocol description language (SPDL) and simulated SPDL model using automated claim verification tool Scyther. The results show that the proposed protocol is more secure and requires less computation compared to existing similar protocols.

Matrix constructions of centroid sets for classification systems

This article continues the investigation of matrix constructions motivated by their applications to the design of classification systems. Our main theorems strengthen and generalize previous results by describing all centroid sets for classification systems that can be generated as one-sided ideals with the largest weight in structural matrix semirings. Centroid sets are well known in data mining, where they are used for the design of centroid-based classification systems, as well as for the design of multiple classification systems combining several individual classifiers.

The CMS experiment at the CERN LHC

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

From capital surges to drought: seeking stability for emerging economies

Includes bibliography

Hepatitis C Virus NS2 Protein Inhibits DNA Damage Pathway by Sequestering p53 to the Cytoplasm

Chronic hepatitis C virus (HCV) infection is an important cause of morbidity and mortality globally, and often leads to end-stage liver disease. The DNA damage checkpoint pathway induces cell cycle arrest for repairing DNA in response to DNA damage. HCV infection has been involved in this pathway. In this study, we assess the effects of HCV NS2 on DNA damage checkpoint pathway. We have observed that HCV NS2 induces ataxia-telangiectasia mutated checkpoint pathway by inducing Chk2, however, fails to activate the subsequent downstream pathway. Further study suggested that p53 is retained in the cytoplasm of HCV NS2 expressing cells, and p21 expression is not enhanced. We further observed that HCV NS2 expressing cells induce cyclin E expression and promote cell growth. Together these results suggested that HCV NS2 inhibits DNA damage response by altering the localization of p53, and may play a role in the pathogenesis of HCV infection. © 2013 Bitter et al.

Dissecting Phaseolus vulgaris Innate Immune System against Colletotrichum lindemuthianum Infection

Background: The genus Colletotrichum is one of the most economically important plant pathogens, causing anthracnose on a wide range of crops including common beans (Phaseolus vulgaris L.). Crop yield can be dramatically decreased depending on the plant cultivar used and the environmental conditions. This study aimed to identify potential genetic components of the bean immune system to provide environmentally friendly control measures against this fungus. Methodology and Principal Findings: As the common bean is not amenable to reverse genetics to explore functionality and its genome is not fully curated, we used putative Arabidopsis orthologs of bean expressed sequence tag (EST) to perform bioinformatic analysis and experimental validation of gene expression to identify common bean genes regulated during the incompatible interaction with C. lindemuthianum. Similar to model pathosystems, Gene Ontology (GO) analysis indicated that hormone biosynthesis and signaling in common beans seem to be modulated by fungus infection. For instance, cytokinin and ethylene responses were up-regulated and jasmonic acid, gibberellin, and abscisic acid responses were down-regulated, indicating that these hormones may play a central role in this pathosystem. Importantly, we have identified putative bean gene orthologs of Arabidopsis genes involved in the plant immune system. Based on experimental validation of gene expression, we propose that hypersensitive reaction as part of effector-triggered immunity may operate, at least in part, by down-regulating genes, such as FLS2-like and MKK5-like, putative orthologs of the Arabidopsis genes involved in pathogen perception and downstream signaling. Conclusions/Significance: We have identified specific bean genes and uncovered metabolic processes and pathways that may be involved in the immune response against pathogens. Our transcriptome database is a rich resource for mining novel defense-related genes, which enabled us to develop a model of the molecular components of the bean innate immune system regulated upon pathogen attack.