Reviewerly/exHarmony huggingface dataset:
Representing Fitness Landscapes by Valued Constraints to Understand the Complexity of Local Search

Local search is widely used to solve combinatorial optimisation problems and to model biological evolution, but the performance of local search algorithms on different kinds of fitness landscapes is poorly understood. Here we introduce a natural approach to modelling fitness landscapes using valued constraints. This allows us to investigate minimal representations (normal forms) and to consider the effects of the structure of the constraint graph on the tractability of local search. First, we show that for fitness landscapes representable by binary Boolean valued constraints there is a minimal necessary constraint graph that can be easily computed. Second, we consider landscapes as equivalent if they allow the same (improving) local search moves; we show that a minimal normal form still exists, but is NP-hard to compute. Next we consider the complexity of local search on fitness landscapes modelled by valued constraints with restricted forms of constraint graph. In the binary Boolean case, we prove that a tree-structured constraint graph gives a tight quadratic bound on the number of improving moves made by any local search; hence, any landscape that can be represented by such a model will be tractable for local search. We build two families of examples to show that both the conditions in our tractability result are essential. With domain size three, even just a path of binary constraints can model a landscape with an exponentially long sequence of improving moves. With a treewidth two constraint graph, even with a maximum degree of three, binary Boolean constraints can model a landscape with an exponentially long sequence of improving moves.
A Semi-supervised Classification Using Gated Linear Model

Semi-supervised learning aims to construct a classifier by making use of both labeled data and unlabeled data. This paper proposes a semi-supervised classification method using a gated linear model, based on the idea of effectively utilizing manifold information. A gating mechanism is firstly trained in a semi-supervised manner to capture manifold information which guides the generation of gate signals. Then the gated linear model is formulated into a linear regression form with the gate signals included. Secondly, a Laplacian regularized least squares (LapRLS) formulation is applied to optimize the linear regression form of the gated linear model. In this way, the gate signals are integrated into the kernel function, which is defined as inner product of the regression vectors. Moreover, this kernel function is used as a better similarity function for graph construction. As a result, the manifold information is ingeniously incorporated into both kernel and graph Laplacian in the LapRLS. Experimental results exhibit the effectiveness of our proposed method.
Android-based Image and Video Steganography System

Steganography is a form of security measure wherein confidential information is hidden within a cover media.This study aims to contribute to the security of digital information, particularly of audio data using image and video steganography.A total of six technique combinations were derived from three-pixel location strategies and spatial domain embedding in order to successfully mask and impose audio data into cover images and videos.The final prototype comes in the form of an integrated system that operates on three environments.The first platform is an android application, which serves as the input/output gateway, followed by a Matlab program which serves as the main processor, and a server that allows two-way exchange of information at both ends.The goal of the prototype is to successfully hide the audio data into the cover media with minimal to negligible visual and audible changes between the original files and output files.To evaluate the system's performance, both qualitative and quantitative bases are used.Quantitative assessment includes the MSE and PSNR of the steganography output, the BER and accuracy of the recovered audio data.Meanwhile, qualitative assessment is conducted in the form of a survey.Results from quantitative and qualitative assessment strongly verify that the proposed integrated system is verified and hereby recognized as consistent, reliable and accurate.
Sound Propagation and Reconstruction Algorithm Based on Geometry

This paper presents a method of simulating sound propagation and reconstruction for the virtual reality applications. The algorithm being developed in this paper is based on a ray sound theory. If we are given 3 dimensional geometry input as well as sound sources as inputs, we can compute sound effects over the entire boundary surfaces. In this paper, we present two approaches to compute sound field: The first approach, called forward tracing, traces sounds emanating from sound sources, while the second approach, called geometry based computation, computes possible propagation routes between sources and receivers. We compare two approaches and propose a geometry-based sound computation method for outdoor simulation. This approach is computationally more efficient than the forward sound tracing. The physical environment affects sound propagation simulation by impulse- response. When a sound source waveform and numerically computed impulse in time is convoluted, a synthetic sound is generated. This technique can be easily generalized to synthesize realistic stereo sounds for the virtual reality applications. At the same time, the simulation result can be visualized using VRML.
Self-sovereign Management of Privacy Consensus using Blockchain

In this paper, we propose a solution implementing a self-sovereign approach to manage privacy consensus in a open domain. The idea is allowing the user to set her policies in a unique way, in such a way that she keeps the full control on her personal data. The goal is achieved by combining blockchain with Attribute-Based Encryption and Proxy Re-encryption. Blockchain is also used to implement the notarization of the critical actions to obtain accountability and non-repudiation.
A familiar voice in the lab

When voice-activated assistants first appeared on the market, they were perceived as a high-tech frill. Science fiction enthusiasts, reminded of the HAL 9000 computer in the movie 2001: A Space Odyssey, amused their friends by stumping Amazon’s Alexa with commands to open the pod bay doors. Meanwhile, Apple had to prime its Siri iPhone voice assistant with searing comebacks to the question: What are you wearing? But pretty soon, consumers got serious about voice-activated devices, routinely asking the ever-ready, ever-listening vocal presence in their living space for a check on the weather or to cue up the latest from Taylor Swift. Voice activation is now becoming an even more serious technology, completing its journey from science fiction to fact-based science tool with the emergence of voice-activated laboratory assistants. The trick will be upgrading the natural language processing (NLP) programs underpinning home voice systems to recognize chemical names, technical jargon, full
Space Independent Image Registration Using Curve-Based Method with Combination of Multiple Deformable Vector Fields

This paper proposes a novel curve-based or edge-based image registration technique that utilizes the curve transformation function and Gaussian function. It enables deformable image registration between images in different spaces, e.g., different color spaces or different medical image modalities. In particular, piecewise polynomial fitting is used to fit a curve and convert it to the global cubic B-spline control points. The transformation between the curves in the reference and source images are performed by using these control points. The image area is segmented with respect to the reference curve for the moving pixels. The Gaussian function, which is symmetric about the coordinates of the points of the reference curve, was used to improve the continuity in the intra- and inter-segmented areas. The overall result on curve transformation by means of the Hausdroff distance was 5.820 ± 1.127 pixels on average on several 512 × 512 synthetic images. The proposed method was compared with an ImageJ plugin, namely bUnwarpJ, and a software suite for deformable image registration and adaptive radiotherapy research, namely DIRART, to evaluate the image registration performance. The experimental result shows that the proposed method yielded better image registration performance than its counterparts. On average, the proposed method could reduce the root mean square error from 2970.66 before registration to 1677.94 after registration and can increase the normalized cross-correlation coefficient from 91.87% before registration to 97.40% after registration.
Fuzzy Logic Control System with Gaussian Membership Functions

One of the most widely known advanced control techniques is Fuzzy Logic Control.This paper aims to define the concept and function of Fuzzy Logic Control.Furthermore, this paper consists of brief discussion on how this type of control works, and how it is applied to several types of control systems.The procedure followed by this approach is explained and presented in this paper as well.This includes a discussion on the three steps namely fuzzification, Fuzzy Logic has become a popular approach in researches in the fields of science, technology, engineering, and medicine.This paper also shows the versatility of this approach in terms of numerous functions and applications.
Multi-criteria Modelling Approach for Ambient Assisted Coaching of Senior Adults

This paper presents and critically discusses an approach for knowledge modelling and reasoning in a system for monitoring and coaching of senior adults. We present a modular architecture of the system and a detailed description of the modelling methodology which originates from the field of multi-criteria decision modelling and differs from the commonly used ones in this problem domain. The methodology has several characteristics that make it fit well to the purpose in this application and initial insights from potential users are positive. A discussion of the suitability of the proposed methodology for knowledge representation and reasoning in the given problem domain is provided, with an outline of its potential benefits and drawbacks and a comparison with the ontological approach.
Implementation of optical feedback modulation in photonic reservoir computing

We experimentally investigate photonic reservoir computing using a single semiconductor laser with time-delayed feedback modulation. We perform the time-series prediction task and achieve better results using phase modulation than those using intensity modulation.
Systemic cohesion in social media conversations: Cases on Facebook and Twitter

As a new way of communication, social media conversations on the Internet do have some characteristics that are different from common face-to-face conversations. One of the differences lies in the existence of systemic cohesion in addition to the established conventional cohesion. Systemic cohesion is a form of structural and textual unity which is generated by the system of a social media platform and is not available in offline discourse. This article is aimed at describing the phenomena of systemic cohesion of social media conversations, particularly on Facebook and Twitter, by analyzing them based on the classification of cohesive devices made by Halliday and Hasan (1976, 1985). In general, systemic cohesion can be distinguished into structural and textual cohesion. The former is represented by the functions of conversation components, indentation, and vertical line whereas the latter is implemented in the form of mention and hashtag. Facebook and Twitter share both similarities and differences in either case.
Conceptual Analysis of Different Clustering Techniques for Static Security Investigation

Power system contingency studies play a pivotal role in maintaining the security and integrity of modern power system operation.However, the number of possible contingencies is enormous and mostly vague.Therefore, in this paper, two well-known clustering techniques namely K-Means (KM) and Fuzzy C-Means (FCM) are used for contingency screening and ranking.The performance of both algorithms is comparatively investigated using IEEE 118-bus test system.Considering various loading conditions and multiple outages, the IEEE 118-bus contingencies have been generated using fast-decoupled power flow (FDPF).Silhouette analysis and fuzzy partition coefficient techniques have been profitably exploited to offer an insight view of the number of centroids.Moreover, the principal component analysis (PCA) has been used to extract the dominant features and ensure the consistency of passed data with artificial intelligence algorithms' requirements.Although analysis of comparison results showed excellent compatibility between the two clustering algorithms, the FCM model was found more suitable for power system static security investigation.
CONSTRUCTIVE REFLECTIVITY PRINCIPLES FOR REGULAR THEORIES

Abstract Classically, any structure for a signature ${\rm{\Sigma }}$ may be completed to a model of a desired regular theory ${T}}$ by means of the chase construction or small object argument . Moreover, this exhibits ${\rm{Mod}}\left(T)$ as weakly reflective in ${\rm{Str}}\left( {\rm{\Sigma }} \right)$ . We investigate this in the constructive setting. The basic construction is unproblematic; however, it is no longer a weak reflection. Indeed, we show that various reflectivity principles for models of regular theories are equivalent to choice principles in the ambient set theory. However, the embedding of a structure into its chase-completion still satisfies a conservativity property, which suffices for applications such as the completeness of regular logic with respect to Tarski (i.e., set) models. Unlike most constructive developments of predicate logic, we do not assume that equality between symbols in the signature is decidable. While in this setting, we also give a version of one classical lemma which is trivial over discrete signatures but more interesting here: the abstraction of constants in a proof to variables.
Distortion-aware Virtual Environments Transmission Scheme over a Bandwidth-limited Network

Virtual environments (VEs) have been widely used in multimedia applications, with trends toward larger data size. 3D streaming has recently been proposed to enable users to view the VEs in real time. However, how to efficiently download the VEs over a bandwidth-limited network becomes a bottleneck. With the aim of minimizing the scene distortion and achieving a more efficient use of bandwidth, it’s necessary to download the visible 3D contents at an appropriate resolution. In this paper, we propose a distortion-aware VEs transmission scheme. The main contributions of the proposed scheme include: (1) Improving the traditional interest management algorithm, so that our method can fit the user’s visual and behavioral characteristics better. (2) Proposing a scene distortion estimation algorithm, by which we can effectively calculate and evaluate the scene distortion. (3) Based on (1) and (2), we propose a scene update strategy, which combines the user’s visual characteristics, scene distortion and bandwidth estimation. The experimental results show that the proposed scheme can lower distortion especially when network condition is poor.
Real Avatar Production - Raspberry Pi Zero W Based Low-Cost Full Body 3D Scan System Kit for VRM Format

We would like to introduce Raspberry Pi Zero W based 360-degree full body shooting / 3D scanning system kit in order to create "Real Avatar"."Real Avatar" is a word for photo-real 3D Humanoid Avatar.System configuration, flow, operation and resulting 3D scanned model are shown in this paper.In order to create mesh and texture, we use Photogrammetry software, RealityCapture, on Microsoft Azure virtual machine being configured with NVIDIA GPU.We also briefly introduce VRM format which is 3D Humanoid Avatar format that has the potential to be widely used for various VR/AR apps and platforms.
Pelatihan Media Pembelajaran dengan Ms. Office Power Point bagi Guru SMA IT Plus BAZMA Brilliant Dumai

Teachers are currently required to use learning media, in accordance with government regulations. Learning media are used for teaching materials for student learning. Learning evaluation can consist of questions or quizzes using multiple choice quiz. Evaluation of student learning by using learning media is one of the things which teachers of IT PLUS BAZMA Briliant High School. Therefore, STT Dumai held community service for IT PLUS BAZMA Brilliant High School Teachers, namely, Training to Make Multiple Choice Test Using Ms. Office Power Point for IT Plus Bazma Brilliant High School Teachers on Wednesday, January 30, 2018. Training provided for three materials, namely techniques and things to consider in making Power Point, the use of features in Power Point, and make a quiz with Power Point. The training was attended by 19 teachers and held for approximately 2 hours. The training begins with the implementing material ending with practice. The material given by sequence is in accordance with the desired goals, namely making learning material and also student learning.
Guided just-in-time specialization

JavaScript's portability across a vast ecosystem of browsers makes it today a core building block of the web. Yet, building efficient systems in JavaScript is still challenging. Because this language is so dynamic, JavaScript programs provide little information that just-in-time compilers can use to carry out safe optimizations. Motivated by this observation, we propose to guide the JIT compiler in the task of code specialization. To this end, we have augmented the language with an annotation that indicates which function call sites are likely to benefit from specialization. To support the automatic annotation of programs, we have introduced a novel static analysis that identifies profitable specialization points. We have implemented our ideas in JavaScriptCore, the built-in JavaScript engine for WebKit. The addition of guided specialization to this engine required us to change it in several non-trivial ways, which we describe in this paper. Such changes let us observe speedups of up to 1.7x on programs present in synthetic benchmarks.
Tendency of ICT Usage among Adolescent in Oredo Local Govenrment Primary Schools, Benin City, Edo State-Nigeria

The viability of a society depends largely on the learning outcome of its teenagers. Raising them can be challenging because modern society is embolden with information communication technology (ICT) that do not only isolate them from peers but create mental disorder in them. ICT is not an isolated entity rather an embodiment of deferent technologies that act as an entity to delivering and channeling information. To ascertain it tendency in primary school and its impact on adolescent, this paper reviewed the concept of ICT and carried out a survey on its usage among adolescent. The survey questionnaire was structured on five points scale and the feedbacks from hundred respondents were analyzed with Statistical package for social sciences (SPSS). From the findings, it was showed that the tendency of ICT by both private and government primary school is indeed poor and its impact on adolescent is on the downward trend. The study offered some recommendations including the need for government to carry out a holistic review of the primary schools curriculum so as to accommodate ICT usage.
Distance learning and external studies in the system of continuous learning

The article deals with extra-institutional forms of getting education: self-education with subsequent external studies in getting general education and distance learning in getting higher education. The objective of the article is to substantiate distance learning as a form of self-education, as a technology which makes education more accessible for different layers of society irrespective of their place of residence and the chosen study program. Different forms of study are compared according to the criteria of their efficiency or quality, accessibility or transparency and affordability.
Arabic Twitter User Profiling: Application to Cyber-security

In recent years, we witnessed a rapid growth of social media networking and micro-blogging sites such as Twitter. In these sites, users provide a variety of data such as their personal data, interests, and opinions. However, this data shared is not always true. Often, social media users hide behind a fake profile and may use it to spread rumors or threaten others. To address that, different methods and techniques were proposed for user profiling. In this article, we use machine learning for user profiling in order to predict the age and gender of a user’s profile and we assess whether it is a dangerous profile using the users’ tweets and features. Our approach uses several stylistic features such as characters based, words based and syntax based. Moreover, the topics of interest of a user are included in the profiling task. We obtained the best accuracy levels with SVM and these were respectively 73.49% for age, 83.7% for gender, and 88.7% for the dangerous profile detection.
Modified Seam Carving by Changing Resizing Depending on the Object Size in Time and Space Domains

Modified seam carving by switching from the conventional method to resizing method depending on the object size is proposed.When the object size is dominant in the scene of interest, the conventional seam carving shows deformation of components in the object.To avoid the situation, resizing method is applied rather than the conventional seam carving in the proposed method.Also, the method for video data compression based on the seam carving not only in image space domain but also in time domain is proposed.It is specific feature that original quality of video picture can be displayed when it is replayed.Using frame to frame similarity defined with histograms distance between the neighboring frames, frames which have great similarity can be carved results in data is compressed in time domain.Moreover, such carved frame can be recorded in the frame header so that the carved frame can be recovered in reproducing the compressed video.Thus, video quality can be maintained, no degradation of video quality at all.Compression ratio is assessed with the several video data.It is obvious that data compression ratio of the proposed space and time domain seam carving is greater than that of the conventional space domain seam carving.
Genetic Algorithm with Success History based Parameter Adaptation

Genetic algorithm is a popular optimization method for solving binary optimization problems. However, its efficiency highly depends on the parameters of the algorithm. In this study the success history adaptation (SHA) mechanism is applied to genetic algorithm to improve its performance. The SHA method was originally proposed for another class of evolutionary algorithms, namely differential evolution (DE). The application of DE’s adaptation mechanisms for genetic algorithm allowed significant improvement of GA performance when solving different types of problems including binary optimization problems and continuous optimization problems. For comparison, in this study, a self-configured genetic algorithm is implemented, in which the adaptive mechanisms for probabilities of choosing one of three selection, three crossover and three mutation types are implemented. The comparison was performed on the set of functions, presented at the Congress on Evolutionary Computation for numerical optimization in 2017. The results demonstrate that the developed SHAGA algorithm outperforms the self-configuring GA on binary problems and the continuous version of SHAGA is competetive against other methods, which proves the importance of the presented modification.