Miracle-dz/UniFAR-FTUs huggingface dataset:
Liver Detection Algorithm Based on an Improved Deep Network Combined With Edge Perception

Due to the large number of organs and the similar grayscale in abdominal medical images, accurately locating and identifying the liver in an abdominal image is a challenging problem. To improve the accuracies of liver detection and localization, this paper proposes an improved deep network that is combined with edge perception. The network improves the contour-detection accuracy of the liver via an edge-perception fusion module and captures the high-level semantic features of the abdominal image using a multiscale pyramid pooling layer. The complementary characteristics of the edge-related features can effectively preserve the clear boundaries of the liver, while rich global context information can be extracted from the combination of the auxiliary channel output and the pyramid pooling layer output. Many qualitative and quantitative experimental results demonstrate that the proposed model can effectively improve the performance of detection and localization networks, which can narrow the range of regions of interest, and can enhance the accuracy of subsequent segmentation and recognition.
Hybrid MVDR-LMS beamforming for Massive MIMO

With the high speed of communication in LTE-5G, fast beamforming techniques need to be adopted. The training time required to form and steer the main lobes toward 5G multiple users must be short. Least-Mean-Square (LMS) training time is not suitable to work with in LTE-5G, but it has a good performance in forming multiple beams to large number of users and producing nulls in the interference direction. In this paper, an optimized hybrid MVDR-LMS beamforming algorithm is proposed to reduce the time required to estimate the antenna’s weights. This optimization is made by the benefit of previously set weights calculated using MVDR algorithms. The performance of the proposed hybrid MVDR-LMS algorithm tested using MATLAB 2016a.
What is reverse debugging? Classification of reverse debugging methods

The article discusses an approach to speeding up the search complex errors in software – reverse debugging. In this approach, debugging is divided into two phase. The first phase is to save the behaviour to a log file. The second phase is the reproduction of behaviour and the search for errors. During the second phase, both past and future program states can be examined. The article describes methods that support this approach and general principles for such methods and their differences. A classification of reverse debugging methods is proposed by debugging scope and replay scope. Examples of modern reverse debugging tools and their place in the proposed classification are given.
Unsupervised learning strategies for automatic generation of personalized summaries

It is relatively hard for readers to deal objectively with large documents in order to absorb the key idea about a particular subject. In this sense, automatic text summarization plays an important role by systematically digest a large number of documents to produce indepth abstracts. Despite fifty years of studies in automatic summarization of texts, one of the still persistent shortcomings is that the individual interests of the readers are still not considered. Regarding the automatic techniques for generation of summaries, it mostly relies on supervised Machine Learning algorithms such as classification and regression, however, the quality of results is dependent on the existence of a large, domain-dependent training data set. On the other hand, unsupervised learning strategies are an attractive alternative to avoid the labor-intense and error-prone task of manual annotation of training data sets. To accomplish such objective, this work puts forward a novel unsupervised and semi-supervised algorithms to automatically generate tailored summaries. Our experiments showed that we can effectively identify a significant number of interesting passages for the readers with less data for the training step.
Review, BCG vaccination in children.

BCG is the oldest and most widely used vaccine at presentin the WHO Expanded Programme on Immunization. In a recent meta-analysis, the protective efficacy of BCG in trial was 51% and in the case-control studies 50%. There has been as yet no controlled prospective trial on the efficacy of revaccination. The recent WHO statement does not recommend BCG revaccination. BCG is ne of the vaccines with rare adverse reactions. Lymphadenitis are the most frequent side effects. Disseminated fatal BCG infection is rare. The risk-benefits of a BCG vaccination programme have to be assessed strictly.
Methodology for distribution network reconfiguration in smart grid system regarding power loss, grid reliability and the utilization factor of substations, considering a new reality of energy supply and consumption

— This paper proposes a new methodology for distribution network reconfiguration (DNR), in a Smart Grid (SG) scenario, regarding power losses, grid reliability and the utilization factor of substations; as well as an approach to model the effects of electric vehicle charging stations, distributed energy generators and energy storage systems in the electric grid. The proposed methodology first deals with the problem setting, that is, it determines the state of the grid (in terms of electrical parameters and variables, power loss, reliability indicators and utilization factor for each substation) and its topology. Then, it’s defined the universe of possible solutions, to which is applied a simple formulation of Genetic Algorithm (GA) that solves the optimization problem. To demonstrate the applicability of this methodology in a real network, the methodology was implemented in the specialized commercial power system simulator SINAP Grid and applied in a case study. Its results showed that it is possible to accommodate so many objectives in one solution, however, the state of the grid and its initial topology influence greatly in the outcome of the solution.
Image processing based foot plantar pressure distribution analysis and modeling

Although many equipments and techniques are available for plantar pressure analysis to study foot pressure distributions, there is still a need for mathematical modelling references to compare the acquired measurements. In order to derive formulas in this concern, this research proposes a measurement-based method which adopts the reference measured parameters such as; the weight of a subject, contact-area size, age, and the pressure level distribution over a plantar image captured by the EMED plantar pressure system. The proposed analysis and algorithm were verified by a group 79 volunteers through data collection with four various measurement conditions. Three mathematical modelling equations have been proposed that describe the relationships between the foot plantar pressure levels and the subject’s body mass, foot size, and age. The modelling of foot plantar pressure could be useful for various applications such as gait analysis, hospitals, clinics, custom shoe making, and early detection of ulceration in the case of diabetic patients.
Multi-Level Sentiment Analysis of PolEmo 2.0: Extended Corpus of Multi-Domain Consumer Reviews

In this article we present an extended version of PolEmo – a corpus of consumer reviews from 4 domains: medicine, hotels, products and school. Current version (PolEmo 2.0) contains 8,216 reviews having 57,466 sentences. Each text and sentence was manually annotated with sentiment in 2+1 scheme, which gives a total of 197,046 annotations. We obtained a high value of Positive Specific Agreement, which is 0.91 for texts and 0.88 for sentences. PolEmo 2.0 is publicly available under a Creative Commons copyright license. We explored recent deep learning approaches for the recognition of sentiment, such as Bi-directional Long Short-Term Memory (BiLSTM) and Bidirectional Encoder Representations from Transformers (BERT).
Navegação Topológica Aplicada a Agentes Robóticos Móveis

In our modern society, there is a growing need to use autonomous robots to execute different types of tasks without disturbing the environment where they are introduced. There is a wide variety of robots such as guide robots or service and security robots, that were developed to help people overcome their difficulties while performing a multitude of different tasks. Robots are quickly earning an important role in our daily-life, evolving from laborers to companions. This project aims to create a recepcionist-guide robot to be used at the Institute of Systems and Robotics, University of Coimbra. To accomplish this goal, we have developed a system that supports the navigation of a robot in a known environment, based on the principles of topological navigation. In order to avoid obstacles that may appear along the trajectory, sensorial capabilities were added. To address the fact that the estimation of the position of the robot accumulates error throughout time, a set of visual markers were positioned along the trajectories to aid in localizing the robot. These landmarks provide means for positioning in reference to a global coordinare system over a wide range of viewing configurations. This is a simple, inexpensive, robust, and easy to implement aproach to global localization. To interact with the user a graphical user interface was created were the user can choose from between pre-planned visits or to go to a certain location. We have performed experiments in a indoor scenario, demonstrating the feasibility and performance of the system.
Ensemble Classifier Managing Uncertainty in Accelerometer Data within Human Activity Recognition Systems

Human activity recognition (HAR) is a field of study that aims to recognize activities from data acquired by video or wearable sensors. The biggest health study in Norway, HUNT, has recently ended it’s fourth study where 38 756 participants have recorded activity data while wearing three-axis accelerometer on their thigh and back. HAR systems often require all sensors to be operative and attached to the participant at all times, and shows weaknesses when performing activity recognition, as a lot of misclassifications occur due to sensors lying still after being detached from the subject’s body during activity recording. To make HAR systems more robust against this issue, this thesis researches on a new type of ensemble classifier where a meta classifier predicts sensor no-wear time, eliminates faulty sensor streams and dynamically adjust the LSTM-RNN sensor position specific classification models used, depending on the data available. The developed meta classifier is trained on a new ”Sensor No-Wear Time” dataset that consists of real-world data, and is able to predict sensor no-wear time with 97.2% accuracy and shows promising results towards making more valid contributions towards public health research, as it eliminates up to several days of misclassifications where sensors have been detached. Research done in this thesis shows that individual models for thigh and back are struggling to classify certain static activities. A model for both sensors combined is therefore the best option for activity classification as it achieves an accuracy of 85.1% compared to the existing HAR system’s 76.5%, and outperforms individual models when classifying static activities. Storing classification results for all participants in HUNT requires huge amounts of storage space, and Feather is proving to be the file format that is best suited for storing activity classification results, as the result file size for each participant is reduced from 2.5 GB to 941 KB with a new compression algorithm. This results in a total reduction of 99.96%, as necessary storage space is reduced from 96.89 TB to 0.036469396 TB for all HUNT4 participants.
IDENTIFICATION OF UTERIN MILK PROTEIN (UTMT) GENE IN BALI CATTLE USING DIRECT SEQUENCING

The objective of this research was to identify diversity of exon 5 UTMP gene fragment in Bali cattle using direct sequencing. The total 60 blood samples of Bali Cattle derived from BPTU Bali in Bali siland (20 heads), BPTU Serading in Sumbawa island (20 heads) and Village Breeding Center in Barru District South Sulawesi (20 heads) were used to evaluate their genetic diversity at exon 5 UTMP gene. The forward and reverse data sequences were analyzed using Bioedit program and alignment analysis was carried out using MEGA5 program. Meanwhile haplotype analysis was performed by DnaSPv5 program. The result showed that partial sequences in exon 5 UTMP gene had 16 haplotypes with the highest number of haplotypes ware found in VBC Barru district South Sulawesi (8 haplotypes). Moreover, the highest average of haplotype (h) and nucleotide (p) diversity were found in VBC Barru district South Sulawesi were 0.7949 and 0.0016, respectively. In addition, minisatellite insersion was found in exon 5 UTMP gene fragment on Bali cattle which are consist of 5'-CCA GTC ATG AAG AAG GCA GAG GTC GTC GTG CCG GCG AAA-3'. According to our results, haplotype and minisatellite variation in exon 5 UTMP gene fragment can be used as a candidate genetic marker specific for reproductive trait in the Bali cattle and for its strategy breeding program in the future.
Socio-hydrological perspectives of the co-evolution of humans and groundwater in Cangzhou, North China Plain

Abstract. This paper presents a historical analysis from socio-hydrological perspectives of the coupled human–groundwater system of the Cangzhou region in the North China Plain (NCP). The history of the pendulum swing for water allocation between the economic development and aquifer environmental health of the system is divided into five eras (i.e., natural, exploitation, degradation and restoration, drought-triggered deterioration, and returning to equilibrium). The system's evolution was interpreted using the Taiji–Tire model. Over-exploitation was considered as the main cause of aquifer depletion, and the groundwater utilization pattern was affected by the varying groundwater table. The aquifer depletion enhanced community sensitivity toward environmental issues, and upgraded the social productive force for restoration. The evolution of the system was substantially impacted by two droughts. The drought in 1965 induced the system from natural conditions to groundwater exploiting. The drought from 1997 to 2002 resulted in a surge in further groundwater abstraction and dramatic aquifer deterioration, and community sensitivity increased rapidly and induced the social productive force to a tipping point. From then on, the system returns to equilibrium through new policies and water-saving technologies. Along with the establishment of a strict water resource management strategy and the launch of the South-to-North Water Diversion Project, further restoration of groundwater environment was implemented. However, a comprehensive and coordinated drought management plan should be devised to avoid irreversible change in the system.
Energy saving by power electronics: towards a new concept of renewable source

The use of fossil sources has been increasing the excess of carbon dioxide (CO2) emission in the atmosphere since the last century with detrimental to the weather. Renewable Energy Sources (RESs) appear a valid solution to mitigate CO2 emissions but their growth is still too small compared to fossil sources, for this reason they need to be sustained by available technologies. Among these, the use of More Power Electronics (MPE) for electrical energy conversion leads to increase efficiency conversion and the investment is compensated in few time both for new equipment and retrofitting. The saved energy meets the definition of renewable energy. The whole amount of the energy saving potential achievable by MPE is comparable to the electric energy generated by the installed renewable sources.
Study of Knowledge Management Efficiency on Employees Performance in Kerman Sport and Youth Offices

The purpose of this paper is to measure the efficiency of knowledge management in Kerman Sport and Youth Office and also measure the relationship of organizational structure variables, organizational culture, technology, strategy, efficiency, knowledge interaction, keeping knowledge, knowledge application, and knowledge acquisition with the efficiency of knowledge management. The statistical society contains of employees of the above mentioned office (110 individuals) and 100 questionnaires Trevor(2006) were distributed and 82 of them were relapsed, Validity of this questionnaire was confirmed by the specialists and its reliability was measured by Alpha cronbakh (97%). For data analysis, Pearson, Freidman ranking test was used. The obtained results show that the efficiency of knowledge management in this office is in the average level and there is a significant relationship between organizational structure and the efficiency of knowledge management. And also there is a significant relationship between field factors such as organizational culture, technology, strategy, creating the efficiency fields and process of knowledge management such as acquisition of knowledge management, efficiency, knowledge interaction, keeping knowledge, knowledge application, and efficiency of knowledge management.
Recent Advances in Organic Solar Cells

Solar cells based on organic semiconductors have attracted much attention. The thickness of the active layer of organic solar cells is typically only 100 nm thin, which is about 1000 times thinner than for crystalline silicon solar cells and still 10 times thinner than for current inorganic thin film cells. The low material consumption per area and the easy processing of organic semiconductors offer a huge potential for low cost large area solar cells. However, to compete with inorganic solar cells the efficiency of organic solar cells has to be improved by a factor of 2-3. Several organic semiconducting materials have been investigated so far, but the optimum material still has to be designed. Similar as for organic light emitting devices (OLED) small molecules are competing with polymers to become the material of choice. After a general introduction into the device structures and operational principles of organic solar cells the three different basic types (all polymer based, all small molecules based and small molecules mixed with polymers) are described in detail in this review. For each kind the current state of research is described and the best of class reported efficiencies are listed.
Irrigation scheduling for corn in a coastal saline soil

Abstract: Currently, water scarcity is serious and the irrigation scheduling with efficient water use becomes important in China. In this study, irrigation systems were scheduled in the saline area along Laizhou Bay. Field study was conducted to determine the relation of irrigation regime and crop yield from 2010 to 2012, and the representative rainfall years (high-flow year, normal-flow year and low-flow year) were calculated by analyzing rainfall frequency over 30 years. Six irrigation regimes were set according to local farmers’ practices. Irrigation amounts of T1, T2, T3, T4, T5 and T6 were 225.0 mm, 270.0 mm, 337.5 mm, 300.0 mm, 360.0 mm and 450.0 mm, respectively, with the same frequency of four times. The results showed that soil salt content decreased with the increase of irrigation water amounts. The corn yield varied from 6560 kg/hm2 to 8060 kg/hm2. The highest yield was obtained from T5. Production functions related to irrigated water (I, mm) for corn yield (Y, kg/hm2) was Y = −0.0397I2 + 1059.6 (R2 = 0.8892). Aiming at high corn yield, total water supply (irrigation and rainfall) to corn crops was 859 mm. Precipitation amounts at low-flow year (p=80%), normal-flow year (p=50%) and high-flow year (p=20%) were obtained by the simulation of rainfall frequency curve, which were 348 mm, 457 mm and 604 mm respectively in the whole growth period (from late June to mid-October). In order to obtain the highest theoretical corn yield, according to field results and rainfall, the optimum irrigation frequency at low-flow year, normal-flow year or high-flow year was four times for corn in the saline area along Laizhou Bay. Keywords: corn (Zea mays), irrigation regime, desalination, rainfall, soil salinity DOI: 10.3965/j.ijabe. 20160906.2133 Citation: Chang T T, Shao X H, Ye H, Li W, Zhang J, Zhang Z Y. Irrigation scheduling for corn in a coastal saline soil. Int J Agric & Biol Eng, 2016; 9(6): 91－99.
Cloud pressure retrieval using the O2‐O2 absorption band at 477 nm

[1] We present an operational method for cloud pressure retrieval from the Earth's reflectance spectrum in the visible, using the O2-O2 absorption band at 477 nm. The algorithm is simple and robust. Apart from cloud pressure, an effective cloud fraction is also retrieved. Using simulations and Global Ozone Monitoring Instrument (GOME) data the accuracy of the O2-O2 retrieval method is estimated. The Ozone Monitoring Instrument (OMI), to be space-borne on board the EOS-AURA platform in 2004, will use this algorithm to produce an official cloud product. The cloud product will be used to support the cloud correction of several of the OMI trace gas retrievals.
An ARDL Bounds Test Approach to Modelling Tourist Expenditure in South Africa

This research follows micro-economic theory, according to which demand for a product is influenced by price, substitute prices and income, to determine the sensitivity of inbound tourist expenditure in South Africa to changes in these variables. Tourist expenditure per person per day from different origins forms the dependent variable. Using quarterly time-series data from 2003 to 2010, this article models inbound tourist expenditure from key source markets for the country. Previous research based on arrivals finds that South Africa is a relatively price-insensitive destination. However, this research shows that this is not the case for all markets. It mostly confirms the income elasticity of South Africa as a destination.
Dynamic load identification of stochastic structures based on unscented transformation

In view of some unknown parameters in structures, which are described by the Gaussian distribution model in this paper, a new dynamic load identification method for stochastic structures is proposed based on unscented transformation (UT). Firstly, the convolution equation for solving structural response is discretized, and the sampling points, namely, sigma points of stochastic parameters are calculated according to the unscented transformation. Then, when the stochastic parameters take each sigma point, the dynamic load is calculated by the direct inversion method combined with the regularization method. Finally, the mean value and standard deviation of the identified load are obtained, and the coefficient of variation and the upper and low bounds of the identified load are defined. The result of an example shows that compared with the Monte Carlo simulation (MCS) and perturbation method (PM), the proposed method has higher computational efficiency and accuracy.