Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybridized germ swarm optimization technique to calculate resonant frequency of RMA

Soft computing applications to antenna design are becoming the potential solution provider as reflected from the number of papers published in various journals. Resonant frequency of rectangular microstrip antenna having various substrate thicknesses are generally calculated using the standard expressions presented in literatures. In this paper, hybridizing bacterial foraging optimization technique in conjunction with particle swarm optimization developed as, "Hybridized germ swarm optimization technique (HGSOT)rdquo and applied on the published expressions, to calculate accurately the desired resonant frequency of rectangular microstrip antenna of any dimension and of any substrate thickness.
Improving eye cursor's stability for eye pointing tasks

In order to improve the stability of eye cursor, we introduce three methods, force field (FF), speed reduction (SR), and warping to target center (TC) to modulate eye cursor trajectories by counteracting eye jitter, which is the main cause of destabilizing the eye cursor. We evaluate these methods using two controlled experiments. One is an attention task experiment, which indicates that both FF and SR significantly alleviate the instability of eye cursor, but TC is not as we anticipated. The other is a 2D pointing task experiment, which shows that FF and SR as well as the improved implementation of SR (iSR) indeed improve human performance in dominant dwell-based eye pointing tasks of eye-based interactions. The method iSR is especially effective to accelerate eye pointing (10.5% and 8.5%) and reduce error rate (6.1% and 2.7%) when target diameter D = 45 and 60 pixels.
In vitro Evaluation of Different Feeds for Their Potential to Generate Methane and Change Methanogen Diversity

Optimization of the dietary formulation is the most effective way to reduce methane. Nineteen feed ingredients (brans, vegetable proteins, and grains) were evaluated for their potential to generate methane and change methanogen diversity using an in vitro ruminal fermentation technique. Feed formulations categorized into high, medium and low production based on methane production of each ingredient were then subjected to in vitro fermentation to determine the real methane production and their effects on digestibility. Methanogen diversity among low, medium and high-methane producing groups was analyzed by PCR-DGGE. The highest methane production was observed in Korean wheat bran, soybean and perilla meals, and wheat and maize of brans, vegetable protein and cereal groups, respectively. On the other hand, corn bran, cotton seed meal and barley led to the lowest production in the same groups. Nine bacteria and 18 methanogen 16s rDNA PCR-DGGE dominant bands were identified with 83% to 99% and 92% to 100% similarity, respectively. Overall, the results of this study showed that methane emissions from ruminants can be mitigated through proper selection of feed ingredients to be used in the formulation of diets.
Why batch and user evaluations do not give the same results

Much system-oriented evaluation of information retrieval systems has used the Cranfield approach based upon queries run against test collections in a batch mode. Some researchers have questioned whether this approach can be applied to the real world, but little data exists for or against that assertion. We have studied this question in the context of the TREC Interactive Track. Previous results demonstrated that improved performance as measured by relevance-based metrics in batch studies did not correspond with the results of outcomes based on real user searching tasks. The experiments in this paper analyzed those results to determine why this occurred. Our assessment showed that while the queries entered by real users into systems yielding better results in batch studies gave comparable gains in ranking of relevant documents for those users, they did not translate into better performance on specific tasks. This was most likely due to users being able to adequately find and utilize relevant documents ranked further down the output list.
“It is a good idea, but…” A qualitative study of implementation of ‘Individual Plan’ in Norwegian mental health care

Aim of the study The aim of the study is to explore and describe what hampers and promotes the implementation of ‘Individual Plan’—Norway’s answer to integrated care, and to discuss the findings according to implementation theory and research. Background ‘Individual Plan’ is a master-plan intended to increase user-participation and provide better coordination of measures for patients in need of extensive and long-term health-care services. Norwegian Health Authorities used a dissemination strategy to implement ‘Individual Plan’ but managers within health and social care could choose their own way of implementation in their organisation. Methodology Twenty-two managers from different clinics and organisational levels within mental health care were interviewed with an in-depth semi-structured interview about the implementation process in their organisation. The analysis was primarily made according to systematic text condensation. Findings The findings describe different implementation processes and how the managers identified with the usefulness of ‘Individual Plan’ as a tool, choice of practical implementation strategies, the manager’s own role, characteristics of organisational culture as well as how the manager considered external factors such as administration, lack of time and resources. The evolved implementation themes are discussed within a frame of existing knowledge and theory. Conclusion A complex picture of barriers, dilemmas and benefits emerges, both internal and external to an organisation as well as at a personal level that need to be taken into consideration in forthcoming implementation processes to increase the rate of success.
MultiOSN: realtime monitoring of real world events on multiple online social media

The flow of information in online social media during events has been widely studied in the computer science community. It has also been shown how information picked from online social media can help to eventually aid eventful, especially, crisis situations in real life. However, most of the work has focused on utilizing a single social network for monitoring such events, mostly Twitter. Given the immense popularity and diversity of various online social networks across the globe, studying multiple online social networks during an event can reveal much more information about the event, than a single online social network. In this work, we present MultiOSN, a framework which collects data from five different online social networks viz. Facebook, Twitter, Google+, YouTube, and Flickr, and presents real-time analytics and visualizations. MultiOSN can be particularly helpful to users and organizations which are directly or indirectly connected to law and order. Organizations can utilize MultiOSN to uncover the general sentiment of social media users about an event, and trace public gatherings for example, which are usually discussed and planned publicly on social networking platforms.
Farm Commodity Prices: Why the Boom and What Happens Now?

For many years, the price of food was a nonstory. Food price inflation was about the same as the general rate of inflation, and farm commodity market developments rarely drew the attention of those not directly involved in agriculture and the food industry. That has changed. Rising commodity prices and high food price inflation here and abroad have put agricultural commodity markets in the spotlight. The media are full of stories about the causes and impacts of the commodity boom. In this context, it may be hard to imagine that there is an angle to the story that has not already been covered repeatedly. However, some very simple economics may help us to understand some of the reasons for the increase in prices and to speculate about what might happen in the future.
Evaluation of a High Resolution Genotyping Method for Chlamydia trachomatis Using Routine Clinical Samples

Background Genital chlamydia infection is the most commonly diagnosed sexually transmitted infection in the UK. C. trachomatis genital infections are usually caused by strains which fall into two pathovars: lymphogranuloma venereum (LGV) and the genitourinary genotypes D–K. Although these genotypes can be discriminated by outer membrane protein gene (ompA) sequencing or multi-locus sequence typing (MLST), neither protocol affords the high-resolution genotyping required for local epidemiology and accurate contact-tracing. Principal Findings We evaluated variable number tandem repeat (VNTR) and ompA sequencing (now called multi-locus VNTR analysis and ompA or “MLVA-ompA”) to study local epidemiology in Southampton over a period of six months. One hundred and fifty seven endocervical swabs that tested positive for C. trachomatis from both the Southampton genitourinary medicine (GUM) clinic and local GP surgeries were tested by COBAS Taqman 48 (Roche) PCR for the presence of C. trachomatis. Samples tested as positive by the commercial NAATs test were genotyped, where possible, by a MLVA-ompA sequencing technique. Attempts were made to isolate C. trachomatis from all 157 samples in cell culture, and 68 (43%) were successfully recovered by repeatable passage in culture. Of the 157 samples, 93 (i.e. 59%) were fully genotyped by MLVA-ompA. Only one mixed infection (E & D) in a single sample was confirmed. There were two distinct D genotypes for the ompA gene. Most frequent ompA genotypes were D, E and F, comprising 20%, 41% and 16% of the type-able samples respectively. Within all genotypes we detected numerous MLVA sub-types. Conclusions Amongst the common genotypes, there are a significant number of defined MLVA sub-types, which may reflect particular background demographics including age group, geography, high-risk sexual behavior, and sexual networks.
A user-friendly platform for developing grid services over Globus Toolkit 3

This paper presents a platform that provides developers with a friendly development environment of grid services over Globus Toolkit 3. This platform includes a class of functions for processing parameters inputted from a developer via GUI and a class of functions for generating files required for defining grid services that the developer specifies. As a result, the development of grid services requires less special expert knowledge of a developer, the efficiency of developing grid services can be improved, and Globus Toolkit therefore increases its popularity and is for more practical and wider uses. This paper describes our design ideas, necessary functions, and implementations. The comparisons with other related toolkits are given in the paper.
Feature‐Preserving Reconstruction of Singular Surfaces

Reconstructing a surface mesh from a set of discrete point samples is a fundamental problem in geometric modeling. It becomes challenging in presence of ‘singularities’ such as boundaries, sharp features, and non‐manifolds. A few of the current research in reconstruction have addressed handling some of these singularities, but a unified approach to handle them all is missing. In this paper we allow the presence of various singularities by requiring that the sampled object is a collection of smooth surface patches with boundaries that can meet or intersect.
Hidden Understanding Models of Natural Language

We describe and evaluate hidden understanding models, a statistical learning approach to natural language understanding. Given a string of words, hidden understanding models determine the most likely meaning for the string. We discuss 1) the problem of representing meaning in this framework, 2) the structure of the statistical model, 3) the process of training the model, and 4) the process of understanding using the model. Finally, we give experimental results, including results on an ARPA evaluation.
Verification of Transaction Level models with Simulation Accelerator

Recently, transaction level modeling (TLM) has been widely referred to in system level design community. Due to lower modeling effort yet higher simulation speed, transaction level models are useful for architectural exploration, algorithmic evaluation, hardware-software partitioning and software development. However, TLM can’t be widely applicable to IP level design phase, because the simulation speed, one of the key merits of TLM, is slowed down where design is progressed. The simulation speed is dependant upon the abstraction level. Higher abstraction level makes faster simulation speed possible. In the IP level design phase, transaction level IP is substituted by lower abstraction level IP such as RTL IP. The conventional method of mixed level simulation is using transaction level simulator and HDL simulator. This two simulator is connected with IPC (inter process communication). But the whole simulation speed of this method is restricted by the speed of HDL simulation. This paper focuses on the methodology to increase the whole simulation speed of mixed level simulation between lower abstraction level IP and transaction level IP. For this acceleration, we approached the hardware-based simulation accelerator. We connected TLM to simulation accelerator instead of HDL simulator.
Effect of sympathetic relation and unsympathetic relation in multi-agent spoken dialogue system

Recently, spoken dialog systems using speech recognition technology have been becoming popular. Such as chat-like dialog systems, these systems which do not have any specific purpose are called “Non-Task-oriented spoken dialog system”. In this study, we focused on non-task-oriented spoken dialog systems. We have developed a multi-party chat-like dialog system with different preferences between two agents. In order to provide more enjoyable chatting to users, we focused on the relationship between two agents. In this study, we dealt with two types of the chat-like dialog system with two agents: an “Unsympathetic dialog system ”where one agent's preference differs from another agent, and a “Sympathetic dialog system” where both agents have the same preference. We evaluated user's degree of satisfaction by using our developed systems. As a result of the experiment, the sympathetic dialog system achieved a better impression in chatting. In order to solve the system problems obtained from the experimental results, we designed a new dialog system in order to deal with a more enjoyable conversation.
Cold acclimation affects immune composition in skeletal muscle of healthy lean subjects

Low environmental temperatures have a profound effect on biological processes in the body, including the immune system. Cold exposure coincides with hormonal changes, which may directly or indirectly alter the immune system, even in the skeletal muscle. The aim of the present study was to investigate the effect of cold acclimation on immune composition in skeletal muscle. Skeletal muscle biopsies were obtained from 17 healthy lean subjects before and after 10 days of mild cold exposure (15°C, 6 h/day). Nonshivering thermogenesis was calculated by indirect calorimetry. We found that cold acclimation increased nonshivering thermogenesis from 10.8 ± 7.5 before to 17.8 ± 11.1% after cold acclimation (P < 0.01), but did not affect plasma catecholamine nor cytokine levels. In contrast, cold acclimation affected mRNA expression of several immune cell markers in skeletal muscle. It downregulated expression of the Th17 markers RORC (−28%, P < 0.01) and NEDD4L (−15%, P < 0.05), as well as the regulatory T‐cell marker FOXP3 (−13%, P < 0.05). Furthermore, cold acclimation downregulated expression of the M2 macrophage markers CCL22 (−50%, P < 0.05), CXCL13 (−17%, P < 0.05) and CD209 (−15%, P < 0.05), while the M1 macrophage marker IL12B was upregulated (+141%, P < 0.05). Cold acclimation also enhanced several markers related to interferon (IFN) signaling, including TAP1 (+12%, P < 0.01), IFITM1/3 (+11%, P < 0.05), CD274 (+36%, P < 0.05) and STAT 2 (+10%, P < 0.05). In conclusion, 10 days of intermittent cold exposure induces marked changes in the expression of immune cell markers in skeletal muscle of healthy lean subjects. The physiological consequences and therapeutic relevance of these changes remain to be determined.
Phylogenetic and Demographic Insights into Kuhl’s Pipistrelle, Pipistrellus kuhlii, in the Middle East

Kuhl’s pipistrelle is found from Europe and North Africa all of the way to Asia, yet studies have thus far concentrated on the western limit of its distribution. Here we form a multi-marker picture of the diversity of Kuhl’s pipistrelle at a mid point in the Arabian peninsula in an attempt to redress the western sampling bias and to represent a region from which no genetic data has thus far been presented for this species. The three Arabian Cytochrome b haplotypes showed a clear divergence of 19 substitutions from those found in either Europe or North Africa. Molecular dating suggests the Arabian population split from the remaining Kuhl’s somewhere between 0.7 and 1.7 million years before present around the time of a series of aridification events across northern Africa. Well supported lineages within Arabia are typical of that which may be seen after an expansion from multiple Pleistocene refugia, but may also reflect the loss of intermediate haplotypes during historical population fluctuations. A long-term population contraction coincides with climatic changes towards those conditions more typical of contemporary Arabia.
Trade and growth in Ecuador : a partial equilibrium view

When the outbreak of the debt crisis in 1982 halted private international capital flows to most developing countries, it was not easy for Ecuador to cope with the changed international circumstances. Investments were largely in imported machinery as domestic capital goods production was in its infancy. Exports were concentrated in petroleum and several agricultural products and could not be counted on to increase foreign exchange in the short run. The trade balance was improved in the first half of the 1980s by reducing imports. The author examines the behavior of the Ecuadoran economy in a period of scarce foreign exchange. He uses a small, econometrically specified"trade and growth"model of the Ecuadoran economy to illustrate the importance of trade elasticities. He estimates trade elasticities for Ecuador and integrates them into a small simulation model of Ecuador's supply side. He uses a nested constant-elasticity-of-substitution production function to derive factor input demands for two types of imported goods important in Ecuador: imported intermediate goods and imported machinery. Elasticity estimates of imported factor of production are very low. They characterize both types of imports as complements to domestic factors. The author uses the econometrically specified model to examine the connection between imported factors of production and output capacity. He analyzed trade balance responses to a terms-of-trade shock, a devaluation, and an increase in world demand. Low trade elasticities on the import side make the economy vulnerable to external shocks. The low elasticities necessitate large relative price shifts (through devaluation) to improve the trade balance if growth-reducing policies are to be avoided in times of scarce foreign exchange. A deterioration in terms of trade has a pronounced negative impact on the trade balance. To the extent that trade elasticities remain low in the 1990s, events such as a commodity price decline, a renewed credit squeeze, or increased protectionism against Ecuadoran exports - like the recent European Union quotas on banana imports - can translate into renewed domestic supply disturbances. Policies that lead to diversification of exports and higher price responsiveness for both imports and exports would reduce the vulnerability of Ecuador's economy to external shocks.
Iterative receiver for synchronous CDMA using hidden Markov model

The expectation maximization (EM) algorithm is popular in estimating the parameters of the statistical models. We consider application of the EM algorithm to maximum likelihood estimation. A hidden Markov model (HMM) formulation is used and the EM algorithm is applied to estimate the parameters of the HMM which, in turn, are used to estimate received amplitudes of the users. The proposed method is compared with that of Khan (see PIMRC, 2002) and is found to be superior.
Face detection based on improved AdaBoost algorithm in E-Learning

This paper is based on the background of learners' expression recognition in emotion recognition interactive E-Learning. This paper aims at time-consuming of training samples and weights degradation two problems of traditional AdaBoost algorithm, proposes a decile eigenvalue AdaBoost algorithm and joins FPR (False Positive Rate) in this algorithm. The experiments use improved AdaBoost algorithm in E-Learning face detection achieved good effect, and the results provide good conditions for the follow-up E-Learning expression feature extraction.
A New ILP Based Approach to Schedule and Bind Simultaneously

To construct complete design space for high-level synthesis and obtain globally optimized solution. An approach that fulfills operation scheduling and binding simultaneously is presented in this paper. The improved ASAP and ALAP scheduling algorithms are employed to compute the actually soonest and latest control steps with the condition of referring binding information. A basic model based on ILP is presented to solve the minimum resource occupance scheduling and binding under timing constraints. The means to solve minimum execution control steps scheduling and binding is also investigated. According to experiments, when scheduling fulfilled by this approach is accomplished, the binding results are obtained meanwhile. The executing time required by the approach is very low. And the feature of ILP has guaranteed the global optimization of results. Based on plenty of benchmark experiments, it can be concluded that the approach presented in this paper is effective and efficient.
Toward a practical visual object recognition system

Recent researches in cognitive science and document recognition have been applied to deal with the problem of categorizing object. Bag-of-Features (BoF) and its extension Spatial Pyramid Matching (SPM) have made a breakthrough in resolving this kind of challenges. Many methods followed this guideline really enhance the recognition accuracy but still have drawbacks in developing a real-world application whose data size is many times bigger. In this paper we propose two kinds of strategy include five criteria to evaluate and select the most appropriate training samples using for building a high performance classifier. We also suggest a method called reinforcement codebook learning to make the codebook training process not only purpose-built to best fits with the most suitable criteria but also much more efficient by reducing significantly its complexity of computation. Experiments on benchmark object dataset demonstrate that our proposed framework outperforms remarkable results and is comparable with the state-of-the-art in spite of using just 20% of 9 · 106 descriptors for training the dictionary. These results give a promise of building a efficient and feasible object categorization system for practical application as so as suggest some ideas to improve the visual feature representation in future.
Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem

This paper presents performance evaluation of GPU-accelerated Support Vector Machines (SVMs) using large datasets. Although SVMs algorithm is popular among machine learning researchers and data mining practitioners, its computational time is too long and impractical for large datasets due to its complex Quadratic Programming (QP) solver. The result shows that using GPU-accelerated SVMs can significantly reduce computational time for training phase of SVMs and it can be a viable solution for any project that require real-time forecasting output.