Reviewerly/exHarmony huggingface dataset:
Face Photograph Recognition via Generation from Sketches using Convolutional Neural Networks

Face photo-sketch matching is an important problem for law enforcement agencies in terms of identifying suspects.In this study, a new sketch-photo generation and recognition technique is proposed by using residual convolutional neural network architecture.The suggested RCNN architecture consists of 6 convolutions, 6 ReLU, 4 poolings, 2 deconvolution layers.The proposed architecture is trained with face photos and sketches.Sketches are supplied as an input to the RCNN architecture and, generated face photos are obtained as the output.Then, the generated face photos are compared with the photos of the people in the database.Structural Similarity Index (SSIM) is used to measure the pairwise similarity and the photo with the highest index score is matched.CUHK Face Sketch Database containing 188 images is tested.In the experiments, 148, 20, and 20 images are used for training, validation, and testing, respectively.Data augmentation applied to 148 training images produced 444 images.Experimental results show that the success of the training curve is 90.55% and the validation success is 91.1%.True face recognition success from generated face images with SSIM is 93.89% for CUHK Face Sketch database (CUFS) and 84.55% AR database.
Towards Security Effectiveness Evaluation for Cloud Services Selection following a Risk-Driven Approach

Cloud computing is gaining a lot of popularity with an increasing number of services available in the market.This has rendered services selection and evaluation a difficult and challenging task, particularly for security-based evaluation.A key problem with much of the literature on cloud services security evaluation is that it fails to consider the overall evaluation context given the cloud characteristics and the underlying influence factors including threats, vulnerabilities, and security controls.In this paper, we propose a holistic riskdriven security evaluation approach for cloud services selection.We first use fuzzy DEMATEL method to jointly assess the likelihood and impact of threats with respect to the cloud service types, the exploitability of vulnerabilities to the identified threats, and the effectiveness of security controls in mitigating those vulnerabilities.Consequently, the overall diffusion of risk is captured via the relations across these concepts, which is leveraged to filter and prioritize the most critical security controls.The selected controls were then weighted using a combination of fuzzy DEMATEL and fuzzy ANP methods based on several factors, including their effectiveness in preventing the identified risks, user's preferences and level of control (i.e., responsibilities).The latter denotes how much control a cloud user is transferring to the cloud provider.To enhance the reliability of the results, the subjective weights were integrated with objective weights using the Entropy method.Finally, the TOPSIS method was employed for services ranking and the Improvement Gap Analysis (IGA) method was leveraged to provide more insights on the strength and weaknesses of the selected services.An illustrative example is given to demonstrate the application of the proposed framework.
Design and Implementation of a Digital Dual Orthogonal Outputs Chaotic Oscillator

Discrete time dynamical chaotic systems obey a set of recurrence equations involving one or more variables. Many chaotic maps have been proposed. None that simultaneously provides two sine–cosine outputs has stationary mean and standard deviation, or is quite robust with respect to the data format used in the hardware implementation. Here, we propose a chaotic oscillator based on a complex phasor whose angular argument evolves according to a geometric progression that is independent of the instantaneous amplitude. In order to maintain the oscillations, the phasor magnitude is normalized at each iteration using an approximation factor. The statistical characteristics of this oscillator are stationary in the short term, and do not depend on the initial conditions. The mean and standard deviation of the two orthogonal sequences quickly approach 0 and 1 / 2 , respectively. The resulting distribution is similar to that of a digital sine with a constant angular step. We also present an FPGA architecture and its implementation results. This oscillator can be used in modulation schemes, such as the chaotic shift keying one or for data and image encryption. Finally, we show an original application that exploits the orthogonality of the two chaotic signals for the simultaneous encryption of two digital images.
Block-based Approach to Observe Game Content Space in Endless-runner Game

Game genres are rapidly growing with the technological advances, one of them is the endless runner that becomes favourable in recent years. One example is Flappy Bird which is a fun and popular game. Unfortunately, randomly generating obstacles for Flappy Bird game often frustrates the players due to there were no specific rules to differentiate the difficulty of an obstacle to another. For example, by chance, player A can complete 10 easy obstacles, while player B gets 10 obstacles with a high degree of difficulty. This causes unfair experiences/achievements shared on social media. Meanwhile, a good game should provide distinct difficulty playable from its elements. These problems pose a challenge to make the Flappy bird game have acceptable difficulty levels relevant to its obstacles. In this research, procedural content generation (PCG) technique is proposed to categorize the difficulty of obstacles in Flappy Bird. It combines search-based and learning-based PCG techniques. Search-based PCG is used to define the game's representation relative to a block of obstacles. Then, a bot observes and evaluates them to label the obstacle blocks. Consequently, learning-based PCG acts as the classifier to the observed obstacle blocks with more than 70% accuracy of the selected classification algorithm.
Intelligent Web Applications as Future Generation of Web Applications

During the recent years World Wide Web very fast increased a fundamental part in our everyday life. In commerce, personal relationship, the effect of the universal network has wholly changed the way people interact with each other and with machines. The problem is after rising the Artificial Intelligence to presenting human feelings, everything changed including web applications. In this paper, we describe the intelligent web applications as present and future of web applications, moreover we highlight the special features and their roles in increasing intelligence of web applications as well as impact this application in the process development web systems. The goals of this paper led to developers to create smart and modern web applications.
A Listening Lesson Prototype for the First-Grade in Primary School

One of the main purposes of learning Bahasa Indonesia is to make students be fluent in using language. Language skills consist of two receptive skills (listening and reading), and two productive skills (speaking and writing). Those four skills are expected to be practiced equally. However, based on the previous research, listening lessons were rarely implemented in class. Moreover, listening lesson were inappropriately implemented by asking students to read. Additionally, the listening tests to measure the students’ listening proficiency were also unsuitable. Based on those findings, the researchers conducted a listening lesson developmental research for the first-grade primary school. This research is part of a developmental research referring to Gall, Gall, and Borg’s developmental research steps. This research is the second of five planned research phases. In this second phase, the researchers developed a listening lesson prototype validated by six validators. To validate the data, this research employed the triangulation method. Meanwhile, Miles and Huberman’s data analysis technique was utilized to analyze the data. The result of this research was a listening lesson prototype, including the mapping of basic competencies, networking of themes, determining of listening learning success indicators, learning stages, and listening evaluation.
KUALITAS LAYANAN KETERBUKAAN INFORMASI PUBLIK BERBASIS WEBPORTAL PADA PEJABAT PENGELOLA INFORMASI DAN DOKUMENTASI (PPID) KABUPATEN SLEMAN TAHUN 2019

At present the development of technology and information has reached a very rapid level. Technology and information are used as a service media in the government environment which is also known as e-Government, one of which is the service of public information disclosure. The central government through Law No. 14 of 2008 concerning Openness of Public Information, encourages all Public Agencies including the Sleman Regency Government to make transparency in the administration of the state by utilizing information technology. This research is a qualitative descriptive study which aims to describe the reality that occurs. The object of research in this study is the official website of the Information and Documentation Management Officer (PPID) of Sleman Regency with the domain https://ppid.slemankab.go.id then the Sleman Regency Communication and Informatics Office as the organizer of the public information disclosure program. The data collection technique itself is carried out by means of interviews, documentation studies, and field observations (observations). After collecting and presenting data, then the data will be reduced first then analyzed and concluded. From the results of the study, in general the researchers concluded that the Sleman Regency PPID website had reached the level of qualification to become a quality website, however there were still some improvements and evaluations that had to be done by the relevant agencies in order to be better, namely (i) the website was still being assessed as a one-way service (ii) There are still many OPDs that are not ready to implement PPID (iii) data and information are still not updated (iv) lack of responsiveness of services in requests for information.
Basic principles of blind write protocol

The current approach to handle interleaved write operation and preserve consistency in relational database system still relies on the locking protocol. If any entity is locked by any transaction, then it becomes temporary unavailable to other transaction until the lock is released. The temporary unavailability can be more often if the number of write operation increases as happens in the application systems that utilize IoT technology or smartphone devices to collect the data. To solve this problem, this research is proposed blind write protocol which does not lock the entity while the transaction is performing a write operation. This paper presents the basic principles of blind write protocol implementation in a relational database system
Making Future-Ready Students with Design and the Internet of Things

INTRODUCTION:IoT will transform our future in unimaginable ways.The necessity for young people to understand and design with IoT seems unequivocal but there is currently limited integration in K-12 education.OBJECTIVES: To investigate these gaps in research and practice, this study aimed to explore the design processes and understandings of IoT that emerge when youth design an IoT passion project within a constructionist context.METHODS: A mixed methods multiple case study design was employed, analyzing questionnaires, interviews, recordings, and participant artifacts.RESULTS: Factors contributing to a successful design included guided inquiry, detailed plans, access to support, and perseverance.Participants also experienced gains in IoT skills and knowledge.CONCLUSION: Design and making with IoT through passion-based, guided inquiry appeared to facilitate the development of valuable knowledge and skills.Further research is needed to explore implementations in formal education.
The dual-design-based pneumatic simulator as supporting media for electro-pneumatic practicum in vocational higher education

This study aims to: (1) determine the process of developing a learning media simulator for electro-pneumatic systems based on dual design, (2) knowing the effectiveness of learning media in the form of electro-pneumatic system simulators based on dual design. This research is a research and development adapted from the 4D development model, namely Define, Design, Develop and Disseminate. The subjects of this study were students of Mechanical Engineering Education in Semester IV and V with 30 students taking pneumatic hydraulic courses. Data collection techniques in this study used questionnaires and interviews with research instruments in the form of interview guidelines and questionnaires. The data obtained were analyzed with descriptive quantitative. The results showed (1) The results of the development of learning media for electro-pneumatic system simulators based on Dual Design as supporting media for electro-pneumatic practices produced 3 main components, namely the working system in the pneumatic electro system, wiring diagrams and electrical circuits, (2) the feasibility results of expert validation media is 84% (Very Good), expert material validation is 92% (Very Good), and user validation is 86% (Very Good). So, the learning media for electro-pneumatic system simulator is feasible as a learning media in pneumatic hydraulic courses.
Fluid Dynamics: On the Representation of Water and Discourses of the Digital

Water bottles, ripples, waves, storms, floods, pipes and oceans. In the last decade, water has featured as a major thematic or visual trope in artworks made with, for or about the Internet. From Helen Marten's Evian Disease (2012) to Hito Steyerl's Liquidity Inc . (2014), this essay considers why the image of water has provided such a powerful and provocative visual metaphor for new digital technologies. I analyse how the image of water has been used to map out a series of key relationships between information technology, finance and the environment. Drawing these fields together through the themes of transparency and opacity, order and chaos, I argue that the image of water serves as a shorthand for making art in a time of crisis: a representation of a meltdown that is at once both metaphoric and all too real. At stake in this is the idea that the repeated and recurrent use of images of water in recent art reveals not simply how but crucially why a new set of narratives about digital technology has emerged since 2008: narratives in which a historical language of immaterial flows has now come to be superseded by one of material realities.
Closed-form solution for thin lens image irradiance under arbitrary solid angle

Optical imaging systems are found everywhere in modern society. They are integral to computer vision, where the goal is often to infer geometric and radiometric information about a 3D environment given limited sensing resources. It is helpful to develop relationships between these real-world properties and the actual measurements that are taken, such as 2D images. To this end, we propose a new relationship between object radiance and image irradiance based on power conservation and a thin lens imaging model. The relationship has a closed-form solution for in-focus points and can be solved via numerical integration for points that are not focused. It can be thought of as a generalization of Horn’s commonly accepted irradiance equation. Through both ray tracing simulations and comparison to the intensity values of actual images, we believe our equation provides better accuracy than Horn’s equation. An improvement is most notable for large lenses and near-focused images where the pinhole imaging model implicit in Horn’s derivation breaks down. Outside of this regime, our model validates the use of Horn’s approximation through a more thorough theoretical foundation.
Latency-Constrained Cost-Minimized Request Allocation for Geo-Distributed Cloud Services

Latency to end-users and regulatory requirements push cloud providers to operate many datacenters all around the globe to host their cloud services. An emerging problem under such geo-distributed architecture is to assign each user request to an appropriate datacenter to benefit both cloud providers (e.g., low bandwidth cost) and end-users (e.g., low latency)-known as request allocation. However, prior request allocation solutions have significant limitations: they either focus only on optimizing the benefits for one entity (e.g., providers or users), or ignore some practical yet indispensable factors (e.g., heterogeneous latency requirements of different users and diverse per unit bandwidth cost among different datacenters) when optimizing benefits for both entities. In this paper, we study the problem of minimizing the total bandwidth cost for cloud service providers while guaranteeing the latency requirement for end-users. Specifically, we formulate an integer programming with consideration of the diversities in both the delay of requests and per unit bandwidth cost of datacenters. To efficiently and practically solve this problem, we first relax the integer programming into a continuous convex optimization and then take the advantages of random sampling to enforce the solution to be a feasible one for the original integer programming. We have conducted rigorous theoretical analysis to prove that our algorithm can provide a considerable good competitive ratio. Extensive simulations demonstrate that our proposed algorithm can reduce the total bandwidth cost by 30% while guaranteeing the latency requirements of all requests, as compared to conventional methods.
A Configurable Architecture of ANN in Hardware with Resource-Efficient Reusable Neuron

Artificial Neural Network (ANN) is one of the most important structure of machine learning and it has been widely used in various areas such as medical diagnosis, image classification and signal processing. The large area and resource cost make it difficult for the realization of ANN in hardware. This paper presents a flexible architecture of ANN with resource-efficient reusable neuron. The dynamical activation method of neurons is proposed and utilized to make the ANN more flexible and configurable. The designed structure of neuron supports multiple calculation modes which is reused in both feedforward and back-propagation. The approach of multiplexing layer is adopted to reduce the number of physical layers to 1. The simulation results show the proposed method can achieve the function of ANN while significantly reducing the resource cost and area.
In for a Penny, in for a Pound? A Lifecycle Model for Agile Teams

Agile methods are increasingly popular -in information systems development and in general.The process of transformation, however, is not easily done, and the inherent barriers for successful transformation are high.To successfully transform a team or a whole organization to work in an agile manner, the threats, barriers, and the overall process have to be known.In this paper, we derive a lifecycle model of agile teams as well as threats to their success, based on interviews from six cases across a variety of industries and organizational contexts.This model further includes pathways for teams to discard agile methods if these do not fit the team's needs.Based on this model, organizations can refine their agile transformation strategies and can keep on improving success rates of agile transformation processes.
Strategic Framework for Service Delivery Improvement in School Libraries

One of the fundamentals to building a knowledge-based economy is through the provision of quality information via school libraries. Schools play a fundamental role in raising an educated and informed nation. Therefore, the school library is fundamental to the teaching and learning activities of the school. The school library should be able to provide resources that are relevant to the school curriculum and also be able to provide quality information services to both students and teachers. That being said, this study introduces a school library assessment model that can be used by school management and librarians to evaluate the effectiveness of their school library resources and services. The proposed model integrates the IFLA school library guidelines and the LibQUAL model. The study is based on literature review to explicitly present the proposed model. The proposed school library assessment model is expected to help school librarians to implement the right programs and acquire the right resources for the school library, to be able to meet the users` information needs and satisfy them, thereby making the library relevant to the 21st century information era. This will further ensure that the school library is rightly positioned to support training and teaching activities effectively. As a result, quality education and lifelong learning skills will be realized.Keywords: School libraries, LibQUAL, quality, service, service delivery framework,
Exploring Convolutional Neural Networks and Recurrent Neural Networks for Arabic Question Classification

Questions classification which consists of assigning a category to each question is a crucial process in question answering systems. Deep neural networks have appeared to be effective in several text mining applications such as text categorization, information retrieval, etc. However, these models have not gained much attention in the field of Arabic question classification. In this paper, we propose an efficient Arabic question classification method based on continuous distributed word representation and deep neural networks. First, we opt for continuous distributed representation to capture syntactic and semantic relations between words. Then, we apply Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to classify Arabic questions into seven categories (or classes) according to Li and Roth [3] taxonomy. We investigate several variations of CNN and RNN where the output layer depends on two activation functions, the softmax and the sigmoid functions. We carry out several experiments and compare different architectures of CNN and RNN trained on our dataset containing 3173 Arabic labeled questions. The obtained results demonstrate that both deep neural network models are promising as they achieve up to 92% in terms of micro average F1 measure.
SISTEM REKOMENDASI PERTANIAN PADA ARSITEKTUR AGRIBUSINESS E-MARKETPLACE

Currently the development of information technology has driven the development of e-commerce which is quite promising in Indonesia. This development has brought an era of new digital-based creative developments. Agriculture as one of the economic and community welfare bases in Indonesia needs to be developed and supported with digital finance. Several agricultural markets have been established in Indonesia to help farmers to participate in digital economic activities. Some e-commerce systems that have been built in Indonesia only help the downstream process or the marketing process. While farmers need information that can help them for agricultural purposes. Machine learning technology uses data collected in the agricultural marketplace system to be used in building a social assessment system. Recommendations for agricultural activities are adjusted to the cost of agriculture, location of agriculture, pricing of agricultural commodities at the time of receipt and timing of agricultural activities. In this research an analysis and design of an agricultural e-commerce system will be provided to provide farmers to sell their agricultural products at competitive prices and help farmers to obtain information that can be used to plan further agricultural activities.