Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Method for Multi-bit Correction using BCH

: Transmission of information through a physical medium or wireless medium ,possibility that data get corrupted this leads to an error in a random only selected locations of a symbol or the entire symbol. To have a reliable communication through a communication channel that has an acceptable Bit Error Rate(BER) error correcting codes are used . These codes are used to detect and correct a specific number of error which may occur during transmission of message over a communication channel. As the complexity of communications and signal processing systems increases, so does the number of blocks or elements that they have. The increase in complexity also poses reliability challenges and creates the need for fault-tolerant implementations. In those complex systems, it is common that some of the filters operate in parallel to provide the error free output to the filters by using hamming code in redundant module. It is used for single fault corrections papers. In this paper few methods are proposed for the multiple bit error corrections. The BCH code is used for the multiple error corrections. The encoding ,decoding ,syndrome and error corrections are also discussed. This method shows more reliability with the single error correction implementations existed upto now. BCH codes are widely used in the area like ,mobile communication, Digital communication, Satellite communication ,Optical and Magnetic storage system and Computer Network etc.
Inulin and Microbial Inulinases from the Brazilian Cerrado: Occurrence, Characterization and Potential Uses

The Brazilian cerrado is a biome characterized by a well-defined humid summer and a dry winter, where plant growth is concentrated in certain seasons within the annual cycle. Fructans of the inulin-type are the main reserve carbohydrate in about 60% of the Asteraceae species growing in the cerrado. These soluble carbohydrates have been associated with tolerance to cold and drought and in the adaptation of plants to unfavorable environmental conditions prevailing in the cerrado. The high fructan concentrations found in the cerrado flora and the occurrence of species characterized by inulins with high degree of polymerization among them are of particular importance concerning the production of inulin and derivatives and their industrial use as ingredients of functional foods. The search of efficient fungi isolated from the rhizosphere of Asteraceae for the production of extracellular inulinases, using inulin from the reserve organs of cerrado plants as a carbon source, is of great importance considering the increasing interest in the commercial production of free fructose and other inulin derivatives. _____________________________________________________________________________________________________________
HYBRID FEATURE SELECTION BASED ON MUTUAL INFORMATION AND AUC FOR PARKINSON’S DISEASE CLASSIFICATION

Machine learning classifiers are used to distinguish healthy individuals from patients with Parkinson’s disease through the use of a dataset of voice measurements based on patient speech recordings. Feature selection based on information theory is used in many data mining and machine learning applications. Mutual information is used on the Parkinson disease dataset to select a subset of relevant features that contribute the most in the decision making process. In conjunction with Mutual Information, the area under curve (AUC) is applied for feature selection, and features are eliminated by majority voting. In this paper, five classifiers are used to classify Parkinson’s disease: Multilayer Feedforward Artificial Neural Network, k-Nearest Neighbor (kNN), Support Vector Machines, Naïve Bayes, and k-Means. The dataset is preprocessed prior to the classification, and the classifiers are trained using the k-fold cross validation evaluation model. The performance of the classifiers is evaluated based on the accuracy and the area under curve before and after the feature selection. The results are promising, particularly for the kNN classifier; k-Means presents the worst performance.
The Adoption of Technology and Innovation Among Native Online News Media in Colombia

This study analyzes how entrepreneurial native online newsrooms in Colombia are implementing digital technologies and innovation in their workspaces. The article uses technology studies and entrepreneurial journalism as frameworks to investigate eight relevant case studies. The method used in-depth interviews with the directors of these online media. Results show that native online outlets value people, quality of content, access to information, and journalistic standards more than digital technology and platforms. For them, innovation is not strictly related to implementing new technology, but it is somewhat linked to the type of journalistic innovation products they are creating. They believe they are an alternative voice to mainstream media content but use traditional outlets to distribute their stories and increase their relevance. The integration of users into their editorial process is a goal, but it is still limited.
EU and North African Migrants: Health and Health Systems

Executive Summary: EUNAM (EU and North African Migrants: Health and Health Systems) was funded under the European Union’s 7th Framework Program for 4 years with the starting date on April 2011 and a total budget of close to €2 million. The project was summarized: “The coordinates of human health are complex even in a single population but they are even more complex in migrants whose life situation is always in uenced by the host country and the country of origin. Some migrants may experience several host countries and some return to the country of origin. Thus it is important to survey wellbeing, health status, disease panorama and use of health services of immigrants compared to the native population; such analyses would be incomplete without casting a view on the same indicators and parameters in the country of origin”. The partners were a team of experts covering health aspects of the full cycle of migration, viewing the health situation in Egypt, Tunisia and Morocco as representatives of the Mediterranean North African (NA) partner countries, the origins of vast numbers of immigrants in the European Union (EU). The EU partner countries from France, Italy, Germany and Sweden are not only receivers of the NA immigrants but they also have large numbers of immigrants from others areas, allowing comparisons between immigrant groups. The team had experience on a variety of health and disease measures and it had access to a variety of survey and register material relating to population health, disease patterns and function of health care systems. The team has been in the position to respond to the expectations of the call by reviewing health effects of migration from the country of origin to the host country and coming up with scienti cally valid state-of-the-art evaluations published in some 50 articles.
How many flower types can bumble bees work at the same time

Bumble bees often restrict their foraging behaviour to the flowers of two plant species on a single foraging trip ("a major and a minor" sensu Heinrich), perhaps because learning additional flower-handling techniques interferes with their ability to recall previously learned flower-handling skills. This hypothesis was tested with bumble bees (Bombus impatiens) foraging on arrays of artificial flower types. Test bees were first trained on one flower type, then retested on the same flower type after learning one, two, or three different types. The number of flower types selected by bees on a mixed array consisting of several types was also tested. Interference effects increased with the number and complexity of interfering flower types: a 0% increase for one simple flower type; 278% for two simple flower types; 357% for three simple flower types; and 565% for two complex flower types; switching among more than two flower types caused substantial interference. On the mixed array of three flower types, none o.
CARDIOVASCULAR DISEASE CLASSIFICATION BASED ON ECHOCARDIOGRAPHY AND ELECTROCARDIOGRAM DATA USING THE DECISION TREE CLASSIFICATION APPROACH

For a doctor, diagnosing a patient's heart disease is not easy. It takes the ability and experience with high flying hours to be able to accurately diagnose the type of patient's heart disease based on the existing factors in the patient. Several studies have been carried out to develop tools to identify types of heart disease in patients. However, most only focus on the results of patient answers and lab results, the rest use only echocardiography data or electrocardiogram results. This research was conducted to test how accurate the results of the classification of heart disease by using two medical data, namely echocardiography and electrocardiogram. Initial research was conducted by comparing two classification methods, namely Naive Bayes and Decision Tree. The results of the comparison of classification models show that the decision tree approach has a better accuracy than Naive Bayes. Three treatments were applied to the two medical data and analyzed using the decision tree approach. The first treatment was to build a classification model for types of heart disease based on echocardiography and electrocardiogram data, the second treatment only used echocardiography data and the third treatment only used electrocardiogram data. The results showed that the classification of types of heart disease in the first treatment had a higher level of accuracy than the second and third treatments. The accuracy level for the first, second and third treatment were 78.95%, 73.69% and 50%, respectively. This shows that in order to diagnose the type of patient's heart disease, it is advisable to look at the records of both the patient's medical data (echocardiography and electrocardiogram) to get an accurate level of diagnosis results that can be accounted for.
Level Of Economic Development (Ed) And Advanced Management Accounting Practice (Amap)

The article examined the nexus between the level of economic development and the adoption of advanced management accounting practices in Nigeria by industrial manufacturing firms. The study adopted a survey research strategy, for which the opinion of 74 executive-level accounting staff of industrial manufacturing companies was sampled using a questionnaire. The responses were analysed using descriptive statistics, simple percentage, tables and ordinary least square regression methods. From the results garnered, it concluded that the level of adoption of advanced management accounting practices by manufacturing companies in Nigeria is quite low, which is attributed to the fact that manufacturing companies in the country use mostly flat methods of manufacturing. Thus, it is concluded that the level of economic development of a nation determines the nature of manufacturing technology deployed by the firms, and therefore the choice of MA methologies. The foregoing observation leads to the conclusion that the low level of adoption of advanced management accouting practice correlates with the level of economic and industrial development of Nigeria.Thus, the government must deliberately support industrial development via deliberate and targetd policies, and should strive to established technology incubation and development centres, to facilitate industrial development. All oppurnities for indingenous technology development must be exploited. Finally,firms in the industrial sector should also develop and deploy strategic master plans towards acquiring and deploying improved technology to harness the gains derivable therein.
6RLR-ABC: 6LoWPAN Routing Protocol With Local Repair Using Bio Inspired Artificial Bee Colony

In recent years, Micro-Electro-Mechanical System (MEMS) has successfully enabled the development of IPv6 over Low power Wireless Personal Area Network (6LoWPAN). This network is equipped with low-cost, low-power, lightweight and varied functions devices. These devices are capable of amassing, storing, processing environmental information and conversing with neighbouring sensors. These requisites pose a new and interesting challenge for the development of IEEE 802.15. 4 together with routing protocol. In this work, 6LoWPAN Routing Protocol with Local Repair Using Bio Inspired Artificial Bee Colony (6RLR-ABC) has been introduced. This protocol supports connection establishment between nodes in an energy-efficient manner while maintaining high packet delivery ratio and throughput and minimizing average end-to-end delay. This protocol has been evaluated based on increasing generated traffic. The performance of the designed 6RLR-ABC routing protocol has been evaluated compared to 6LoWPAN Ad-hoc On-Demand Distance Vector (LOAD) routing protocol. LOAD protocol has been chosen since it is the most relevant existed 6LoWPANrouting protocol. The simulation results show that the introduced 6RLR-ABC protocol achieves lower packet average end-to-end delay and lower energy consumption compared to LOAD protocol.Additionally,the packet delivery ratio of the designed protocol is much higher than LOAD protocol. The proposed 6RLR-ABC achieved about 39% higher packet delivery ratio and about 54.8% higher throughput while simultaneously offering lower average end-to-end delay and lower average energy consumption than LOAD protocol.
Scale-Dependent Recolonization: The Role of Sediment Stability in a Dynamic Sandflat Habitat

An important ecological issue is developing an understanding of how patterns and processes vary with scale. We designed a field experiment to test how differences in the aerial extent of disturbance affected macrofaunal recolonization on a sandflat. Three different plot sizes (0.203 m 2 , 0.81 m 2 , and 3.24 m 2 ) were defaunated, and samples were collected to assess recovery over a 9-mo period. As the sandflat used for the experiment was prone to disturbance by wind-driven waves, we also measured changes in sediment bed height (an indicator of sediment stability) over the course of the experiment. Most common species revealed significant relationships between density and disturbance plot size. Scale-dependent recovery was also demonstrated by differences in species assemblage structure over the course of the experiment. Relative rates of colonization varied by 50% between large and small experimental plots. However, these differences were not related to specific species, particular functional groups, or potential modes of colonization. The results revealed an unusually slow rate of faunal recovery following defaunation. Both increasing numbers of colonists and density changes in ambient sediments made an important contribution to recovery. The relationship found between changes in sediment bed height and wind velocity indicated that wind-driven wave disturbance was an important factor influencing sediment instability. Sediment instability was higher in all experimental plots than in the ambient sediments, due to the initial removal of a dense spionid polychaete tube mat characteristically found at the study site. Sediment instability also increased with increasing plot size. Thus in this dynamic sandflat habitat, faunal emigration from recovering disturbed patches of sediment may significantly slow rates of recolonization. These results demonstrate that incorporating patch size, emigration, recovery time, and interactions between hydrodynamic conditions and habitat stability (particularly where colonists influence sediment stability) are crucial to generating a general understanding of recovery processes in soft-sediment habitats. While our results demonstrate the need for caution in scaling-up from small-scale studies, they do indicate that larger scale disturbances that destroy organisms with a role in maintaining habitat stability are likely to result in very slow recovery dynamics, particularly in wave-disturbed soft-sediment habitats.
Effects on plumage condition, health and mortality of dietary oats/wheat ratios to three hybrids of laying hens in different housing systems

The effects on plumage condition and health when feeding diets with varying oats/wheat ratios to different non‐beak‐trimmed hybrids housed in various systems were studied in two experiments. In experiment 1 (Expt. 1) 1146 Lohmann Selected Leghorn (LSL) and 1006 Lohmann Brown (LB) birds were housed in eight aviary pens; four in each of the systems Lovsta (L) and Marielund (M), or in six groups of 24 conventional cages each (C). Two diets with a high proportion of either oats or wheat were used. Experiment 2 (Expt. 2) included 1740 LSL and 1632 SLU‐1329 birds housed in 6 pens each of system M. Diets with varying proportions of oats and wheat were given. In Expt. 1, LB hens housed in C showed better plumage condition compared with those housed in the aviaries, whereas LSL birds showed the opposite trend. Housing system affected most health traits, showing superior results for system C regarding, for example, bumble foot, cleanliness of feet and keel bone lesions. In Expt. 2, feather cover deteriorated in LSL.
Transition from freestanding SnO2 nanowires to laterally aligned nanowires with a simulation-based experimental design

In this study, we used simulations as a guide for experiments in order to switch freestanding nanowire growth to a laterally aligned growth mode. By means of finite element simulations, we determined that a higher volumetric flow and a reduced process pressure will result in a preferred laterally aligned nanowire growth. Furthermore, increasing the volumetric flow leads to a higher species dilution. Based on our numerical results, we were able to successfully grow laterally aligned SnO2 nanowires out of gold film edges and gold nanoparticles on a-plane sapphire substrates. In our experiments a horizontal 2-zone tube furnace was used. The generation of Sn gas was achieved by a carbothermal reduction of SnO2 powder. However, we observed no elongation of the nanowire length with an increase of the process time. Nevertheless, an alternating gas exchange between an inert gas (Ar) and an oxygen-containing process atmosphere yielded an elongation of the laterally aligned nanowires, indicating that the nanowire growth takes place in a transient period of the gas exchange.
LSTM and Regression Methods for Stock Market Prediction

-By using stock market prediction, the aim is to predict the values of stocks in the future. There has been a growing interest in stock market prediction technologies via the use of machine learning. This is done by taking the current values of the market after taking previous stock values as the training data. Various Machine learning techniques can be used to make prediction simpler in general. The proposed paper works on the working of 2 different algorithms, the Regression and LSVM based algorithm.
THE IMPACT OF FOREIGN DIRECT INVESTMENT ON CHINESE SOE PERFORMANCE: THE ROLE OF MANAGEMENT DECENTRALIZATION

The research tests the hypothesis that centralization within a Chinese state-owned enterprise (SOE) interacts with (or moderates) industry foreign direct investment (FDI) in predicting performance. The results show that when industry FDI is low, centralized SOEs outperform decentralized and moderately decentralized SOEs. But when industry FDI is high, moderately decentralized SOEs outperform both centralized and decentralized SOEs. These results have significant implications for multinational firms doing business in China, SOE managers, and reform-minded policy makers.
CoCoNuT: combining context-aware neural translation models using ensemble for program repair

Automated generate-and-validate (GV) program repair techniques (APR) typically rely on hard-coded rules, thus only fixing bugs following specific fix patterns. These rules require a significant amount of manual effort to discover and it is hard to adapt these rules to different programming languages. To address these challenges, we propose a new G&V technique—CoCoNuT, which uses ensemble learning on the combination of convolutional neural networks (CNNs) and a new context-aware neural machine translation (NMT) architecture to automatically fix bugs in multiple programming languages. To better represent the context of a bug, we introduce a new context-aware NMT architecture that represents the buggy source code and its surrounding context separately. CoCoNuT uses CNNs instead of recurrent neural networks (RNNs), since CNN layers can be stacked to extract hierarchical features and better model source code at different granularity levels (e.g., statements and functions). In addition, CoCoNuT takes advantage of the randomness in hyperparameter tuning to build multiple models that fix different bugs and combines these models using ensemble learning to fix more bugs. Our evaluation on six popular benchmarks for four programming languages (Java, C, Python, and JavaScript) shows that CoCoNuT correctly fixes (i.e., the first generated patch is semantically equivalent to the developer’s patch) 509 bugs, including 309 bugs that are fixed by none of the 27 techniques with which we compare.
Studies on Trunk Density and Prediction of Starch Productivity of Sago Palm (Metroxylon sagu Rottb.): A Case Study of a Cultivated Sago Palm Garden near Kendari, Southeast Sulawesi Province, Indonesia

This research was carried out in a cultivated sago palm (Metroxylon sagu Rottb.) garden near Kendari, Southeast Sulawesi Province, Indonesia in 2006 to predict the annual starch yield from 2006 to 2015. The average trunk (with trunk height of >0.5 m) density and the average number of trunks in each class of length (at 1 m separation, from 1.0 to 10 m) per hectare were 228 palms/ha and 19 palms/ha, respectively. The trunk elongation rate was estimated to be 1m/year from the coefficient of regression line between the trunk length and the estimated years after trunk formation. The average number of harvestable trunks estimated by the elongation rate per year (1 m/year) and the trunk length at the harvesting stage (ca. 10 m) was 22 palms/ha/year, and the average annual starch yield per hectare was estimated to be 9.0 t from 2006 to 2015 with an average starch yield of 393 kg/palm by chemical analysis of mature palms grown around the surveyed area. However, the starch yield showed a downward trend from 13.5 t/ha in 2006 to 4.3 t/ha in 2015. This trend is caused by the decreasing numbers of harvestable trunks in each subsequent year. The above finding indicates that proper cultivation techniques to maintain a suitable trunk density with different trunk lengths (ages) by appropriate sucker thinning should be established for a stable annual starch production per unit area.
The Analysis of Traffic Flow on the Three-leg Intersection – Case Study Cazin

This paper deals with the analysis of traffic on the three-leg intersection in the city Cazin, at the junction of the three-leg intersection. The main issue of this research refers to the left-turn of vehicles coming from the merging road of the given intersection. The extensive analysis covered the current state of traffic flow by using the software tool, SIDRA INTERSECTION program. Within the suggested measures of improvement, the construction of a unsignalised roundabout was proposed. Implementation of the construction of a unsingalised roundabout would increase the level of traffic safety, reduce time losses while taking a left turn and therefore improve the Level of Service (LOS) as a qualitative indicator of traffic flow.