Miracle-dz/UniFAR-FTUs huggingface dataset:
The development of an integrated framework in order to address King III's IT governance principles at a strategic level

In today’s technologically advanced business environments, Information Technology (IT) has become the center of most businesses’ strategic activities. It is for this reason that the King III report has dedicated a chapter to addressing IT governance principles, holding the board of directors (senior management) responsible for addressing such principles. The King III report does provide broad level guidance, however lack sufficient detail on its interpretation. Although various guidelines in the form of IT control frameworks -models and -standards exist, it remains theoretical in nature and companies tend to implement these guidelines in an ad hoc manner. This ad hoc implementation of controls leads to unnecessary controls being implemented, resulting in an ineffective IT governance system that does not address each key strategic risk area. The objective of this research is to develop an integrated best practices framework, which will provide guidance to senior management in how to effectively and efficiently address King III’s IT governance principles by taking a business’ unique strategic objectives into account. A detailed literature review was performed of different control frameworks,-models and standards. These were analysed to identify a list of similar and overlapping control areas. These control areas were thereafter mapped to a list of strategic objectives applicable to most businesses. In doing so, effective and efficient IT governance principles which are understood by senior management, are able to be implemented.
Impact of scattering on the performance of a Si GAA nanowire FETs: From diffusive to ballistic regime

In this paper we study the effect of the phonon scattering in Silicon nanowire transistors using a Non equillibrium Green Function Formalism. We consider a wide range of channel lengths from 6 to 40 nm in 2.2×2.2 nm2 cross section devices. We study the reduction in drain current due to scattering in these devices and extract the phonon-limited mobility. We also show the impact of the scattering in the channel and the source and drain regions and their contribution to the total current degradation, showing that for short gate length transistors most of the impact of the phonons comes from the source and drain regions.
Abstraction of On-Board Resources in Mobiles: SAaaS4Mobile, a First Step towards a Sensing Cloud

Through the Sensing and Actuation as a Service (SAaaS) we aim at implementing a sensing Cloud by enrolling and aggregating sensing resources from sensor networks and personal, mobile devices. We follow a device-driven approach, as adopted in IaaS Clouds: once collected, the physical (sensing) resources are abstracted and virtualised and then provided as a service to end users. A key point of the SAaaS is the abstraction of resources, i.e. providing a uniform way to access to and interact with the underlying physical nodes. In this paper we focus on the sensing resource abstraction in SAaaS, providing details on theoretical and design aspects as well as on technical and implementation ones. In particular, an implementation of the SAaaS abstraction layers for mobiles (SAaaS4mobile) is reported, giving adequate architectural descriptions of the main SAaaS4mobile modules and detailing the actual implementation of such modules for Android-powered mobiles.
Usability evaluation to an eLearning course presenting a regional destination. The case of "Ticino Switzerland travel specialist".

In recent years Destination Management Organizations (DMOs) have started to offer eLearning courses, which train travel agents and tour operators to promote better tourism destinations. eLearning courses increase marketing activities of a DMO also they meet the needs of travel agents, who are in search of new unique selling points in the threatening context of eTourism disintermediation. Nevertheless, the user-friendly appearance of these eLearning courses and their easiness of use are still a challenge within the tourism industry. This paper introduces such a course, offered by a Swiss regional DMO, and presents its evaluation through a usability testing. Based on such a procedure, found usability issues were marked, implemented, then course has been released in beta version.
Two problems with variational expectation maximisation for time-series models

Variational methods are a key component of the approximate inference and learning toolbox. These methods fill an important middle ground, retaining distributional information about uncertainty in latent variables, unlike maximum a posteriori methods (MAP), and yet generally requiring less computational time than Monte Carlo Markov Chain methods. In particular the variational Expectation Maximisation (vEM) and variational Bayes algorithms, both involving variational optimisation of a free-energy, are widely used in time-series modelling. Here, we investigate the success of vEM in simple probabilistic time-series models. First we consider the inference step of vEM, and show that a consequence of the well-known compactness property of variational inference is a failure to propagate uncertainty in time, thus limiting the usefulness of the retained distributional information. In particular, the uncertainty may appear to be smallest precisely when the approximation is poorest. Second, we consider parameter learning and analytically reveal systematic biases in the parameters found by vEM. Surprisingly, simpler variational approximations (such a mean-field) can lead to less bias than more complicated structured approximations.
Imperfect Competition and the Dynamics of Mark-Ups

This paper investigates the behaviour of the mark-up of prices over marginal costs under two different assumptions about market structure. In the customer market model firms lower their mark-up when current output is low relative to future profits, foregoing current profits in order to capture future market share. In markets characterised by implicit collusion, firms lower their mark-ups when current output is high relative to future profits in order to lower the incentives to undercut the implicit cartel. Only the customer market model generates predictions consistent with UK evidence, but this in inconsistent with evidence from the United States. It may be necessary to use more than one model to explain all the facts.
A Review of the Influence of User Involvement on System Success

User involvement in the system design process and the final success of a system has been the subject of many studies. Conflicting results reported in those studies have not helped to resolve the issue. This study employs meta-analysis to systematically combine the results of many user involvement studies to see if the overall results are significant. In addition, the strength of the relationship between user involvement and system success is also developed. The dependent variables in the underlying studies were combined to form two global variables: attitude and reported behavior. All of the relationships between various types of involvement and different measures of success yielded significant results.
Global Crises from the Perspective of Complex Adaptive Systems

i) Complete control of CAS is impossible. Hence the decisions should instead be guidelines. Detailed plans should be left to those executing them. ii) Expect some failures. Hence continuous revision and updating are required. iii) There is no single solution but multi-solutions that accommodate the different contradictory objectives. iv) Diversity should be preserved and encouraged. v) Transparency and trust have to exist. vi) Decisions can result only after serious consultations with those executing them and those affected by them (bottom-up approach). vii) Deserved decentralization should be encouraged.
A new reduced-rank STAP method based on cross spectral defined by range cell echo

In the cross spectral method (CSM), the cross spectral is defined by space-time steering vector. One character of the method is that the cross spectral should be calculated and arranged in every angle-Doppler cell, so it has a great burden of calculation. A new reduced-rand (RR) STAP method is developed in this paper, the cross spectral is defined by the echo data of a range cell, instead of the steering vector. In the new method the cross spectral is calculated and arranged only one time for each range cell, so it greatly decreases the burden of calculation. It is proved in theory that the new method has a good clutter suppression performance as well. The result of simulation shows the good efficiency of the method.
Monetary Rules for Emerging Market Economies

We compare the performance of a currency board arrangement, inflation targeting, and dollarization in a small open, developing economy with liberalized capital account. We focus explicitly on the transmission of shocks to currency and country risk premia in international financial markets and on the role of fluctuations in premia in the propagation of other shocks. We calibrate our model on Argentina. The framework fits the data relatively well in that it matches the second moments of several key macro variables. Welfare analysis suggests that dollarization is preferable to the alternative regimes we consider because it removes the volatility that originates from the currency premium. However, a currency board can match dollarization if the central bank holds a sufficiently large stock of foreign reserves on average.
Multi-layered architecture of middleware for ubiquitous robot

This paper proposes a multi-layered architecture of middleware for ubiquitous robots. Ubiquitous robots consist of different platforms with various functions and interfaces. Without a middleware, software agents have to hold information of all ubiquitous robots in advance to access other sensors or mobile robots. This decreases modularity and scalability of the entire system, therefore makes it difficult to develop and maintain software agents. The proposed architecture uses context information to decouple hardware and software agents as a bridge between them. Providing context-awareness to the middleware, software agents is able to get context information without accessing physical sensors directly, so that modularity and scalability are increased. Not only providing context information to software agents, the middleware uses mobile robots to gather as much sensor information as possible to generate context information actively. A middleware architecture is proposed with five layers classified due to device/environment dependencies, which are physical layer, device management layer, context provider and mobile robot (Mobot) scheduler layer, software robot (Sobot) management layer and software agent layer. The proposed middleware is implemented and simulated with virtual sensors in the virtual environment.
Nonuniform sampling and reconstruction for high resolution satellite images

The objective of nonuniform sampling methods in image processing is to represent an image with a low number of samples while preserving its content. This paper proposes an adaptive nonuniform sampling algorithm for high-resolution satellite images. The idea is that more samples are selected around the edges thanks to the measure of the local skewness, and that few samples are placed in regions containing low-frequency features. The Delaunay triangulation method has been developed to reconstruct the image from nonuniform samples. The results of the reconstruction show that the proposed algorithm can obtain a similar image quality with fewer samples, which is valuable for high-resolution satellite image transmission and storage system.
Occasional Papers Systematics of Small Anoura (chiroptera: Phyllostomidae) from Colombia, with Description of a New Species

We analyzed the morphological variation of short tailless bats, Anoura, from Colombia in order to determine their phylogenetic affinities and to define their geographic structure. Our analysis confirmed the presence of A. caudifer aequatoris (Lönnberg 1921) as well as A. luismanueli (Molinari 1994) in Colombia and delimited their distributions in the country. Based on morphological and distributional differences between A. caudifer caudifer and A. c. aequatoris, we proposed the elevation of A. aequatoris to specific level. As a result of our morphological and geographic analyses we documented the presence in Colombia of an undescribed species of Anoura, A. cadenai, which is described in the present work.
Comparison between Nearest Neighbours and Bayesian Network for demand forecasting in supply chain management

Machine Learning has found to be playing a significant role in solving issue of demand forecasting in supply chain management, where many traditional methods result in substandard accuracies. There is a high demand of robust computational systems for predicting the trends of demands for the purpose of Inventory Management in supply chain management of an organization. Every organization has Terabytes of transactions and shipments data. These terabytes of data help in defining and implementing robust techniques that can help in identifying stochastic dependency in the historical data to determine future trends. Attributes like Consignee address, shipper, shipper address, place of delivery, weight of container and country are important for prediction supply trends. Naïve Bayes classifier is used to make decision in uncertainty and K nearest neighbor is lazy and supervised learning algorithm to determine the trends in supply chain. The purpose of this research is to bring a close comparison between Nearest Neighbor Algorithm and Bayesian Networks using confusion matrix as a performance metric and Walmart dataset has been used for simulation. The results show that Bayesian networks technique surpasses the Nearest Neighbor technique in detecting relations in dataset for prediction demand in supply chain. Bayesian networks, emerges to be robust in demand prediction instead of increasing K-neighbors in the supervised learning algorithm.
Intelligent video content routing in a direct access network

The video content is growing rapidly in the Internet. This demand has raised a great deal of challenges. One of the crucial problems is to figure out an efficient content routing approach to quickly find and transport right titles to users. This paper presents a direct access network (DAN) which can automatically fetch interesting subject to the users' community in their local network. Our solution can not only optimize the Internet traffic and offer user fluent watching experience but also provide the Omega Point, a fast addressing mechanism to find the requested movies. The effect of the algorithm is also evaluated in the paper.
Turning Graduate School Aspirations into Enrollment: How Student Affairs Professionals Can Help African American Students

The purpose of this qualitative study was to highlight the relationship between student affairs professionals and African American students who are considering pursuing doctoral degree programs. The data were interpreted through Sanfordâ€™s (1966) conceptualization of challenge and support. Findings reveal that African American students form meaningful relationships with student affairs professionals that both challenge and support their pursuit of the doctorate. Implications for research and practice are discussed.
Volatility Matters: Taylor Rules and Capital Accumulation

The operational performance of a set of simple monetary pol- icy rules a la Taylor in a model with capital accumulation and nominal and real rigidities is discussed with a special emphasis on the volatility of output, nominal rate and in.ation rate. Within an enriched modelling framework it is shown that output targeting plays a more crucial role than what has been assessed in the current literature for models without capital accumulation. In fact, with a small value of the output targeting coefficient, monetary authority is not completely successfull in stabilizing the volatility of output, nominal rate and inflation rate only by acting on inflation targeting. Moreover, a too strong concerns towards inflation relatively to output translates into a lower ability to control inflation volatility, together with a strong policy reaction with respect to an exogenous shock hitting the economy. Im- pulse response analysis shows that the risk of an excessive concerns towards inflation might end up in counterproductive results on output, after a positive technological shock. The model also shows a better internal propagation mechanism than what has been previously showed. Finally, the results show that it is no longer possible to miss capital accumulation in modelling monetary policy analyses and calls for further generalizations of the existing modelling framework.
Rollerchain: a DHT for high availability

This paper presents Rollerchain, a novel Distributed Hash Table that offers high availability of stored data in an efficient manner through the combination of unstructured and structured overlay networks. The unstructured component maintains clusters of fully connected nodes, where each cluster acts as a virtual node in the structured component. We have implemented a prototype of Rollerchain that we have used to experimentally validate its better resilience and reduced costs when compared with other state of the art solutions.
High Precision Neural Decoding of Complex Movement Trajectories Using Recursive Bayesian Estimation With Dynamic Movement Primitives

Brain-machine interfaces (BMIs) are a rapidly progressing technology with the potential to restore function to victims of severe paralysis via neural control of robotic systems. Great strides have been made in directly mapping a user's cortical activity to control of the individual degrees of freedom of robotic end-effectors. While BMIs have yet to achieve the level of reliability desired for widespread clinical use, environmental sensors (e.g., RGB-D cameras for object detection) and prior knowledge of common movement trajectories hold great potential for improving system performance. Here, we present a novel sensor fusion paradigm for BMIs that capitalizes on information able to be extracted from the environment to greatly improve the performance of control. This was accomplished by using dynamic movement primitives to model the 3-D endpoint trajectories of manipulating various objects. We then used a switching unscented Kalman filter to continuously arbitrate between the 3-D endpoint kinematics predicted by the dynamic movement primitives and control derived from neural signals. We experimentally validated our system by decoding 3-D endpoint trajectories executed by a nonhuman primate manipulating four different objects at various locations. Performance using our system showed a dramatic improvement over using neural signals alone, with median distance between actual and decoded trajectories decreasing from 31.1 to 9.9 cm, and mean correlation increasing from 0.80 to 0.98. Our results indicate that our sensor fusion framework can dramatically increase the fidelity of neural prosthetic trajectory decoding.
Undergraduate Education at Computer Science Department

The Computer Science (CS) Department of the University of California, Riverside (UCR) has a unique and diverse group of both students and faculty. The CS student body ranges in ethnicity, gender, and most importantly, their ability. As teaching assistants, it is our job to understand and leverage our positions as leaders and teachers, and to encourage growth and understanding of a given subject matter. In this report, we will discuss various strengths and weaknesses of the CS department and present suggestions for possible improvements. We present real world experiments to test and validate our conclusions.
Using Wireless Sensor Networks for Precision Irrigation Scheduling

Worldwide, irrigation uses about 69% of available freshwater resources (Fry, 2005). In the United States, 82% of freshwater resources are used for irrigation purposes. Major concerns on future planetary freshwater resources are the effects of climate change on changing sea temperature and levels, annual snowpack, drought and flood events, as well as changes in water quality, and general ecosystem vulnerabilities (US Global Change Research Program, 2011). Changes in the extreme climatic events are more likely to occur at the regional level than show in national or global statistics. The unpredictability of climatic events is of key concern to farmers in all countries, since the availability and cost of irrigation water is likely to be compounded by increased regulations and competition. Over the past 50 years, the urban demand for freshwater in the United States has also been increasing (Hutson et al. 2004), while the quality of both surface and groundwater has been decreasing due to pollution from both point and nonpoint sources (Secchi et al. 2007). Nitrogen, phosphorus and many other inorganic and organic pollutants such as pesticides and herbicides are being found at increasing concentrations in groundwater under agricultural areas (Guimera, 1998). As demands on water and the cost of purification increase, the cost of freshwater resources will increase and the availability will likely decrease for agriculture. Population growth in the 20th century increased by a factor of three while water withdrawals increased by a factor of seven during the same time, with little hope of these rates slowing in the near future (Agarwal et al. 2000).
Effects of polyamines on the thermal stability and formation kinetics of DNA duplexes with abnormal structure.

The effects of ions (i.e. Na+, Mg2+ and polyamines including spermidine and spermine) on the stability of various DNA oligonucleotides in solution were studied. These synthetic DNA molecules contained sequences that mimic various cellular DNA structures, such as duplexes, bulged loops, hairpins and/or mismatched base pairs. Melting temperature curves obtained from the ultraviolet spectroscopic experiments indicated that the effectiveness of the stabilization of cations on the duplex formation follows the order of spermine > spermidine > Mg2+ > Na+ > Tris-HCl buffer alone at pH 7.3. Circular dichroism spectra showed that salts and polyamines did not change the secondary structures of those DNA molecules under study. Surface plasmon resonance (SPR) observations suggested that the rates of duplex formation are independent of the kind of cations used or the structure of the duplexes. However, the rate constants of DNA duplex dissociation decrease in the same order when those cations are involved. The enhancement of the duplex stability by polyamines, especially spermine, can compensate for the instability caused by abnormal structures (e.g. bulged loops, hairpins or mismatches). The effects can be so great as to make the abnormal DNAs as stable as the perfect duplex, both kinetically and thermodynamically. Our results may suggest that the interconversion of various DNA structures can be accomplished readily in the presence of polyamine. This may be relevant in understanding the role of DNA polymorphism in cells.
TOWARDS MAXIMIZING THROUGHPUT FOR MULTITHREADED PROCESSES IN LINUX

CPU scheduler is a very important key concept in operating system which affects scheduling objectives and criteria. Choosing or modifying scheduling policy for running threads depends on predefined and specific objectives and criteria. In this paper, we investigate the effectiveness of thread weight readjustment scheduler (TWRS) for multithreaded processes in multitasking operating systems from the view point of throughput. TWRS is a proportional share CPU scheduler designed for scheduling multithreaded processes. In this work, we make change kernel performance significantly by modifying just few key parameters. We propose TWRS which preallocates certain amount of CPU time to each thread of the multi-threaded processes. The scheduler was implemented and evaluated under specific hardware and software environment. According to our evaluation results, our scheduler is promising to optimize some scheduling criteria.