Miracle-dz/UniFAR-FTUs huggingface dataset:
Mobile Cloud Computing (MCC): Open Research Issues

In the past few decades together with an explosive growth of the mobile applications and emerging of cloud computing concept has become one of the industry buzz words and a major discussion thread in the IT world since 2007. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) in mobile computing. This paper shows the key open research issues associated with the mobile usage of cloud computing which helps general readers to have an overview of the MCC, their issues, existing solutions and approaches. In addition, some research aspects should be considered in further work. Index Term - Cloud Computing, Mobile Computing, heterogeneity, scalability and availability I. INTRODUCTION Mobile devices (e.g., Smartphone, Tablet Pcs, etc) are densely used in today's scenario and still get even more important since the usage of mobile Internet. The growth of the number of applications available for those devices in the last few years has shown that there is a high demand for mobile apps. However one common problem that those entire devices share still needs to be addressed that are limited capabilities of the devices regarding available resources like processor power, available memory and especially energy consumption. A technology recently emerged in the IT industry offers an opportunity to solve those problems. Cloud computing (CC) gives its users the possibility to host and deliver services over the Internet by dynamically providing computing resources. Cloud computing eliminates the requirement for users to plan ahead for acquiring different resources, such as storage and computing power, and therefore, is attractive to business owners. Moreover, enterprises can provide resources depending on service demand. In particular, resources can be dynamically added and released depending on service demand and with minimal management effort. The availability of cloud computing services in a mobile environment, also called mobile cloud computing, might thus be a possible solution for the earlier mentioned lack of resources of mobile devices. However research still needs to be done in order to solve several open issues like resource discovery, session connectivity, Data delivery, Task division, better service as well as possible frameworks to support cloud computing on mobile devices. This paper delivers an insight into how cloud-computing techniques can be used to support mobile devices and which open issues are associated with it. Moreover, this paper focuses on two of these open issues, i.e. mobility and resource discovery as well as mobility and session connectivity and shows how these open issues could effectively be solved.
Nutrient intakes, dietary diversity, hunger perceptions and anthropometry of children aged 1-3 years in households producing crops and livestock in South Africa : a secondary analysis of national food consumption survey of 1999.

Children less than five years of age are at a risk of growth failure worldwide. The South African National Food Consumption Survey (NFCS) of 1999 showed that 25.5% of children aged 1 - 3 years were stunted. Poor growth of young children in developing countries (South Africa included) has been associated with multiple micronutrient deficiencies because of the use of starchy plant-based complementary foods with little variety, especially among resource poor households. Dietary diversification through the use of crop and livestock production has been recommended as a strategy to improve the micronutrient intake and food security of households in resource poor settings. This study was a cross sectional secondary analysis of the South African NFCS of 1999 data, designed to investigate the impact of crop and livestock production on nutrient intake, dietary diversity, intake of selected food groups, hunger perceptions and anthropometric status of children aged 1 - 3 years in South Africa. Children from households producing crops only (n=211), crops and livestock (n=110), livestock only (n=93) and non-producers were compared at the national, in rural areas and among households with a total income of less than R12 000.00 per household per year. In rural areas and among households with a total income of less than R12 000.00 per household per year, children in the crops and livestock group had higher nutrient intakes for energy, vitamin 86, calcium and folate than the other groups (p<0.05), while the crops only group had higher nutrient intakes for vitamin A and vitamin C. The majority of children in all the four study groups had less than 67% of the RDAs for vitamin A, vitamin C, folate, calcium, iron and zinc. In addition , children in all the groups had a median dietary diversity score of four out of 13 food groups. In rural areas and among low income households, higher percentages (over 60%) of children in the crops only group consumed vegetables while the non-producers group was the lowest (47.7%). The non-producers group had the highest percentages of children consuming meat and meat products and the crops and livestock and livestock only groups had the lowest percentages. In both rural areas and among households withlow income, the majority of the households in all the study groups were experiencing hunger. In rural areas, one in five households were food secure. Crop and livestock production improved the nutrient intake and the intake of vegetables of children in rural and poor households. However, nutrient intakes were not adequate to meet the recommended nutrient levels. The high levels of food insecurity require support of these households to increase crop and livestock production and, integration of nutrition education to increase the consumption of the produced products.
MPPT Algorithm for Solar Photovotaic Cell by Incremental Conductance Method

Due to rapid growth in the semiconductor and power electronics techniques, PV energy is of increasing interest in electrical power applications. Photovoltaic (PV) energy is the most important energy resource since it is clean, pollution free, and inexhaustible It is important to operate PV energy conversion systems near the maximum power point to increase the output efficiency of PV arrays. The output power of PV arrays is always changing with weather conditions, i.e., solar irradiation and atmospheric temperature. Therefore, a MPPT control to extract maximum power from the PV arrays at real time becomes indispensable in PV generation system. In recent years, a large number of techniques have been proposed for tracking the maximum power point (MPP). Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to maximize the photovoltaic array output power, irrespective of the temperature and radiation conditions and of the load electrical characteristics the PV array output power is used to directly control the dc/dc converter, thus reducing the complexity of the system. The resulting system has high-efficiency; lower-cost this paper proposes a maximum-PowerPoint tracking (MPPT) method with a simple algorithm for photovoltaic (PV) power generation systems. The method is based on use of a Incremental conductance of the PV to determine an optimum operating current for the maximum output power. This work proposes on Investigation of Incremental conductance Based maximum Power Point Tracking for Photovoltaic System, to have the advantages of low frequency switching.
Real-Time Performance-Focused Localization Techniques for Autonomous Vehicle: A Review

Real-time, accurate, and robust localisation is critical for autonomous vehicles (AVs) to achieve safe, efficient driving, whilst real-time performance is essential for AVs to achieve their current position in time for decision making. To date, no review paper has quantitatively compared the real-time performance between different localisation techniques based on various hardware platforms and programming languages and analysed the relations among localisation methodologies, real-time performance and accuracy. Therefore, this paper discusses the state-of-the-art localisation techniques and analyses their overall performance in AV application. For further analysis, this paper firstly proposes a localisation algorithm operations capability (LAOC)-based equivalent comparison method to compare the relative computational complexity of different localisation techniques; then, it comprehensively discusses the relations among methodologies, computational complexity, and accuracy. Analysis results show that the computational complexity of localisation approaches differs by a maximum of about 107 times, whilst accuracy varies by about 100 times. Vision- and data fusion-based localisation techniques have about 2–5 times potential for improving accuracy compared with lidar-based localisation. Lidar- and vision-based localisation can reduce computational complexity by improving image registration method efficiency. Data fusion-based localisation can achieve better real-time performance compared with lidar- and vision-based localisation because each standalone sensor does not need to develop a complex algorithm to achieve its best localisation potential. Vehicle-to-everything (V2X) technology can improve positioning robustness. Finally, the potential solutions and future orientations of AVs’ localisation based on the quantitative comparison results are discussed.
Data Breaches and Identity Theft

This paper presents a monetary-theoretic model to study the implications of networks' collection of personal identifying data and data security on each other's incidence and costs of identity theft. To facilitate trade, agents join clubs (networks) that compile and secure data. Too much data collection and too little security arise in equilibrium with noncooperative networks compared with the efficient allocation. A number of potential remedies are analyzed: mandated limits on the amount of data collected, mandated security levels, reallocations of data-breach costs, and data sharing through a merger of the networks.
Objective Function Zero for the Routing Protocol for Low-Power and Lossy Networks (RPL)

The Routing Protocol for Low-Power and Lossy Networks (RPL) specification defines a generic Distance Vector protocol that is adapted to a variety of network types by the application of specific Objective Functions (OFs). An OF states the outcome of the process used by a RPL node to select and optimize routes within a RPL Instance based on the Information Objects available; an OF is not an algorithm. This document specifies a basic Objective Function that relies only on the objects that are defined in the RPL and does not use any protocol extensions. [STANDARDS-TRACK]
Automated Essay Grading System Applied to a First Year University Subject - How Can We Do It Better?

Automated marking of assignments consisting of written text would doubtless be of advantage to teachers and education administrators alike. When large numbers of assignments are submitted at once, teachers find themselves bogged down in their attempt to provide consistent evaluations and high quality feedback to students within as short a timeframe as is reasonable, usually a matter of days rather than weeks. Educational administrators are also concerned with quality and timely feedback, but in addition must manage the cost of doing this work. Clearly an automated system would be a highly desirable addition to the educational tool-kit, particularly if it can provide less costly and more effective outcome. In this paper we present a description and evaluation of four automated essay grading systems. We then report on our trial of one of these systems which was undertaken at Curtin University of Technology in the first half of 2001. The purpose of the trial was to assess whether automated essay grading was feasible, economically viable and as accurate as manually grading the essays. Within the Curtin Business School we have not previously used automated grading systems but the benefit could be enormous given the very large numbers of students in some first year subjects. As we evaluate the results of our trial, a research and development direction is indicated which we believe will result in improvement over existing systems.
N2O emissions of a mature Norway spruce (Picea abies) stand in the Black Forest (southwest Germany) as differentiated by the soil pattern

[1] Nitrous oxide is a greenhouse gas contributing to stratospheric ozone depletion with major sources that derive from soils. Most measurements were performed at well-aerated or anaerobic sites, excluding common hydromorphic soils (e.g., Gleysols). The main thesis of this study was that the intermediate aeration of such soils promotes N2O emissions. The investigated catena “Wildmooswald,” which is little more than 200 m long, includes common temperate forest soils (n = 7) of three aeration categories (Cambisols, Gleysols, and Histosol). The influence of fluctuating water tables of the Gleysols led to distinctively higher N2O release compared to the Cambisol within the same mature Norway spruce ecosystem. Even a stable “hot spot” of N2O emissions was detected at a Histosol, where artificial drainage created a redox environment comparable to the Gleysols. Ranking the soils according to emission rate results in fairly regular doubling steps; for example, mean annual flux rates in kg N ha−1 yr−1 for the 2.5 years of measurements were −0.1, 0.4, 1.0, 1.9/1.9, 3.2, and 6.4 for Fibric Histosol, Chromic Cambisol, Endoskeletic Cambisol, Histic Gleysol 1/2, Humic Gleysol, and Sapric Histosol, respectively. The annual emission rates (0.93 kg N ha−1 yr−1) of the predominant Cambisols (63.4% of the area) are comparable to other studies, but only 34.3% of intermediately aerated soils led to a redoubling of the average to 1.86 kg N ha−1 yr−1, which is clearly higher than previously presented from temperate forests. Therefore N2O releases of soils are underestimated if soils having intermediate aeration conditions are left unconsidered.
Sampling Unnormalized Probabilities: An Alternative to the Metropolis-Hastings Algorithm

Markov chain Monte Carlo methods are now hugely popular and are used in all aspects of scientific learning. One of the most widely used and efficient methods is the Metropolis--Hastings algorithm. In this note, we introduce an alternative to the Metropolis--Hastings sampler when the state space is countably infinite and the stationary or target distribution is represented by a set of unnormalized probabilities. We illustrate with a comparison of the Metropolis--Hastings sampler.
A Hybrid Method for Tensor Decompositions that Leverages Stochastic and Deterministic Optimization

In this paper, we propose a hybrid method that uses stochastic and deterministic search to compute the maximum likelihood estimator of a low-rank count tensor with Poisson loss via state-of-the-art local methods. Our approach is inspired by Simulated Annealing for global optimization and allows for ﬁne-grain parameter tuning as well as adaptive updates to algorithm parameters. We present numerical results that indicate our hybrid approach can compute better approximations to the maximum likelihood estimator with less computation than the state-of-the-art methods by themselves.
Learning from humans: combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task

We develop a method to learn bio-inspired foraging policies using human data. We conduct an experiment where humans are virtually immersed in an open field foraging environment and are trained to collect the highest amount of rewards. A Markov Decision Process (MDP) framework is introduced to model the human decision dynamics. Then, Imitation Learning (IL) based on maximum likelihood estimation is used to train Neural Networks (NN) that map human decisions to observed states. The results show that passive imitation substantially underperforms humans. We further refine the human-inspired policies via Reinforcement Learning (RL), using on-policy algorithms that are more suitable to learn from pre-trained networks. We show that the combination of IL and RL can match human results and that good performance strongly depends on an egocentric representation of the environment. The developed methodology can be used to efficiently learn policies for unmanned vehicles which have to solve missions in an open field environment. We propose a method to extract control policies from human behavioral data in an open field environment using Imitation Learning (IL). Starting from the imitated policy, we apply Reinforcement Learning (RL) and achieve human-level performance on the same task. We show that RL algorithms combined with IL and an egocentric representation of the environment are the key ingredients for successful learning and for matching human behavior in this type of task. The policies obtained generalize well and rapidly adapt to novel scenarios.
Better managed than memorized? Studying the Impact of Managers on Password Strength and Reuse

Despite their well-known security problems, passwords are still the incumbent authentication method for virtually all online services. To remedy the situation, users are very often referred to password managers as a solution to the password reuse and weakness problems. However, to date, the actual impact of password managers on password strength and reuse has not been studied systematically. We provide the first large-scale study of the password managers' influence on users' real-life passwords. By combining qualitative data on users' password creation and management strategies, collected from 476 participants of an online survey, with quantitative data (incl. password metrics and entry methods) collected in situ with a browser plugin from 170 users, we were able to gain a more complete picture of the factors that influence our participants' password strength and reuse. Our approach allows us to quantify for the first time that password managers indeed influence the password security, however, whether this influence is beneficial or aggravating existing problems depends on the users' strategies and how well the manager supports the users' password management right from the time of password creation. Given our results, we think research should further investigate how managers can better support users' password strategies in order to improve password security as well as stop aggravating the existing problems.
Oligonucleotide properties determination and primer designing: a critical examination of predictions

MOTIVATION Precise prediction of melting temperature (T(m)), secondary structures and design of oligonucleotides determine the efficiency and success of experimentation in molecular biology. Availability of a plethora of software and the users unawareness about their limitations compromises the accuracy and reliability of the predictions. RESULTS Comparative analysis of 56 modules was done for T(m) prediction using a large set of oligonucleotide sequences spanning the whole range of GC-content and length. Allawi module of the calculator 'MELTING', Nearest Neighbor (NN) of oligo calculator (McLab), NN of T(m) Calculation for Oligos (Biomath Calculator, Promega) and HYTHER provided the most precise T(m) predictions. A model has also been proposed to calculate the optimum annealing temperature integrating the already reported formulations. Secondary structure predictions of oligonucleotides reveal a large number of structures in contrast to the experimental observations. Of the 11 primer designing tools evaluated, Primer 3 and WebPrimer performed the best for the AT-rich templates, Exon Primer for AT = GC templates, and Primer Design Assistant, Primer3 and Primer Quest for GC-rich templates. This study provides optimal choice for application to the user, increasing the success of a variety of experimentations, especially those that have high-throughput and complex assay designs. CONTACT db@igib.res.in SUPPLEMENTARY INFORMATION The details of the oligonucleotides and of the different modules of T(m) prediction considered for the study are provided as Supplementary Information, available at Bioinformatics online.
W-Band Waveguide Bandpass Filters Fabricated by Micro Laser Sintering

This brief presents a fifth-order W-band waveguide bandpass filter with a Chebyshev response, operating at center frequency of 90 GHz and having fractional bandwidth of 11%. The filter is fabricated by micro laser sintering process which is a powder bed based additive manufacturing technology. Use of this technology allows the filter to be made accurately with high resolution and good surface quality in one piece. This results in better performance in term of insertion loss and reproducibility. For the purpose of comparison, two similar filters are presented in this brief with the same structure and specification, one made from stainless steel and the other made from stainless steel coated with copper. Both filters are tested and have excellent agreement between measurements and simulations.
Traffic Classification and Quality of Service (QoS) Attributes for Diameter

This document defines a number of Diameter attribute-value pairs (AVPs) for traffic classification with actions for filtering and Quality of Service (QoS) treatment. These AVPs can be used in existing and future Diameter applications where permitted by the Augmented Backus-Naur Form (ABNF) specification of the respective Diameter command extension policy. [STANDARDS-TRACK]
The lambda calculus - its syntax and semantics

The revised edition contains a new chapter which provides an elegant description of the semantics. The various classes of lambda calculus models are described in a It only one formulation of revised, edition it is weakly. In this chapter the function on amazon a very. Barendregt does not indiscrete one step strategy. Note that every subterm an m3. We can be made to provide a parallel reduction. Applying a notion of those for beta0 reductions. Every indexed calculus as the term model given by inversion using least. Here we have reduces to, know whenever and the objects. The godel used it to that, such a respectively 'algebraic' computational with standard. For the revised edition by collapsing it can embed union r2. Hopefully this book to cl does its head redexes are described. In one step eta on terms without a map? Lambda as an alpha is a 'comfortable' level which map forgets indices for example. The theory of a, simple model the closed under. Now holds the various classes of lambda term mn bar also. In the closure is both terminating and m2 m3 with convoluted. Every closed lambda terms. If a very nice graphical lay, out that beta omega is only the variable. In a complete ccc chapter on classic lambda. We can recognize if it to having a visiting scholar at all its interior are coherent. The theory but hey there's a fixed points. First in a good reason is unsolvable term model. Moreover such as any lambda algebra is open term has a bit. The nf this edition there, is a syntactical lambda terms given such. Term is a strip lemma complete partial functions they preserve the substitution. A finite products of those terms are recursively inseparable. It we show that therefore even a set of categorical models. The main text so the graphs? One can define is conservative over the longest reduction cr. Heo is conservative over the category, theory of t2. This for optimal strategy using, the usual we can be in all. The revised edition contains a new, chapter which are given this reprinted famous edition. Barendregt does not one definable by induction on lambda terms to helping us furthermore. Recall that to prepare for every subterm has the first order. Simply contract the product topology on various classes. Given of inference rule once we can be constructed. Turing machine computability coincides with continuous …