Patients with schizophrenia may exhibit deficiency in the working memory amongst other symptoms like hallucinations and delusions. Functional magnetic resonance imaging (fMRI) is an imaging method that has shown potential in understanding brain activity in psychiatric diseases. However, improved methods for the analysis of fMRI data are continuously evolving. In this direction, group independent component analysis (GICA) has been integrated with the standard statistical measures for feature extraction and selection for classification of working memory task fMRI data. The proposed approach yields high classification accuracy using linear SVM and k-NN classifiers. It also yields different brain regions which are mostly affected by schizophrenia leading to impairment of the working memory of the patients.

The printing technology revolutionized the dissemination of knowledge at a pace never conceived of earlier. In recent times, radio and television brought education within the reach of masses. More recently, the multimedia technology, and Internet have revolutionized the delivery of education. Top universities of the world have collaborated to develop massive open online courses (MOOCs) that are made available to public either free of charge or at a nominal cost. Mainly supported by start-ups such as Coursera, Udacity, and EdX, MOOCs are mostly created by universities in United States and Europe. This essay reviews the impact of these changes on higher education using available reports, articles, and meta-analyses. Although there is no conclusive evidence of the impact of MOOCs, there is a strong possibility of MOOCs leaving a lasting mark on the traditional higher education system. This chapter falls within the book section ‘RIA and education practice of MOOCs,' aligning to the discussion on the topic of ‘educational training design.'

We have identified the following biomarkers (protein and targets) for brain & blood cancer: DNA topoisomearase,Epidermal growth factor, Estrogen receptor, Adenosine deamenase, Receptor protein tyrosine kinase, Arachidonate 5-lipoxygenase and B-Raf protooncogenase\threonineprotein kinase. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics. This demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application. KeywordAdenosine deamenase, Arachidonate 5-lipoxygenase, Biomarker, B-Raf protooncogenase\threonineprotein kinase, ,DNA topoisomearase,Epidermal growth factor, Estrogen receptor, Receptor protein tyrosine kinase.

Massive Open Online Course (MOOC) is an emerging method in online education. Sakai is a popular open source platform widely used by e-learning providers to offer MOOC. Sakai provides a set of collaborative tools for teachers, learners and researchers to support teaching, learning and research. For using Sakai, the e-learning provider needs to customize and adapt the interface of Sakai, like, banner, logo, background color etc. to suit their requirement. This paper presents the development of a tool named SkinChanger that facilitates customizing of Sakai interface, based on need of the e-learning provider. SkinChanger customizes the appearance of Sakai body, header and footer. It facilitates skin changing by providing a user friendly interface. SkinChanger is component-based tool and can be plug-in. This paper illustrates the use of tool to customize the Sakai interface for University of Delhi.

This study has been done on a technique which is suitable for tapping the telephonic conversation from a remote location to identify intoxication and consequent impaired brain activity that may cause criminal events e.g. DUI (driving under influence). This technique is time efficient, easy to use, non–invasive for the peoples and affordable for law enforcement personnel, bartenders/servers, court of law, coworkers/supervisors, clinicians, teachers and individuals who need to identify the presence and level of intoxication state in other peoples. The peaks in log Mel Filter Bank are main cues for identifying the sounds of speech. If a person is found drunk and his/her voice shows a great deal of variation, then this study describes an effective unsupervised method for query-by-audio sample speaker retrieval firstly by extracting MFCC features and then VQ (vector quantization) algorithms on the alcoholic audios. This method is also supported by verifying some speech parameters (fundamental frequency, jitter, shimmer). A set of twelve mel-frequency cepstrum coefficients computed every 10ms and which resulted the best performance i.e. 95% recognition with each of 8 speakers. The superior performance of the mel-frequency cepstrum coefficients may be an attributed to the fact that they better represent the perceptually relevant aspects of the short-terms speech spectrum.

We present an efficient hardware architecture design & implementation of Advanced Encryption Standard (AES) – Rijndael cryptosystem. The AES algorithm defined by the National Institute of Standard and Technology (NIST) of United States has been widely accepted. All the cryptographic algorithms developed can be implemented with software or built with pure hardware. However with the help of Field Programmable Gate Arrays (FPGA) we tend to find expeditious solution and which can be easily upgraded to integrateany concordat changes. This contribution investigates the AES encryption and decryption cryptosystem with regard to FPGA and Very High Speed Integrated Circuit Hardware Description language (VHDL). Optimized and Synthesizable VHDL code is developed for the implementation of both 128bit data encryption and decryption process. Xilinx ISE 10.1 software is used for simulation. Each program is tested with some of the sample vectors provided by NIST and output results are perfect with minimal delay. The synthesis results found from FPGA implementation by Xilinx Synthesis Tool on Virtex II pro kit shows that the computation time for generating the ciphertext by AES with 4 sbox and 2 dual port RAM is 6.922 ns.

Debugging programs at the source level is essential in the software development cycle. With the growing importance of dynamic optimization, there is a clear need for debugging support in the presence of runtime code transformation. This paper presents a framework, called DeDoc, and lightweight techniques that allow debugging at the source level for programs that have been transformed by a trace-based binary dynamic optimizer. Our techniques provide full transparency and hide from the user the effect of dynamic optimizations on code statements and data values. We describe and evaluate an implementation of DeDoc and its techniques that interface a dynamic optimizer with a native debugger. Our experimental results indicate that DeDoc is able to report over 96% of values, that are otherwise not reportable due to code transformations, and incurs less than 1% performance overhead.

Software designers and developers face many problems in designing, building, deploying, and maintaining cutting-edge software applications–reliability,security,performance,power,legacy code,use of multi-core platforms,and maintenance are just a few of the issues that must be considered. Many of these issues are fundamental parts of the grand challenges in computer science such as reliability and security.

— Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules leads to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach based on both objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules (knowledge). We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are promising.

Software dynamic translators have been used for many purposes, such as dynamic code optimization, profiling, and security. Many of these applications need to instrument a program’s binary code to gather run-time information about the program. Such instrumentation is varied, with different software dynamic translator applications requiring different kinds of information. Hence, there is a need for a flexible mechanism for information gathering and instrumentation in software dynamic translators. In this paper, we describe our approach to providing flexible instrumentation. We also experimentally evaluate our approach and investigate its overhead and demonstrate its flexibility for different software dynamic translation

In today's dynamic computing environments, the available resources and even underlying computation engine can change during the execution of a program. Additionally, current trends in software development favor the flexibility and cost-effectiveness of dynamically loaded components and libraries. Because of these trends, there has been increased research interest in virtual execution environments (VEEs) for delivering adaptable software suitable for today's rapidly changing, heterogeneous computing environments. In this project, we have been investigating tools and techniques to support implementation of VEEs using software dynamic translation (SDT). This paper highlights some of our recent results. One significant result is that we have developed novel translation techniques that reduce the memory and runtime overhead of SDT to negligible levels. We have also developed innovative debugging and instrumentation tools for SDT-based software environments. Together, these results make SDT-based systems viable for solving a wide range of pressing problems. The paper concludes with a discussion of how SDT may offer a solution to one such problem-inherent process variation in emerging chip multiprocessors.

Traditional code optimizers have produced significant performance improvements over the past forty years. While promising avenues of research still exist, traditional static and profiling techniques have reached the point of diminishing returns. The main problem is that these approaches have only a limited view of the program and have difficulty taking advantage of the actual run-time behavior of a program. We are addressing this problem through the development of a dynamic optimization system suited for aggressive optimization - using the full power of the most beneficial optimizations. We have designed our optimizer to operate using a software dynamic translation (SDT) execution system. Difficult challenges in this research include reducing SDT overhead and determining what optimizations to apply and where in the code to apply them. Another challenge is having the necessary tools to ensure the reliability of software that is dynamically optimized. In this paper, we describe our efforts in reducing overhead in SDT and efficient techniques for instrumenting the application code. We also describe our approach to determine what and where an optimization should be applied. We discuss other fundamental issues in developing a dynamic optimizer and finally present a basic debugger for SDT systems

With the internet becoming one of the most popular sources of the information, adaptive hypermedia systems (AHS) have moved from ordinary hypermedia systems to adaptive web systems and now they have graduated to adaptive mobile systems. With this change, the requirements have also changed for the systems. We have presented the requirements of an AHS in the form of a hierarchical framework. It takes into consideration the environment of the accessing device, the type and levels of the adaptations provided in AHS and the functionality of AHS. The framework has been used to evaluate and compare two web-based adaptive educational systems.

Dynamic instrumentation systems, used for program analysis, bug isolation, software security and simulations, are becoming increasingly popular. There exists a need to debug dynamically instrumented programs while keeping the presence of dynamic instrumentation system hidden from debug users. Existing debuggers use debug information in program binaries that have been generated by a compiler at static compile time, to provide their debug support. Since dynamic instrumentation systems generate program code at run-time, existing debuggers are not able to provide the same kind of debug support. The most comprehensive existing debug techniques that satisfy this need, used by Tdb, require modification of existing debuggers. This paper provides an OS level approach that silently intercepts the communication between a debugger and the OS and uses a set of debug specifications to provide Tdb's transparent debugging. As a result, any existing debugger can be used to debug dynamically instrumented programs. The proposed techniques have been implemented on x86/Linux platform for the dynamic instrumentation system Pin.

Software dynamic translation (SDT) is a technology for modifying programs as they are running. The overhead of monitoring and modifying a running program’s instructions is often substantial in SDT systems. As a result, SDT can be impractically slow, especially in SDT systems that do not or can not employ dynamic optimization to offset overhead. This is unfortunate since SDT has many advantages in modern computing environments and interesting uses of SDT continue to emerge. In this paper, we describe techniques to reduce the overhead of SDT. In particular, we present a compile-time planning technique to reduce the overhead due to indirect branch handling. Our results show that this technique is very effective and can improve SDT performance by up to 36%, with an average of 20%.

The capability to debug a program at the source level is useful and often indispensable. Debuggers use sophisticated techniques to provide a source view of a program, even though what is executing on the hardware is machine code. Debugging techniques evolve with significant changes in programming languages and execution environments. Recently, software dynamic translation (SDT) has emerged as a new execution mechanism. SDT inserts a run-time software layer between the program and the host machine, providing flexibility in execution and program monitoring. Increasingly popular technologies that use this mechanism include dynamic optimization, dynamic instrumentation, security checking, binary translation, and host machine virtualization. However, the run-time program modifications in a SDT environment pose significant challenges to a source level debugger. Currently debugging techniques do not exist for software dynamic translators. This thesis is the first to provide techniques for source level debugging of dynamically translated programs. The thesis proposes a novel debugging framework, called Tdb, that addresses the difficult challenge of maintaining and providing source level information for programs whose binary code changes as the program executes. The proposed framework has a number of important features. First, it does not require or induce changes in the program being debugged. In other words, programs are debugged is their deployment environment. Second, the framework is portable and can be applied to virtually any SDT system. The framework requires minimal changes to an SDT implementation, usually just a few lines of code. Third, the framework can be integrated with existing debuggers, such as Gdb, and does not require changes to these debuggers. This improves usability and adoption, eliminating the learning curve associated with a new debugging environment. Finally, the proposed techniques are efficient. The runtime overhead of the debugged programs is low and comparable to that of existing debuggers. Tdb's techniques have been implemented for three different dynamic translators, on two different hardware platforms. The experimental results demonstrate that source level debugging of dynamically translated programs is feasible, and our implemented systems are portable, usable, and efficient.

Program instrumentation, inserted either before or during execution, is rapidly becoming a necessary component of many systems. Instrumentation is commonly used to collect information for many diverse analysis applications, such as detecting program invariants, dynamic slicing and alias analysis, software security checking, and computer architecture modeling. Because instrumentation typically has a high run-time overhead, techniques are needed to mitigate the overheads. This paper describes "instrumentation optimizations" that reduce the overhead of profiling for program analysis. Our approach applies transformations to the instrumentation code that reduce the (1) number of instrumentation points executed, (2) cost of instrumentation probes, and (3) cost of instrumentation payload, while maintaining the semantics of the original instrumentation. We present the transformations and apply them for program profiling and computer architecture modeling. We evaluate the optimizations and show that the optimizations improve profiling performance by 1.26-2.63x and architecture modeling performance by 2-3.3x.