Reviewerly/exHarmony huggingface dataset:
Features Extraction based on an Origami Representation of 3D Landmarks

Feature extraction analysis has been widely investigated during the last decades in computer vision community due to the large range of possible applications. Significant work has been done in order to improve the performance of the emotion detection methods. Classification algorithms have been refined, novel preprocessing techniques have been applied and novel representations from images and videos have been introduced. In this paper, we propose a preprocessing method and a novel facial landmarks' representation aiming to improve the facial emotion detection accuracy. We apply our novel methodology on the extended Cohn-Kanade (CK+) dataset and other datasets for affect classification based on Action Units (AU). The performance evaluation demonstrates an improvement on facial emotion classification (accuracy and F1 score) that indicates the superiority of the proposed methodology.
Toward a contextual quality of service evaluation approach

The Quality of Service (QoS) evaluation techniques are required because web services having same functional properties are not a guarantee to have the same quality. This paper deals with a new QoS evaluation method for web services. The objective of the proposed approach is to offer the use of the existing QoS evaluation/assessment methods in constructing a new contextual QoS evaluation approach. The proposed approach is a multi-layer technique specified with the MAP formalism. The principle of the proposed contextual-oriented modelling approach is to guide the evaluator during all web services evaluation steps using different methodologies at varied levels of abstractions. A better understanding of the major web services quality factors that affect QoS will help QoS evaluators to judge the most appropriate QoS evaluation approach corresponding to their user and business requirements with more flexibility in personalising the QoS evaluation process.
Comparison of C4.5 Algorithm, Naive Bayes and Support Vector Machine (SVM) in Predicting Customers that Potentially Open Deposits

This research is based on the application of data mining processing to produce information that is useful in helping decision making. In this study aims to determine the superior algorithm between C4.5, Naive Bayes and SVM algorithms in predicting which customers who have high potential to open deposits. The data used in this study is secondary data where its data is obtained from the UCI dataset. The comparison results of the accuracy value of C4.5 Algorithm 90.57%, accuracy of Naive Bayes 87.70% and SVM 89.29%. Based on the results of the comparison of accuracy values, it is found that the C4.5 algorithm has the highest level of accuracy. So that the application of supporting applications to predict customers who have the potential to open deposits uses the rules for establishing C4.5 data processing.
IMPLEMENTASI PENGEMBANGAN SISTEM LAPORAN BKD (STUDI KASUS BKD ONLINE KOPERTAIS WILAYAH I DKI JAKARTA)

Implementation of BKD Report Software Development (Case Study of BKD Online Kopertais Region I DKI Jakarta). In the era of information technology advancement today, there are almost no institutions or organizations that do not involve information technology in order to improve the quality of management services for these institutions. The BKD (Lecturer Performance Performance) report so far, which is coordinated by Kopertais 1 DKI Jakarta Region has not been fully optimal and efficient, because it is still managed manually. Therefore, in early 2018, the BKD Report for the Jul-Dec Period 2017, Kopertais 1 DKI Jakarta Region implemented BKD Report assessment policy by online. This application was built using PHP programming language and PostgreSQL database with Laravel framework. The implementation of this policy is not only intended to make the BKD Report more organized, optimal and efficient, it is also expected that all PTKIS lecturers under Kopertais 1 DKI Jakarta Region will eventually be able to take advantage of information technology progress in order to develop scientific quality in accordance with their fields of science.
The effects of a fault management architecture on the performance of a cloud based application

Increasingly, the application providers are using a separate fault management system that offers out-of-the-box monitoring and alarms support for application instances. A fault management system usually consists of a set of management components that does both fault detection and can trigger actions, for example, automatic restart of monitored components. Such a distributed structure supports scalability and helps to ensure that an application meets its quality requirements. However, successful recovery of an application now depends on the fault management architecture and the status of the management components. This thesis presents a model that accounts for the effect of management-architecture based coverage on the mean throughput of an application. Such a model would benefit the application providers for choosing the right fault management architecture for their applications. Comparing five different sample fault management architectures, shows that for higher workload, the case with highest number of detection paths has the maximum throughput.
Sanctuary: documentary in virtual reality (VR)

Sanctuary is a documentary film in virtual reality (VR). The film uses 360-camera technology to offer a sensory immersive viewing experience. The film attempts to transcend the borders of filmmaking by merging new 360-camera technology and a nonlinear form of storytelling. The film is an observational piece. 360-degree videos are an emerging technology, which offers the viewer a sensory, immersive experience in virtual reality. Influenced by the 360-panoramic mural paintings created in 1860s, the use of the 360-camera breaks away from the syntax of documentary filmmaking and gives the audience an active role in the film-viewing experience. It breaks the traditional semantics of filmmaking and sets new rules of viewing which are personal and unique to each viewer. Sanctuary documents the Juhasz family, which has been living in a church since November 2014. The film is an eight-minute experience that gives the audience a 360- degree glimpse into the Juhasz family’s life and their living conditions. The film is presented as an installation, using Samsung’s Gear VR as the exhibition technology.
Aprendizado de máquina: breve introdução e aplicações

In this article, some complex real world problems are described, which are faced by industry and academy, for which Machine Learning methods are used. This study also presents classification methods used in many research areas, such as Bioinformatics. In addition, a literature review of Machine Learning methods applied to agriculture and livestock was performed. Finally, the study presents some research groups of Embrapa, the academy and the industry that use Machine Learning method.
Provide a New Encryption Algorithm for Medical Images and Evaluate the Proposed Algorithm

Introduction :  In this paper, an encryption algorithm for the security of medical images is presented, which has extraordinary security. Given that the confidentiality of patient data is one of the priorities of medical informatics, the algorithm can be used to store and send medical image. Material and Methods :  In this paper, the solutions of chaotic differential equations are used to generate encryption keys. This method is more than other methods used in encoding medical images, resistant to statistics attacks, low encryption and decryption time and very high key space. In the proposed algorithm, unlike other methods that use random key generation, this method uses the production of solutions of the chaotic differential equations in a given time period for generating a key. All simulations and coding are done in MATLAB software. Results :   Chaotic Differential Equations have two very important features that make it possible to encode medical images. One is the unpredictability of the system's behavior and the other is a severe sensitivity to the initial condition. Conclusion : These two features make the method resistant to possible attacks to decode the concept of synchronization chaotic systems. Using the results of the method, medical information can be made safer than existing ones.
Сложная динамика неавтономного осциллятора с управляемой фазой внешнего воздействия

AbstractThe dynamics of a non-autonomous oscillator in which the phase of external force linearly depends on a dynamic variable has been investigated. This control of the external-drive phase leads to the formation of a hierarchy of various periodic and chaotic oscillations. The structure of the space of control parameters has been studied. It is established that dynamics of the system exhibits oscillatory regimes analogous to those of a non-autonomous oscillator with potential in the form of a periodic function.
BREAST CANCER DIAGNOSIS USING A MINKOWSKI DISTANCE METHOD BASED ON MUTUAL INFORMATION AND GENETIC ALGORITHM

Breast cancer is one of the most frequently diagnosed cancers and can lead to death in women worldwide. Diagnosing breast cancer is one of the most challenging tasks as symptoms may only be present in later stages. This paper presents a mutual information genetic algorithm (MIGA) where MIGA is a combination of two algorithms, mutual information (MI) and genetic algorithm (GA). The method of this work is as follows: attributes of breast cancer patients were collected using the Breast Cancer Wisconsin Diagnostic dataset. A breast cancer diagnosis system was developed using a GA and hybrid algorithm (genetic and K-nearest neighbour) and then used MI and GA. GA fitness was calculated using the Minkowski distance method. The obtained solutions are verified for three algorithms (GA, GA+KNN, and MIGA). Finally, the proposed MIGA algorithm results show that the highest accuracy (99%) obtained with the GA-based MI features.
Software Engineering for Smart Cyber-Physical Systems

Smart Cyber-Physical Systems (sCPS) are a novel kind of Cyber- Physical Systems engineered to take advantage of large-scale cooperation between devices, users and environment to achieve added value in face of uncertainty and various situations in their environment. Examples of sCPS include modern traffic systems, Industry 4.0 systems, systems for smart-buildings, smart energy grids, etc. The uniting aspect of all these systems is that to achieve their high-level of intelligence, adaptivity and ability to optimize and learn, they heavily rely on software. This makes them software-intensive systems, where software becomes their most complex part. Engineering sCPS thus becomes a recognized software engineering discipline, which however, due to specifics of sCPS, can only partially rely on the existing body of knowledge in software engineering. In fact, it turns out that many of the traditional approaches to architecture modeling and software development fail to cope with the high dynamicity and uncertainty of sCPS. This calls for innovative approaches that jointly reflect and address the specifics of such systems. This paper maps the discussions and results of the Third International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS 2017), which specifically focuses on challenges and promising solutions in the area of software engineering for sCPS.
Opportunities for Student Members [The Way Ahead]

Discusses the opportunities for students to join the IEEE.
Assessing the Adequacy of Synthetic Programs for Learning SPF's Configurations

Static program analysis is a powerful technique that reasons about a program's behavior without actually executing the program. To balance between the precision and the efficiency of an analyzer, developers often manually tune-up analyzer's parameters for a specific program. However, this task can be tedious and time-consuming. To automate the search for the optimal parameters for a program, researchers employ machine learning (ML) techniques, that from the existing data learn the relationship between the program and the optimal parameters, which it encodes in an ML model. The existing, or training, data set, plays an important role in the correctness of an ML model. In this work we investigate whether automatically generated programs are adequate for training an ML model, which determines SPF's configurations for a given Java method. To do this, we compare the performance of a model trained on real programs with that of a model trained on synthetic programs. Our results indicate that while synthetic programs are inadequate for training a model alone, adding them to the training set of real programs improves the classification power of the resulting model.
Policy Recommendations for Africa

Abstract This section presents comprehensive policy recommendations for Africa. The overarching theme is ‘the need for drastic turnaround’. An important question asked here is: ‘What induces people to act?’ The mechanism of incentives and sanctions, and how they should be framed to make societies developmental, are elaborated upon. The chapter assesses the present structure of economic development in Africa and points out the essential principles or elements that are lacking. Out of this, a new development formula for Africa is deduced. The author also touches upon government reform and economic policies. In closing, he stresses the need for education in ethics and mindset change.
Side-Channel Analysis via Symbolic Execution and Model Counting

An important problem in computer security is the detection of side-channel vulnerabilities. Information gained by observing nonfunctional properties of program executions (i.e., sidechannels such as execution time or memory usage) can enable attackers to infer secrets that the program accesses (such as a password). In this talk, I will discuss how symbolic execution, combined with a model counting constraint solver, can be used for quantifying side- channel leakage in Java programs. I will also discuss automata-based model counting techniques. We have implemented these techniques by integrating our modelcounting constraint solver, called Automata-Based model Counter (ABC), with the symbolic execution tool Symbolic Path Finder (SPF).
Research on Evaluation of Soil Fertility Resource Space Based on Regional Hotspots and Clustering Method

Based on each unit of Nong’an County, With ArcGis software platform, the establishment of a part of the total nitrogen in the soil attribute data Nong’an topsoil fertility resources, phosphorus, potassium and organic matter and effective nutrient database, Global Clustering and outlier analysis and hot spot analysis of the autocorrelation method, the county topsoil fertility resources were analyzed and evaluated. The results for farmland protection and optimal layout policy to provide a reference for the theory and methods, but also on the implementation of the agricultural work provides precise basis for decision making.
“Edu Game Monopoly” Media Development On Sosial Arithmetic Material Of Junior High School

The purpose of this research is to develop a decent monopoly edugame media product on social arithmetic material with the concept of learning while playing. To support media feasibility, process of media expert validation, material expert validation, teacher response and student trials are conducted. The feasibility assessment includes three aspects: the aspects of media engineering, social communication aspects and learning aspects. The research method used is research and development of R &amp; D, Borg and Gall model that has been modified into five stages consisting of (1) requirement analysis stage, (2) planning stage, (3) early product development stage, (4) validation and trial stage, and (5) final product stage. The results of research and development shows that: Assessment of feasibility in terms of the above three aspects have been obtained percentvage of 90.3%. In accordance with the conversion table of achievement level on a scale of 5, the value is obtained with the qualification of "Very Good". Thus, it can be concluded that the development of monopoly edugame media in this study is "Eligible" to be used as a medium of learning on the social arithmetic material of Junior High School.
An Analysis of Zeno’s View Regarding Motion

Zeno of Elea (about 489 BC), is the favorite disciple of Parmenides (about 514 BC).Zeno devotes himself in refuting the views of the opponents of Parmenides.Arguments against the possibility of motion, is first found in 'The Dialectic of Zeno'.To examine the reality of motion, it is necessary to make a new look towards Zeno's reaction on motion.The ancient Greek philosophers are confused to think about space, time and motion.Zeno is the first who deeply thinks about these.His arguments, generally known as his paradoxes, seem to show that motion is simply an illusion which is not possible in any circumstances.Arguments of Zeno are based upon the argument which may be called the antinomy, i.e., a proof that since two contradictory propositions equally follows from a given assumption that must be false of infinite divisibility.But in our times, we know that the fallacies of his proofs, the confusion of the infinite divisibility of space and time with infinite dividedness, he does not notice himself.He argues from the geometrical line to the actual line.Indeed, a geometrical point has no magnitude and a geometrical line is infinitely divisible.But in everyday life the movement between any distance, is not infinitely divisible, nor any observed time which we live through as short or long, is infinitely divisible into moments.Zeno confused an analytic proposition with a synthetic proposition.An analytic proposition does not require any observation to confirm or disconfirm its truth while a synthetic proposition can be true if it corresponds to an actual state of affairs.A distance or time is infinitely divisible, is only an analytic proposition but actual distance traversed in same observed time is not infinitely divisible.Without motion our usual life would be stopped.Sun, moon, stars, planets and other stars cannot move without motion.If motion is not accepted then astronomy would be in vein.Even we cannot speak and write without the movement of our vocabulary organs and that of fingers respectively.So, the existence of motion has to accept in usual life, in scientific research and in all other aspects of life.
Self - Regulated Strategy, Effect on Self - Efficacy and Well - Being of the Students with Learning Disability

BackgroundSelf -regulation and self -regulated learning in particular have gained a lot of focus lately in general and special education.Self -regulated strategy is a highly flexible and fluid approach.The strategy offers a lot of ease of implementation as regards being reordered, combined and modified.This makes it an appealing approach to put to use in mainstream inclusive classrooms. Method & Tools The present study employed a true experimental design. The specific design used was Pre-test -Post-test Control Group Design. The psychological tools used to conduct the present study were Self-Efficacy Scale (SES-SANS) by (Singh & Narain, 2014) and General Well-Being Scale (GWBS-KADA). The results The intervention in self -regulated strategy caused significant changes in all dimensions of self -efficacy i.e. self -confidence, efficacy expectation, positive attitude and outcome expectation. A significant change was seen even in the total self -efficacy scores. Similarly, intervention in self -regulated strategy also led to significant changes in the well -being scores across all the dimensions of physical well -being, emotional well -being, social well -beingand school well -being.Significant changes were also seen for overall or total well -being scores. ConclusionThe present study makes a good case for self -regulated strategy as a promising intervention approach for students with learning disabilities in particular and students facing learning issues or problems in general in the mainstream classrooms of the inclusive school environment.
Mobile Based Application of Document Delivery (Case Study: PT Waindo Specterra)

The document delivery process at PT Waindo SpecTerra is still running manually.Problems arising from road documents that have been received need to be inputted into digital format by admin, travel documents are lost and not stored properly, so that entry data process by admin becomes disrupted.The purpose of this study are the availability of a mobile application that facilitates Company Admin and Driver in sending documents process, data delivery history that's directly stored in the database, and backup data in a structured database.This application uses the PHP programming language, HTML, MySQL Database, and Apache Cordova technology in the development of mobile-based systems.The research method used are library method, observation method and documentation method.The final researches are expected to provide an application system that can facilitate the process of sending documents at PT Waindo SpecTerra, so the road history data is more structured and backup data is available.
JPEG Steganalysis Based on Multi-Projection Ensemble Discriminant Clustering

In this paper, we propose a novel algorithm called multi-projection ensemble discriminant clustering (MPEDC) for JPEG steganalysis. The scheme makes use of the optimal projection of linear discriminant analysis (LDA) algorithm to get more projection vectors by using the micro-rotation method. These vectors are similar to the optimal vector. MPEDC combines unsupervised K-means algorithm to make a comprehensive decision classification adaptively. The power of the proposed method is demonstrated on three steganographic methods with three feature extraction methods. Experimental results show that the accuracy can be improved using iterative discriminant classification.
Attempt of JiTT Based on Cloud-Based Class—Review of Acid Properties as Example

Feedback is the lifeline of classroom teaching. In teaching, how to immediately feedback students' learning situation is often based on the teacher's subjective judgment. Teaching based on Cloud-based Class is one of the ways to try to realize JiTT teaching. Taking the teaching of the review of acid properties in the junior middle school chemistry class as an example, the author tries the JiTT teaching mode, uses the Cloud-based Class to realize the real-time interaction, resource push and homework tasks between teachings, and records the students' learning behaviors in real time through cloud services to achieve process evaluation and individualized teaching. According to the platform characteristics of the Cloud-based Class, JiTT teaching mode theory, combined with the practical experience of junior middle school chemistry teaching, the teaching strategy model based on Cloud-based class is proposed. The teaching model has three advantages. First, teaching feedback is more efficient, second, participation motivation is stronger, and third, process evaluation is more scientific. At the same time, it also puts forward three points of thinking based on the teaching model. Firstly, it should pay attention to the consistency of teaching objectives, teaching activities and evaluation. Secondly, the construction of information-based teaching environment is the basis for the curriculum integration. Finally, the school and parents’ concept change is a guarantee for blended learning.