Reviewerly/exHarmony huggingface dataset:
A Compact Deep Learning Model for Robust Facial Expression Recognition

In this paper we are proposing a compact CNN model for facial expression recognition. Expression recognition on the low quality images are much more challenging and interesting due to the presence of low-intensity expressions. These low intensity expressions are difficult to distinguish with insufficient image resolution. Data collection for FER is expensive and time-consuming. Researches indicates the fact that downloaded images from the Internet is very useful to model and train expression recognition problem. We use extra datasets to improve the training of facial expression recognition, each representing specific data source. Moreover, to prevent subjective annotation, each dataset is labeled with different approaches to ensure annotation qualities. Recognizing the precise and exact expression from a variety of expressions of different people is a huge problem. To solve this problem, we proposed an Emotion Detection Model to extract emotions from the given input image. This work mainly focuses on the psychological approach of color circle-emotion relation[1] to find the accurate emotion from the input image. Initially the whole image is preprocessed and pixel by pixel data is studied. And the combinations of the circles based on combined data will result in a new color. This resulted color will be directly correlated to a particular emotion. Based on the psychological aspects the output will be of reasonable accuracy. The major application of our work is to predict a person’s emotion based on his face images or video frames This can even be applied for evaluating the public opinion relating to a particular movie, form the video reaction posts on social Medias. One of the diverse applications of our system is to understand the students learning from their emotions. Human beings shows their emotional states and intentions through facial expressions.. Facial expressions are powerful and natural methods that emphasize the emotional status of humans .The approach used in this work successfully exploits temporal information and it improves the accuracies on the public benchmarking databases. The basic facial expressions are happiness, fear, anger, disgust sadness, and surprise[2]. Contempt was subsequently added as one of the basic emotions. Having sufficient well labeled training data with variations of the populations and environments is important for the design of a deep expression recognition system .Behaviors, poses, facial expressions, actions and speech are considered as channels, which convey human emotions. Lot of research works are going on in this field to explore the correlation between the above mentioned channels and emotions. This paper highlights on the development of a system which automatically recognizes the
Literasi Informasi Digital: Tantangan Bagi Para Santri Dalam Menjalankan Peran Sebagai Global Citizen (Studi Kasus Pada Pondok Pesantren Darussa”Adah Bandar Lampung)

The purpose of this research is to increase knowledge and understanding as well as digital literacy of the Darussa'adah Islamic Boarding School students in Bandar Lampung about the importance of access and adoption of healthy and safe internet technology. The research method used is descriptive quantitative with data collection techniques using surveys. The results of this study indicate that the mastery of the concept of global citizenship by the students still cannot be understood explicitly, so that further understanding of the students is needed. Most of the students of Darussa'adah Islamic Boarding School still do not have digital literacy skills effectively and efficiently. By doing digital literacy, it is expected to be able to better understand and be able to have cognitive, communicative abilities, have the ability in creativity, have self-confidence and have a critical attitude in consuming media so as to avoid hoax and fake news, so that information received through social media can accountable for the truth. The conclusion of this study is the need to provide a set of literacy competencies, especially digital literacy when surfing the internet, including the importance of how to access the internet in a healthy and safe manner for students and a basic understanding of ethics and culture as well as searching for the right information on the internet, so that students can face challenges as global citizenship.
A Table Segmentation and Text Information Extraction Method for Power Work Ticket

Manually extracting the information in the power work ticket is not only time-consuming, but also troublesome. With the maturity of optical character recognition (OCR) technology, it has become possible to automatically extract information from electronic documents. However, the power work ticket contains a lot of tabular data. The complex table structure often makes the recognition result of tabular data chaotic. In this paper, a method for automatically extracting text information in the work ticket is proposed. It contains two parts: work ticket table segmentation and text information extraction. In the table segmentation part, we first extract the table frame lines through a combination of corrosion and expansion operations. Then, the cell image is segmented based on the extraction result of the table frame lines. As for text information extraction, an OCR model based on CRNN is used. In order to obtain effective information, it is necessary to search and match keywords in the recognition results through regular expressions. At the end of this paper, the feasibility of the proposed method is verified by the experiment.
A Dockers Storage Performance Evaluation: Impact of Backing File Systems

This paper reports on an in-depth examination of the impact of the backing filesystems to Docker performance in the context of Linux container-based virtualization. The experimental design was a 3x3x4 arrangement, i.e., we considered three different numbers of Docker containers, three filesystems (Ext4, XFS and Btrfs), and four application workloads related to Web server I/O activity, e-mail server I/O activity, file server I/O activity and random file access I/O activity, respectively. The experimental results indicate that Ext4 is the most optimal filesystem, among the considered filesystems, for the considered experimental settings. In addition, the XFS filesystem is not suitable for workloads that are dominated by synchronous random write components (e.g., characteristical for mail workload), while the Btrfs filesystem is not suitable for workloads dominated by random write and sequential write components (e.g., file server workload).
An Assessment of the Triple Bottom Line Concept on CSR Effort in FMCG in Nigeria

This paper scanned the history, impact, nature, and objective of CSR in Nigeria using the triple bottom line concept-TBL- (profit, people, and the planet). The primary focus of the study was to launch the impacts of TBL concepts of CSR in multinationals in the non-oil sector (FMCG) using Lagos as a CSR engagement. CSR or Communal responsibility aimed at bringing development, specifically in the rural communities, and the less privileged. In situations like Nigeria, where the infrastructural facilities are either not available or insufficient standard of living continuously declined. This research is critical because there is a dearth of development and governments are no longer able to meet the needs. This research is against the pursuit to use CSR in solving societal problems, but rather investigate whether multinationals have actually used its corporate social responsibility initiatives to meet human development and infrastructural need of its host communities, which suffer displacement, loss of livelihood, environmental pollution and work hazard as a result of their production. This paper also addressed the CSR gap and to evaluate the impact of existing CSR Practices on the economic, environmental, and social bottom line in human development by explaining driving forces that mandate adherence to organizational, Ethical, Environmental, human rights and working conditions, occupational health and safety practices within the ambits of existing laws in Nigeria. Conclusion and recommendations were given among are the Political will to sponsor a bill in the hallow chambers that will firmly establish corporate ethics among the firms in Nigeria specifying rights, responsibilities, and enforcement of each party. It is believed that at the end of this paper, the readers and the audience would have greatly added to their understanding of the comprehensive meaning of CSR in Nigeria and the world at large
A multi-scale methodology of turbine blade surface recovery based on photometric stereo through fast calibrations

This paper proposed a multi-scale measurement methodology for turbine blade, which is able to evaluate the geometrical features of turbine surface in different scales. A turbine blade measurement system is designed by using LED illuminators in this work. To ensure the efficiency and the accuracy of our system during the scale transition, a fast light source calibration method is introduced with a special designed calibration target, where with only one camera snapshot, the position and the orientation of a LED can be calibrated precisely and simultaneously. A surface reconstruction algorithm via iteration is improved by analyzing the LED radiant intensity distribution. The simulation is carried out with a synthetic hyperboloid structure, where the root mean square error (RMSE) of rebuilding is lower than 1.7 µm, and the mean angular error(MAE) of normal estimation is 0.5°. System calibration is performed by using a USAF 1951 calibration target with 3 different scales with the minimum deviation below 4 µm. Experiments are implemented on the concave and the tenon of a turbine blade from civil aero engine, where the profile, the size of the cooling hole and the roughness are retrieved successfully in different scales, which shows the great potential of the proposed methodology in blade inspection applications.
Planning inspection flights with an inhomogeneous fleet of micro aerial vehicles

We consider the problem of planning an inspection flight to a given set of waypo- ints using an inhomogeneous fleet of multirotor, battery-driven micro aerial vehicles (MAVs). Therein, two subproblems must be solved. On the one side, the detailed trajectories of all MAVs must be planned, taking technical and environmental restrictions into account and on the other side, the MAVs must be assigned to the waypoints considering their installed equipment. The goal is to visit all waypoints in minimal time. The strong interaction of the two subproblems makes it necessary to tackle them simultaneously. Several aspects are taken into account to allow realistic solutions. A two-level time grid approach is applied to achieve smooth trajectories, while the flight dynamics of the MAVs are modeled in great detail. Safety distances must be maintained between them and they can recharge at charging stations located within the mission area. There can be polyhedral restricted air spaces that must be avoided. Furthermore, weather conditions are incorporated by polyhedral wind zones affecting the drones and each waypoint has a time window within it must be visited. We formulate this problem as a mixed-integer linear program and show whether the state-of-the-art numerical solver Gurobi is applicable to solve model instances.
Relative Time Quantum-based Enhancements in Round Robin Scheduling

Modern human life is heavily dependent on computing systems and one of the core components affecting the performance of these systems is underlying operating system. Operating systems need to be upgraded to match the needs of modern-day systems relying on Internet of Things, Fog computing and Mobile based applications. The scheduling algorithm of the operating system dictates that how the resources will be allocated to the processes and the Round Robin algorithm (RR) has been widely used for it. The intent of this study is to ameliorate RR scheduling algorithm to optimize task scheduling. We have carried out an experimental study where we have developed four variations of RR, each algorithm considers three-time quanta and the performance of these variations was compared with the RR algorithm, and results highlighted that these variations performed better than conventional RR algorithm. In the future, we intend to develop an automated scheduler that can determine optimal algorithm based on the current set of processes and will allocate time quantum to the processes intelligently at the run time. This way the task performance of modern-day systems can be improved to make them more efficient.
Exponential Graph is Provably Efficient for Decentralized Deep Training

Decentralized SGD is an emerging training method for deep learning known for its much less (thus faster) communication per iteration, which relaxes the averaging step in parallel SGD to inexact averaging. The less exact the averaging is, however, the more the total iterations the training needs to take. Therefore, the key to making decentralized SGD efficient is to realize nearly-exact averaging using little communication. This requires a skillful choice of communication topology, which is an under-studied topic in decentralized optimization. In this paper, we study so-called exponential graphs where every node is connected to $O(\log(n))$ neighbors and $n$ is the total number of nodes. This work proves such graphs can lead to both fast communication and effective averaging simultaneously. We also discover that a sequence of $\log(n)$ one-peer exponential graphs, in which each node communicates to one single neighbor per iteration, can together achieve exact averaging. This favorable property enables one-peer exponential graph to average as effective as its static counterpart but communicates more efficiently. We apply these exponential graphs in decentralized (momentum) SGD to obtain the state-of-the-art balance between per-iteration communication and iteration complexity among all commonly-used topologies. Experimental results on a variety of tasks and models demonstrate that decentralized (momentum) SGD over exponential graphs promises both fast and high-quality training. Our code is implemented through BlueFog and available at https://github.com/Bluefog-Lib/NeurIPS2021-Exponential-Graph.
Documenting factors influencing children like learning English as a foreign language

When English is not only spoken by native speakers of English, English places itself more confidently in all aspects of life, including in the field of Education, and even learned by people with a variety of ages, including children. In an Asian country, particularly, Indonesia, children or young learners have opportunities to learn English from formal classroom instruction to non-formal education. However, since English in Indonesia spreads very largely, this inspires educators to open non-formal education that is English classes conducted outside of school curriculum, and held outside of formal classroom instruction. There are some Indonesian children taking these opportunities by attending the classes and programs offered. The aim of the study is to identify reasons why children like learning English. This study is gathering evidence on what factors that influence children like learning English. Data is obtained from one on one interview. The results of study indicate that there are a variety of reasons on why children like learning English in this context. The results of the interview show that five factors, namely, student level factors, parent level factors, teacher level factors, classroom level factors, and school level factors have a contribution on why children like learning English. The results of the study can be used to provide better assistance for students in order that educational goals can be met. In the future, the results of the study can be used to develop a model of teaching and learning English for children.
LEONARDO DA VINCI’S AND NICOLAUS STENO’S GEOLOGY

Anniversaries for the two founding fathers of geology occurring in the same year prompted a comparative evaluation of how the two contributed to establishing the basic principles of the discipline. To do so, passages from their publications, codices and manuscripts have been quoted directly. The Stenonian principles (‘original horizontality’, ‘original continuity’, and ‘superposition of individual strata’) are present in Leonardo’s notebooks amazingly formulated, using similar wording when studying the same area more than 150 years earlier. Also, Stenonian priority in naming and explaining geological concepts and processes (e.g., faulting, folding, angular unconformity, relative chronology) are mirrored in Leonardo’s writings and pictorial works. While Steno enjoys priority in stepwise restoration of the geological history of a given region, Leonardo was the first to construct a 3D geological profile representation and geomorphologic maps. Lastly, the paper focuses on diverging stances of the two savants about the Noachian Deluge and the age of the Earth. Already 500 years ago, Leonardo had solved the question of marine fossil remains of organic origin found in the mountains implying the possibility of deep geologic time in a statement of ‘eternalism’. 350 years ago, Steno solved the same question in a different way in which he retained a basic role for the Deluge and assumed a short age for the Earth by focusing mainly on short-lived sedimentary and geomorphologic processes.
Map Reduce Based Optimized Frequent Subgraph Mining Algorithm for Large Graph Database

Distributed System, plays a vital role in Frequent Subgraph Mining (FSM) to extract frequent subgraph from Large Graph database. It help to reduce in memory requirements, computational costs as well as increase in data security by distributing resources across distributed sites, which may be homogeneous or heterogeneous. In this paper, we focus on the problem related complexity of data arises in centralized system by using MapReduce framework. We proposed a MapReduced based Optimized Frequent Subgrph Mining (MOFSM) algorithm in MapReduced framework for large graph database. We also compare our algorithm with existing methods using four real-world standard datasets to verify that better solution with respect to performance and scalability of algorithm. These algorithms are used to extract subgraphs in distributed system which is important in real-world applications, such as computer vision, social network analysis, bio-informatics, financial and transportation network.
Relação da Qualidade de Vida e as Doenças Crônicas/ Relationship between Quality of Life and Chronic Diseases

Introduction:The term quality of life has been widely discussed nowadays, due to the increase in life expectancy and the constant search for a more quality experience.When talking about quality of life, daily habits are included, which can be harmful to health, such as sedentary lifestyle, harmful use of alcohol, smoking, inadequate diet and stress, which are considered risk factors that reduce the quality of life, being associated with chronic non-communicable diseases (NCDs).Such illnesses usually last over time, usually do not resolve spontaneously and are rarely cured, completely altering the individual's daily life.Objective: To present the possible relationships between quality of life with the onset of chronic diseases and adherence to treatment.Methodology: A bibliographic survey of articles was carried out on the topic of non-communicable chronic diseases, quality of life and daily habits.Search databases of Academic Google, Medline, Bvs, Lilacs, Scielo, Pubmed, among others, were used, using as search descriptors the key words: quality of life, quality of life and health, daily habits of the Brazilian population, chronic diseases non-communicable, factors that interfere with treatment adherence.Prioritizing publications in Portuguese, between 2010 and 2018, with articles that established analyzes of the Brazilian population.Results and Discussions: From the analysis of 34 articles, it was possible to observe the influence of the quality of life of Brazilians in the development of chronic diseases, as it is related to the behavior and habits of individuals, which can be harmful to health.These risk factors, many present in the Brazilian population, can cause intermediate risks such as increased blood pressure, high glucose level, high lipid concentration and overweight.Stress and depression are other risk factors, as they can cause a deregulation of the biological system, increasing the risk of developing diseases such as diabetes, hypertension, various types of cancer, among others.In turn, the development of chronic diseases causes several impacts on the individual's QoL, such as their physical and mental capacity and their independence.Conclusion: It is concluded that the low level of quality of life predisposes to the development of non-communicable chronic diseases.With its diagnosis, there is a worsening, greater or lesser, in the QoL, depending on the individual's psychological structure, which also influences treatment adherence, responsible for a pos.
UTOPIA OF GLOBAL EDUCATION

It is an multidisciplinary, peer reviewed, refereed publication, publishesÂ  narrative,Â  theoreticalÂ  andÂ  empirically-basedÂ  researchÂ  articles,Â  student reflections,Â  andÂ  bookÂ  reviewsÂ  relevantÂ  toÂ  internationalÂ  studentsÂ  andÂ  theirÂ  cross cultural experiences and understanding. Published biannually, the Journal encourages the submission of manuscripts from around the world, and from a wide range of academic fields, including comparative education, international education, student affairs, linguistics, psychology, religion, sociology,Â  business,Â  socialÂ  work,Â  philosophy,Â  andÂ  cultureÂ  studies. The initiative of publication UTOPIA is taken to report new perception and vision about the role that education plays in the development of human beings through intelligentsia.
Deteksi Kematangan Buah Jambu Kristal Berdasarkan Fitur Warna Menggunakan Metode Transformasi Ruang Warna Hsv (Hue Saturation Value) Dan K-Nearest Neighbor

Guava has properties that are easily damaged, improper handling of guava fruit can result in a decrease in quality and quality. In general, to measure maturity is still done manually, the weakness of this method is the level of accuracy that is not consistent and tends to experience errors. Utilization of images is very important to determine the maturity of guava fruit by utilizing digital images. With the existence of digital images, to determine the maturity of guava fruit based on its color, it can be done computing (technology-based), namely by applying image processing using the HSV (Hue, Saturation, Value) color space transformation method. The HSV (Hue, Saturation, Value) color model groups the intensity components of the carried color information (hue and saturation) in image colors. The results of the ripeness detection can be seen in each test with a percentage value of 91.67% for the ripe guava category, 90% for the raw guava fruit category. The percentage value for testing the overall data has a good percentage value which is influential in detecting the maturity of crystal guava, which is 95%. So it can be concluded that the detection of ripeness of crystal guava fruit can be done by applying the HSV color space transformation method.