Miracle-dz/UniFAR-FTUs huggingface dataset:
Bibliometric Survey of Privacy of Social Media Network Data Publishing

We are witness to see exponential growth of the social media network since the year 2002. Leading social media networking sites used by people are Twitter, Snapchats, Facebook, Google, and Instagram, etc. The latest global digital report (Chaffey and Ellis-Chadwick 2019) states that there exist more than 800 million current online social media users, and the number is still exploding day by day. Users share their day to day activities such as their photos and locations etc. on social media platforms. This information gets consumed by third party users, like marketing companies, researchers, and government firms. Depending upon the purpose, there is a possibility of misuse of the user's personal & sensitive information. Users' sensitive information breaches can further utilized for building a personal profile of individual users and also lead to the unlawful tracing of the individual user, which is a major privacy threat. Thus it is essential to first anonymize users' information before sharing it with any of the third parties. Anonymization helps to prevent exposing sensitive information to the third party and avoids its misuse too. But anonymization leads to information loss, which indirectly affects the utility of data; hence, it is necessary to balance between data privacy and utility of data. This research paper presents a bibliometric analysis of social media privacy and provides the exact scope for future research. The research objective is to analyze different research parameters and get insights into privacy in Social Media Network (OSN). The research paper provides visualization of the big picture of research carried on the privacy of the social media network from the year 2010 to 2019 (covers the span of 19 years). Research data is taken from different online sources such as Google Scholar, Scopus, and Research-gate. Result analysis has been carried out using open source tools such as Gephi and GPS Visualizer. Maximum publications of privacy of the social media network are from articles and conferences affiliated to the Chinese Academy of Science, followed by the Massachusetts Institute of Technology. Social networking is a frequently used keyword by the researchers in the privacy of the online social media network. Major Contribution in this subject area is by the computer science research community, and the least research contribution is from art and science. This study will clearly give an understanding of contributions in the privacy of social media network by different organizations, types of contributions, more cited papers, Authors contributing more in this area, the number of patents in the area, and overall work done in the area of privacy of social media network.
Internalização de novos membros em equipes de desenvolvimento de software: benefícios e limitações

Contexto: A internalização de novos membros em equipes de desenvolvimento de software ocasiona mudanças nas organizações. Objetivo: Investigar os benefícios e limitações da internalização em equipes de desenvolvimento de software. Método: Foi realizado um estudo qualitativo em uma startup de desenvolvimento de software onde a internalização foi observada recentemente. Resultados: Os dados coletados foram analisados utilizando técnicas de codificação qualitativa e os resultados foram verificados e validados com os participantes por meio da verificação de membros. Conclusão: Percebeu-se que a internalização sofre forte influência da cultura da empresa e do acolhimento e integração do time.
Skill gap assessment is a key to survive

To ensure that the workforce is well trained, knowledgeable and better equipped to perform the job. Identifying skill gap becomes essential. Skill gap presents an opportunity for the organization and the employees to identify the missing skills and try to gain them. This study analyzed the skill gap between the employees of VASUDHARA Dairy (AMUL), Nagpur and helped in making employees aware of the critical skills they will need to grow. A sample of 60 respondents was considered. The data were collected in 2 phases. At first, the department heads were interviewed and then the questionnaire was prepared based on the parameters communicated by the heads and then it was circulated to the employees. The major findings reveal that most of the employees out of the total sample lack ICT ( Information and communication technology) and thus a skill gap exists in this area.
Composition, color and antioxidant properties of cocoa shell at different roasting temperatures

Cocoa shell is underexploited and is considered as waste. However, roasting cocoa is a fundamental step in producing cocoa products. Composition of the cocoa shell depends on the origin whereas cocoa processing involves fermentation, drying and roasting. However, scarce research has been conducted to analyze the composition of Malaysian cocoa shells at different roasting temperatures. Therefore, this research aims to determine the effect of different roasting temperatures (110, 120, 130, 140 and 150°C) on the proximate composition, colour and antioxidant activity of cocoa shell. Changes in antioxidant activity and polyphenol content were recorded. Fiber and moisture content were significantly (p<0.05) higher in unroasted cocoa shell. However, the protein was found to decrease significantly (p<0.05) after roasting at 150°C (10.93%). Fat content was found higher in roasted cocoa shell at 150°C (6.82%) compared to the unroasted cocoa shell (6.09%). The colour (L value) recorded significantly (p<0.05). the highest for unroasted cocoa shell (51.28) and the lowest at 150°C (47.93), DPPH radical scavenging activity of ethanolic extract of cocoa shell was significantly (p<0.05) higher in 0% ethanol concentration compared to other ethanol concentrations (20, 50, 80 and 100%). The roasted cocoa shell may be considered as a source of natural antioxidants for functional food development and intermediate food ingredient.
A Case Study of the Habitat Changes due to the Restoration of Low-Flow Channel

This present study conducted the impact of the restoration of low-flow channel on fish habitat in a reach of the Wonju Stream, Korea. The target species were Zacco koreanus, a dominant species in the middleand upper-stream of Wonju Stream. The River2D model was used for the computation of the flow and the habitat suitability index model was used to estimate the quantity and quality of fish habitat using habitat suitability curves. In order to restore the study area, the low-flow channel was identified through the bankfull discharge of the study reach, and the best hydraulic section was designed. In addition, various restoration techniques were applied to the low-flow channel through rocks, pool/riffle structures, and the change of the channel width. Simulation results indicated that the restoration of the best hydraulic section effects decreased habitat suitability for the target species. However, when various restoration techniques were applied, the WUA (Weighted Usable Area) was improved by about 11%.
Musical Notation as the Externalization of Imagined, Complex Sound

Henrik Sinding-Larsen analyzes how new tools for the visual description of sound revolutionized the way music was conceived, performed, and disseminated. Early on, the ancient Greeks had described pitches and intervals in mathematically precise ways. However, their complex system had few consequences until it was combined with the practical minds of Roman Catholic choirmasters around 1000 ce. Now, melodies became depicted as note-heads on lines with precise pitch meanings and with note names based on octaves. This graphical and conceptual externalization of patterns in sound paved the way for a polyphonic complexity unimaginable in a purely oral/aural tradition. However, this higher complexity also entailed strictly standardized/homogenized scales and less room for improvisation in much of notation-based music. Through the concept of externalization, lessons from the history of musical notation are generalized to other tools of description, and Sinding-Larsen ends with a reflection on what future practices might become imaginable and unimaginable as a result of computer programming.
Análisis y experimentación con linked data aplicado a la biodiversidad.

Universidad Nacional de Loja has a strong area to enhance within the area of Biodiversity, it is pertinent to highlight the information regarding the Reinaldo Espinosa Botanical Garden, source of many investigations, so far from technology or very little used, therefore, the opportunity is shown to expose through a technological approach the potential to share such information, achieve an important impact and contribution in this area of knowledge, through the incursion of adopting technologies related to Semantic Web and Linked Data. This Degree Work is oriented to: “Define a Semantic Web and Linked Data model focused on the field of Biodiversity”, such that, the expected result of the different processes developed, is a prototype model that uses Semantic Web technologies and Linked Data, to highlight the importance it has in the conservation of Biodiversity. In the explored study area, the “Reinaldo Espinosa Botanical Garden” denotes problems such as the dispersion of knowledge, because the research carried out is scattered in different repositories; like, the difficulty in the process of searching for information, caused by the lack of available digital resources to consult. The main modeling of the resources of Reinaldo Espinosa Botanical Garden as well as the underlying processes after the generation of the model are addressed and executed within the Linked Data Generation and Publication Methodology, for the modeling phase in the creation of the ontology, It was contemplated to use the Methontology methodology, together with the different tools such as Open Link Virtuoso, Pubby, CmapTools, Protege, LodRefine, Tomcat and Apache Jena Fuseki, resources were applied such as the scientific method, experimental method, transcendental for the development of the model prototype. The main contribution of the Degree Work is the development of a prototype model that covers the reality of the data of the Reinaldo Espinosa Botanical Garden, as well as a first vocabulary. Within the future lines, the contribution of researchers to strengthen the model, the development of a tool such as a Biodiversity portal, a semantic application capable of consuming the data of the model afterwards, stands out.
Distributed Control of Wind Farm Power Set Points to Minimise Fatigue Loads

The quantity and size of wind farms continue to grow as countries around the world strive to meet ambitious targets for renewable electricity generation such as the UK government’s Net Zero target of increasing offshore wind energy from current levels (circa 6 GW) to circa 75 GW by 2050. With increasing size and quantity of wind farms, there is a growing requirement to use wind farm level control both to help with grid integration and to minimise the loads on the turbines in the farm. In this paper, a methodology of distributing power set points through a wind farm to minimise the loads on the turbines whilst meeting a delta power set point for the farm is presented. The methodology in this paper uses a hierarchical control structure, in which a network wind farm controller calculates the required change in wind farm power and then passes this value on to a distributed controller that defines the change in power required from each wind turbine. The network wind farm controller calculates a delta change in wind farm power that the wind farm holds in reserve. The distributed controller allocates the reductions in power output by first setting a baseline reduction that considers the steady state tower loads. The baseline is then adjusted to meet the required change in power, distributing the additional change in one of two ways; either proportional to the square of each turbines estimated wind speed or proportional to the initial baseline. Performance is assessed using the StrathFarm simulation tool. The wind turbine models incorporated into StrathFarm are sufficiently detailed to provide the tower and blade loads and the wind field model is sufficiently detailed to represent turbulence, wind shear, tower shadow and wakes and their interaction. The performance of the proposed wind farm controllers are assessed for a range of wind conditions for two 4x4 wind farms of 5MW wind turbines, one closely spaced (500m) and one less closely spaced (1000m). Both the accuracy of the change in power output from the wind farm and the change in turbines DELs are discussed. Depending on the wind conditions, the approach is found to reduce the tower and blade loads by about 10% more than the case in which each turbine is simply allocated the same change in power. There is good accuracy in the change in power at higher wind speeds. Below rated wind speed, wake effects reduce the accuracy of the change in power.
Multi-agent architecture for local electricity trading in power distribution systems

Over the last decade, electricity markets have created competitive environments for complex power systems. The fast growth of distributed energy resources has made it challenging to maintain the reliability and stability of the system. However, conventional energy management strategies are not capable of resolving these concerns centrally due to the volatility of distributed energy resources. Moreover, centralized electricity markets are not complete enough to follow the flexible behavior of consumers due to demand response programs. Therefore, new electricity trading structures are required to provide energy to distribution networks in a decentralized and distributed manner. This work presents a bottom-up energy management approach based on a multi-agent architecture for local electricity trading. Our proposed structure is defined as a class of organization-based multi-agent systems, where each agent has different tasks. These agents consist of distributed energy resources, electrical consumers, prosumers, electric vehicles, aggregators, a distribution system operator and local coordinators of the system. According to the proposed bottom-up approach in our Ph.D. work, decisions of agents in the bottom layer have priority in comparison to agents’ decisions in the upper layers. In this way, our proposed strategy manages energy locally to pursue global-social optimization. Also, different types of electricity commoditiese.g. energy and flexibilitycan be traded locally in the distribution network. In this Ph.D. work, we define different strategies such as decentralized, partially-decentralized and centralized (community-based) for local electricity trading. Here, the challenge is to model a multi-level problem based on the objective function of agents considering uncertainty of the system’s stochastic parameters. In this way, each agent can participate in different types of the electricity transactions on the basis of their corresponding objective functions.
Neonatal Mortality in the Eastern Mediterranean Region: Socio-Demographic, Economic and Perinatal Factors, 1990 - 2013

Background: The neonatal mortality rate (NMR) is considered amongst the most important socioeconomic and health indicators of a community development. Globally, it has been reported that the daily mortality rate during the neonatal period is much higher (30-fold) than the post-neonatal period. In the Eastern Mediterranean Region, about 40% of the under-5 mortality occurs in the neonatal period. This study aimed to explore the association between the socio-economic, demographic and perinatal care related factors, and the neonatal mortality in the Eastern Mediterranean Region. Methods: The secondary data for the 1990 to 2013 on neonatal mortality rates, socio-demographic, socio-economic and health factors were extracted from official websites, including united nations children’s fund (UNICEF), world health organization (WHO), and united nations educational, scientific and cultural organization (UNESCO). Data were collected using the following keywords: ‘neonatal mortality’, ‘perinatal deaths’, ‘child health, education’, ‘expenditure on health’, ‘safe water’, ‘sanitation’ and ‘health indicators’. We used secondary data analysis to explore the relationship between the possible explanatory variables and neonatal mortality using correlation coefficient analysis. Results: There was a noticeable decline in neonatal mortality rates (NMR) among the Eastern Mediterranean countries from 1990 to 2013. The neonatal mortality rate had a negative and significant association with literacy status of both sexes, annual growth rates, antenatal care coverage, birth attendance by skilled health personnel, Gross National Income (GNI), total health expenditure per capita, safe drinking water and adequate sanitation facilities. However, the neonatal mortality rate had significant and positive relationships with maternal mortality ratio, total fertility rate, population size, total births and low birth weight. Conclusion: Despite the fall in the neonatal mortality rate, it remains high in the Eastern Mediterranean countries. Socioeconomic and other related factors appear to play a major role in determining neonatal mortality and there is an inverse relationship between socioeconomic status and the neonatal mortality rate. Neonatal health in Eastern Mediterranean countries needs a more effective and innovative approach to sustain the rapid progress in the overall reduction of child mortality.
Aplikasi Auto Sales Forecasting Berbasis Computational Intelligence Website untuk Mengoptimalisasi Manajemen Strategi Pemasaran Produk

Business analytics plays an important role in optimizing the management of product marketing strategies. One of the most popular analytical tools in business analytics is sales forecasting. Businesses need to conduct sales forecasting to optimize marketing management in the form of product availability predictions, predictions of capital adequacy, consumer interest, and product price governance. However, the problem that is often encountered in forecasting is the number of forecasting methods available so that it makes it difficult for business people to choose the best forecasting method. The aims of this research is to develop a forecasting software tha can be accessed online based on computational intelligence, which is a software that can make forececasting with various methods and then intelligently choose the best forecasting method. The software development method used in this study is the SDLC with waterfall model. The result of this research is the Auto sales forecasting software was developed using the R programming language by combining various package and can be accessed online through the page Http://bakrizal.com/AutoSalesForecasting . This software can be used to conduct forecast analysis with various methods such as Simple Moving Average, Robust Exponential Smoothing, Auto ARIMA, Artificial Neural Network, Holt-Winters, and Hybrid Forecast. This software contains intelligence computing to choose the best forecasting method based on the smallest RMSE value. After testing the sales transaction data at the Futry Bakery & Cake Shop in Makassar, the results show that the Robust Exponantial Smoothing method is the best forecasting method with an RMSE value of 0.829
Integración de las funciones sustantivas de la universidad y relación Universidad-Sociedad-Estado

Uno de los principales desafios de las universidades publicas en la actualidad, es el de contribuir significativamente a construir una sociedad basada en el conocimiento, que afronte con eficacia y equidad, los grandes problemas de las naciones y de la region, lo que debera hacerse por medio de la integracion de sus funciones sustantivas (Docencia, investigacion y Extension), en el marco de su autonomia, por medio de una efectiva relacion con los distintos sectores de la sociedad y el Estado. Las Universidades Publicas siguen siendo para la sociedad instituciones de prestigio, y para conservarlo y fortalecerlo se requiere de una nueva vision, que combine calidad con pertinencia, a fin de responder a las expectativas de la sociedad en la que funcionan y a la que se deben. Las Universidades Publicas de Centroamerica deben cumplir, no solo con el rol de producir, conservar, transmitir y transferir conocimiento, sino tambien servir de gran foro de debate para los grandes problemas nacionales, ser las consultoras de la nacion, de la provincia y de los municipios, asi como el ambito en el cual puedan discutirse las conveniencias, las ventajas, lo aconsejable y lo no aconsejable para la toma adecuada de decisiones en forma participativa, privilegiando el dialogo de saberes y trabajando en forma integrada con la comunidad.
Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification

Modern deep neural networks (DNNs) often require high memory consumption and large computational loads. In order to deploy DNN algorithms efficiently on edge or mobile devices, a series of DNN compression algorithms have been explored, including factorization methods. Factorization methods approximate the weight matrix of a DNN layer with the multiplication of two or multiple low-rank matrices. However, it is hard to measure the ranks of DNN layers during the training process. Previous works mainly induce low-rank through implicit approximations or via costly singular value decomposition (SVD) process on every training step. The former approach usually induces a high accuracy loss while the latter has a low efficiency. In this work, we propose SVD training, the first method to explicitly achieve low-rank DNNs during training without applying SVD on every step. SVD training first decomposes each layer into the form of its full-rank SVD, then performs training directly on the decomposed weights. We add orthogonality regularization to the singular vectors, which ensure the valid form of SVD and avoid gradient vanishing/exploding. Low-rank is encouraged by applying sparsity-inducing regularizers on the singular values of each layer. Singular value pruning is applied at the end to explicitly reach a low-rank model. We empirically show that SVD training can significantly reduce the rank of DNN layers and achieve higher reduction on computation load under the same accuracy, comparing to not only previous factorization methods but also state-of-the-art filter pruning methods.
Ground Forest Inventory and Assessment of Carbon Stocks in Sierra Leone, West Africa

Forest and woodland are renewable natural resources providing basic human necessities. They have the ability to sequester carbon and mitigate climate change. Sustainable forest management is guided by forest mensuration and inventory which include measuring and calculating growth and changes in trees and forests. The objective of the study was to estimate timber resources and carbon stock using simple hand tools in Kasewe and Singamba forests in the southern part of Sierra Leone. All trees with diameter at breast height (DBH) ≥ 10 cm were measured in every plot for DBH, and three trees were measured for height. The correlation between mean wood volume and carbon stock was highly significant. For Kasewe plantation forest, mean wood volume and carbon stock were 151 m3 ha−1 and 44 t C ha−1, respectively, and for the Singamba natural forest, they were 181 m3 ha−1 and 82 t C ha−1, respectively. The linear correlation between basal area and volume, DBH and volume and basal area and total biomass was significant for the plantation species tested. Realistic national forest inventory and community forestry are inevitable for sustainable forest management in Sierra Leone.