Impact of Assurance of Learning (AOL) in programming course for novices

One of the aims of any higher education institution is to align its curriculum with program learning goals. Programs which ensure proper learning have positive effects on students, instructors, departments and also on the higher education institution itself. This paper discusses the implementation and effects of Assurance Of Learning (AOL) processes on introductory programming (IP) courses. It elaborates five stages of AOL to align program learning goals with IP curriculum. Then, it discusses how the AOL process identifies shortcomings in the assessment methods of IP courses. Furthermore, it enlightens how the assessment findings, as a result of the AOL process, provide mechanisms to address the drawbacks during the delivery of such courses. Feedback on

Scenarios for an RFID tag ownership transfer protocol for a closed loop system

In RFID system a tag is attached to an object which might own by a number of owners during its life time. This requires the RFID system to transfer ownership of the tag to its new owner. The ownership transfer has to protect privacy of current and new owner. Many ownership tag ownership transfer exists in the literature, however, most of them are impractical or insecure to implement on current passive RFID tags. We are proposing a timer based ownership transfer protocol for closed loop RFID systems. The proposal in this paper includes two implement scenario to cover diverse tags type. The protocol will ensure security and privacy of involved parties in the idle circumstances. Our comparison shows that the proposed protocol is more secure and practical than existing similar ones.

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.

Steno cipher to provide data confidentiality and tampered data recovery for RFID tag

Radio Frequency Identification (RFID) is an emerging wireless object identification technology with many potential applications such as supply chain management, personnel tracking and healthcare. However, security vulnerabilities of the RFID system have been a serious concern for its wide adoption in many applications. Although much work has been done to provide privacy and anonymity, little focus has been given to ensure RFID data confidentiality, integrity and to address the tampered data recovery problem. To this end, we propose a lightweight stenographic-based approach to ensure RFID data confidentiality and integrity as well as the recovery of tampered RFID data. © 2013 Springer-Verlag Berlin Heidelberg.

Security framework and protocols for the internet of things

This study was conducted to protect security of human beings and businesses from intruders in the context of IoT which is next generation internet. We have developed a universal framework and a number of communication protocols to provide security that will make IoT cyber world safer for all t users.