Miracle-dz/UniFAR-FTUs huggingface dataset:
An Ethics Framework for Research into Heterogeneous Systems

Heterogeneous systems often found in the Internet of Things (IoT) have a wide range of challenges in ethics and law. Any device with an IP address can potentially collect, process, store and share data and make automated decisions in unpredictable ways. When conducting research and development in IoT, it is necessary to have a comprehensive socio-technical understanding of decision-making and data-handling, as well as procedures in place to pre-empt and address unforeseen consequences. In this paper we propose a comprehensive conceptual-modelling approach to help researchers systematically identify, consider and respond to challenges in ethics and law when conducting research and development of heterogeneous systems. Our framework is a six-layered model that addresses these concerns with regards to proximity to the data and actions in question. Using our framework, researchers should be able to deliver use-case scenarios that should be peer-reviewed by a large number of experts in dissimilar domains with the aim of identifying issues to why the research and development proposed is not done responsibly, so researchers can address these concerns. Finally, we explore a IoT use-case scenario, and we propose future directions for this work.
Learning a Static Analyzer: A Case Study on a Toy Language

Static analyzers are meta-programs that analyze programs to detect potential errors or collect information. For example, they are used as security tools to detect potential buffer overflows. Also, they are used by compilers to verify that a program is well-formed and collect information to generate better code. In this paper, we address the following question: can a static analyzer be learned from data? More specifically, can we use deep learning to learn a static analyzer without the need for complicated feature engineering? We show that long short-term memory networks are able to learn a basic static analyzer for a simple toy language. However, pre-existing approaches based on feature engineering, hidden Markov models, or basic recurrent neural networks fail on such a simple problem. Finally, we show how to make such a tool usable by employing a language model to help the programmer detect where the reported errors are located.
Security Framework for Sharing Data in Fog Computing

: Cloud computing is an attractive criterion for accessing virtually unlimited storage and computational resources. Cloud computing has many advantage, but providing the data confidentiality in the cloud is major concern. The major disadvantages in the cloud computing is high latency, limited mobility, slow response time because data is transferred through Multiple hops. And it is centralized Geo-distribution. In Our System, we propose the Fog computing which address the above problems faced by cloud computing. Fog computing is a criterion which extends the cloud computing and its services to the network edge. It can’t replace cloud. It extends the cloud computing by providing the security in the cloud atmosphere. Fog has many advantages when compared to the cloud i.e., less data traffic, low cost and latency. It also eliminates the overhead to the centralized computing system, and security is high because data moves across the edge of the network so response is quick. Still there are many advantageous in fog computing, but some of the security issues also taken into consideration while transferring the data. In our system we focus on providing the security to the data while transferred via cloud. Here Outsourcer sends the encrypted data along generated key (cipher key/encrypted key) to the data user via Fog Server. Using that encryption key the user decryption is performed and then viewed the original data. This Cipher key is generated by the Modified ELGAMAL algorithm which provides the better security than the existing algorithm.
Do You Like Sclera? Sclera-region Detection and Colorization for Anime Character Line Drawings

Line drawing colorization is an important process in creating artwork such as animation, illustrations and color manga. Many artists color work manually, a process that requires considerable time and effort. In addition, colorizing requires special skills, experience, and knowledge, and this makes such work difficult for beginners. As a result, automated line drawing colorizing methods have significant market demand. However, it is difficult to paint artistic works. Many automated colorizing methods have been developed, but several problems arise in art colorized using these methods. For example, colors may be different in a region that should be painted the same color as another region, or a mismatch may occur between the input line drawing and the colorizing result due to difficulty in understanding the sketches, the inclusion of undesirable artifacts, and other issues. Anime character’s eyes are drawn in various styles, depending on the artists’ preferences. In some styles, eyes are overly abstract. In addition, in grayscale line drawings, the skin and sclera are both expressed in white in many cases. Therefore, the boundaries cannot always be determined using existing automated colorizing techniques. As a result, sclera are often painted the same color as the skin, and there is a mismatch between these regions in the line drawing and the colorizing results. Facial features are important in artworks that depict people, and excessive ambiguity at the boundary between the eyes and the skin may impair quality. Therefore, it is expected that sclera-region detection should improve the accuracy of automated colorizing of grayscale line drawings of people. This paper focuses on inconsistencies in the sclera region between line drawings and colorizing results; we aim to match the structure of line drawings and colorizing results by detecting the sclera regions in grayscale line drawings of people to improve the accuracy of automated colorizing (Figure 1). In our proposed framework, we perform machine learning using a pair of line drawings and a mask image. The sclera regions are labeled to create semantic segmentation models of the sclera regions. Then, to colorize the line drawing, the semantic segmentation models detect the sclera regions, and we apply these regions to the automated colorizing result. As a result, our framework maintains the correct sclera-region color. When using the semantic segmentation model, it is possible to detect sclera regions without requiring the user to add hints. In this paper, we propose two mask image creation methods: the manual type and the graph cut type. Compared with the manual type, the graph cut type can reduce the mask image creator’s burden.
Real-time fast moving object tracking in severely degraded videos captured by unmanned aerial vehicle

Object tracking for unmanned aerial vehicle applications in outdoor scenes is a very complex problem. In videos captured by unmanned aerial vehicle, due to frequent variation in illumination, motion blur, image noise, deformation, lack of image texture, occlusion, fast motion, and other degradations, most tracking methods will lead to failure. The article focuses on the object tracking in severely degraded videos. To deal with those various degradations, a real-time object tracking method for high dynamic background is developed. By integrating histogram of oriented gradient, RGB histogram and motion histogram into a novel statistical model, our method can robustly track the target in unmanned aerial vehicle captured videos. Compared to those existing methods, our proposed approach costs less resource in the tracking, significantly increases the tracking speed, and runs faster than state-of-the-art methods. Also, our approach achieved satisfactory tracking results on the challenging visual tracking benchmark, object tracking benchmark 2013, the supplementary experiments demonstrates that our method is more effective and accurate than other methods.
Research on Modified SVM for Image classification in Remote Sensing

Image classification is based on the analysis in different time from the same area of two or more images, detect the feature in the region information changes over time. Remote sensing image classification has been widely used in such as the dynamic monitoring of forest resources monitoring, the change of land cover and use, agricultural resources survey, urban planning layout, environmental monitoring and analysis, assessment of natural disasters, geographic data update and military reconnaissance in the strategic objectives (such as roads, Bridges, airports) of dynamic monitoring and many other fields. SVM classifiers are most prominently used classifiers and they provide good accuracy. This research paper presents a modified SVM classifier by incorporating intelligence into the proposed system. Intelligence is provided by using an ANN architecture. The proposed SVM-ANN approach aims to reduce the impact of parameters in classification accuracy. In the training stage, the SVM is utilized to reduce the training samples for each of the available categories to their support vectors (SVs). The SVs from different categories are used as the training data of nearest neighbor classification algorithm in which the similarity measures or distance function is used to calculate the which class does the testing data belongs and which also reduce time consumption.
Survey on Tasks and Approaches of Sentiment Analysis

With the emergence of internet, people wholeheartedly involves insharing their experiences on the web ranging from the personal thoughts to the global issues. The world is now embellished by social media which paves way to share the user’s experience of anything across the world. This enables the market to analyze the sentimentor opinion by excerpting and examining the feedbacks of the users. Sentiment analysis involves in understanding the user’s opinions, believes, and feelings towards theindividuals, problems, business and other attributes. This intends to support for making the decision not only for other users but also to the firms. But the acquiescence here is, it is too hard to maintain the review sites and refining the data, as the propagation of sites is too high. This paper intends to present a literal survey on the sentiment analysis. It illustrates the ideas presented in the bunch of articles that are published in the last few years. It is concentrated to deliver the basic tasks, sub-tasks, techniques, methodologies and few applications of the review mining. Keywordssentiment survey, sentiment extraction, sentiment tasks, review evaluation
One Size Does Not Fit All: Understanding Differentiated Instruction in Elementary Mixed-Ability Classrooms

Differentiated instruction (DI) serves as an umbrella term for various approaches that educators adopt to ensure that students can access the curriculum through multiple avenues, ultimately achieving the vision of equitable classrooms across educational institutions (Tomlinson, 2014). Using a qualitative research approach, this study aimed to answer the following key question: How do teachers understand and utilize differentiated instruction to meet students’ individual needs in mixed-ability elementary classrooms? Data from semi-structured interviews with two Ontario certified teachers revealed that differentiated approaches are highly regarded and are utilized to ensure the holistic development of all students, evidencing its significant impact on student learning and motivation. However, findings also showed that the definition of DI is at times misunderstood. The way in which teachers conceptualize DI may hinder its implementation or provide a false sense of inclusivity in the classroom. Furthermore, the participants identified varied challenges when endeavouring to differentiate their instruction, including lack of staff support, lack of resources, and time constraints. In order to alleviate these challenges and consequently accentuate the benefits of DI, teachers need to be proactive and seek professional development in DI. Participants also noted the school administrators’ support as crucial to achieve successful implementation of DI.
Proceedings of the Fifth ACM/IEEE International Symposium on Networks-on-Chip

It is our great pleasure to welcome you to NOCS 2011, the 5th ACM/IEEE International Symposium on Networks-on-Chip. Over the past five years NOCS has grown to become the premier event dedicated to interdisciplinary research on on-chip and off-chip communication. Previous editions of this symposium were held in Princeton, New Jersey in 2007, Newcastle, United Kingdom in 2008, San Diego, California in 2009, and Grenoble, France in 2010. This year, we have the pleasure of hosting the 5th NOCS symposium in the beautiful city of Pittsburgh, Pennsylvania. We have a very exciting program this year. We received a large number of high-quality submissions, reflecting the vitality and growth of this new field. The Program Committee had a difficult task in selecting the best contributions among these submissions and putting together the final program. We received a total of 121 submissions, and an overwhelming majority of these papers were reviewed by four experts in the field (a handful of the submissions received three reviews). Thirty papers were eventually selected for presentation in the conference which represents a highly selective acceptance rate of 25%. The final program also includes 7 demo papers that complement the regular papers and two special sessions on key issues that will likely have a significant impact on the future of Networks-on-Chip.
Pengembangan Adaptive Particle Swarm Optimization (PSO) Dan Aplikasinya Pada Perencanaan Jalur Mobile Robot Dengan Halangan Dinamis

Kunci sukses dari navigasi sebuah mobile robot bergantung pada pembangkitan trajektori atau perencanaan jalur. Perencanaan jalur berbasis metode optimasi heuristik dikembangkan untuk menyederhanakan permasalaahan perencanaan jalur menjadi permasalahan optimasi. Salah satu metode optimasi heuristik yang sering digunakan dalam perencanaan jalur adalah Particle Swarm Optimization (PSO) karena kesederhanaan pada algoritmanya, mudah diimplementasikan dan memiliki sedikit parameter untuk diatur. Akan tetapi pada permasalahan perencanaan jalur yang kompleks dengan lingkungan dinamis, algoritma dasar PSO tidak dapat menjamin menemukan solusi optimal (local optimum) dikarenakan konvergensi prematur yang menyebabkan terjadi tumbukan dengan halangan dan jalur yang lebih panjang. Pada penelitian ini setelah perilaku pencarian PSO dianalisa, PSO adaptif dikembangkan dengan menggunakan fungsi Gaussian dalam pengaturan nilai parameter pada PSO untuk mempercepat konvergensi dan reinisialisai partikel dilakukan untuk mencegah terjadinya konvergensi prematur. Simulasi dan perbandingan dengan algoritma Adaptif Inertia (AIW) PSO dan standard PSO menunjukan algoritma yang diusulkan dapat menemukan solusi optimal lebih cepat dengan konvergensi kurang dari 150 iterasi pada halangan statis dan 200 iterasi pada halangan bergerak. Selain itu algoritma yang diusulkan memiliki 3% panjang lintasan yang lebih pendek, 10% lebih smooth dan lebih terjamin terhindar dari tumbukan. ======================================================================== The success key in mobile robot navigation depends on trajectory generation or path planning. Path planning based on heuristic optimization method is developed to simplify the path planning issues into optimization problems. One of the heuristic optimization methods used in path planning is the Pa rticle Swarm Optimization (PSO) that is often used because of its simplicity, easy to implement and has few parameters to set. However, in the case of complex path planning with dynamic environments, the PSO basic algorithm can not guarantee finding the op timum solution (local optimum) due to premature convergence that causes collisions , with longer obstacles and paths. In the proposed method, the Gaussian parameter updating rule use to speed up the convergence by maintaining exploration and exploitation o f the particle. Then, particle re - initialization is proposed after analyzing the behavior of PSO algorithm to prevent premature convergence. Simulation result shows in benchmark test with Adaptive Inertia (AIW) PSO and standard PSO that proposed PSO algor ithm can find optimal solution faster than the other algorithm which can convergence in less than 150 iteration in static obstacle and 200 iteration in dynamic obstacle. Proposed PSO algorithm with particle re - initialization can guarantee to find optimal solution with resulting path 3% more shortest, 10% more smooth and g uaranteed to collision free path.
Integrated Lecture Tools to Improve Student Competencies to Develop Physical Learning Media Design

Abstract Have been developed a lecture tool for Physics Learning Media Development course. Development applies the ASSURE model, with activities: analysis stages, formulating objectives, selecting media, selecting course materials, developing lecturing tools, implementations to collect student responses, and evaluations. The tools consist of syllabus, hand out, Student Activity Sheet, and Student Performance Appraisal Sheet. This research product has been tested on Physics Education Student of FMIPA UNJ. Student's response to lectures was collected using a fourteen-item questionnaire. The average score given by the students to the lecture is 72.03 good category. Student Performance Making Learning Media Design using this research product average 77,95 good category. Based on the student's response and the student's performance score in making the design of physics learning media, it can be concluded that the integrated lecture tools developed are worthy to be used as teaching materials for the Context Based Learning Media Learning course. Keywords: Lecture tools, Media design, Media development. Abstrak Telah dikembangkan perangkat perkuliahan untuk mata kuliah Pengembangan Media Pembelajaran Fisika. Pengembangan menerapkan penelitian pengembangan yang mengacu pada model ASSURE, dengan tahapan analisis kebutuhan, merumuskan tujuan, memilih media, memilih materi perkuliahan, menyusun perangkat perkuliahan, implementasi untuk mengumpulkan respon mahasiswa, dan evaluasi. Perangkat perkuliahan yang dikembangkan terdiri dari silabus, hand out, Lembar Kegiatan Mahasiswa, dan Lembar Penilaian Kinerja Mahasiswa. Produk penelitian ini sudah diujicobakan terhadap mahasiswa Pendidikan Fisika FMIPA UNJ. Respon mahasiswa terhadap perangkat perkuliahan dijaring menggunakan angket yang terdiri dari empat belas butir. Rerata skor yang diberikan mahasiswa terhadap perangkat perkuliahan adalah 72,03 kategori baik. Kinerja mahasiswa Membuat Desain Media Pembelajaran menggunakan produk penelitian ini rerata 77,95 kategori baik. Berdasarkan respon mahasiswa dan nilai kinerja mahasiswa dalam membuat desain media pembelajaran fisika, dapat disimpulkan bahwa perangkat perkuliahan terintegrasi yang dikembangkan layak digunakan sebagai bahan ajar untuk mata kuliah Pengembangan Media Pembelajaran Fisika Berbasis Konteks. Kata kunci: Perangkat perkuliahan, Desain media, Pengembangan media.
1 Design Technology Group

We describe the SAT solver Eureka. Eureka is a state-of-the-art SAT solver, used in various Formal Verification flows at Intel. Eureka is based upon backtrack search DPLL algorithm, enhanced by failure-driven assertion loop; non-standard conflict analyses; restart and clause deletion strategies; CBH decision heuristic and decision stack shrinking.
Applicabilité de la classification Clavien-Dindo dans l'évaluation des complications postopératoires dans la clinique chirurgicale du Centre Hospitalier National de Nouakchott: analyse observationnelle de 834 cas

Résumé Introduction Les complications postopératoires ne sont pas rares; certaines sont transitoires, d'autres peuvent être graves, mais elles sont toutes importantes pour les patients. L'une des plus importantes lacunes dans la recherche chirurgicale est le manque de consensus sur le résultat préféré, comment la mesurer ou l'évaluer. Méthodes Nous rapportons une étude rétrospective des complications post opératoires survenues au service de chirurgie générale du centre hospitalier national de Nouakchott. Huit cents trente-quatre patients opérés pendant sept mois (1er janvier 2017 au 31 juillet 2017). Les paramètres démographiques et cliniques ont été étudiés, analysés statistiquement sur le logiciel SPSS 20. Résultats Il s'agit de 834 patients dont 426 (51,1%) hommes. L'âge moyen: 34,81 ans (1-90ans). Quatre cents trente-deux (51,2%) patients opérés en urgence. Le sexe ratio (H/F): 1.04. L'ethnie arabo berbère représentait (77,8%). La pathologie appendiculaire (41,12%), pathologie hépatobiliaire (17,76%), pathologie de la paroi abdominale (16,1%). La pathologie thyroïdienne (5,6%). Cent quatre-vingt-trois (21,94%) patients ont développé des complications postopératoires dont 4 (2,1%) décès. Le grade II clavien-Dindo est le plus représenté avec 82,5% des compliquées et représente 17,91% de tous les opérés. L'infection du site opératoire a été de 62.8% de toutes les complications. Conclusion Cette étude a montré que la classification de Clavien-Dindo peut être appliquée pour les patients ayant subi une chirurgie élective et une chirurgie d'urgence. Nous pensons que le manque de suivi et le manque de moyen de lutte contre l'infection et le non-respect rigoureux des mesures d'asepsie et d'antisepsie jouerait un rôle important.
Theoretical Insights into Coverage Analysis of Cellular Networks

Recently tools from stochastic geometry have gained much attention for modeling and analysis of dense cellular networks. Although extensive studies are available in literature in this respect, the approaches are generalized and often lack significance towards practical scenarios where network conditions vary dynamically. The main objective of this research is to provide some insights into the stochastic geometry based analysis of cellular networks through suitable modifications so that it can be used to estimate parameters of interest i.e., intensity and coverage probability for different tiers and scenarios under consideration. The main definition for probability of coverage has been re-defined and complete closed form expression is derived. The intensity for different tiers have been estimated with the help of proposed approach, beyond which no more gain in coverage probability can be achieved. Monte-Carlo simulations have been performed for validation of proposed approach and results are also compared with stateof-the-art approach.
Guidelines for Working Collaboratively in Virtual Teams

As virtual teams continue to become more prevalent, educational administrators, faculty, and other members of online communities must discover and employ guidelines for effectively collaborating in online contexts. Applying the same traditional team strategies to those working in dispersed groups of people may hinder communication and prevent optimal results. In today's world, teams need to execute and learn at the same time. It is time to re-define what constitutes a (virtual) team and consider new avenues for cooperating in an increasingly diverse, global, and continuously “plugged-in” society. A set of practical steps for why and how virtual teams can collaborate in digital environments is presented. Tips for implementing the steps are provided. An analysis of technological tools available for facilitating online team collaboration is also shared.