Reviewerly/exHarmony huggingface dataset:
Revisiting challenges for selective data protection of real applications

Selective data protection is a promising technique to defend against the data leakage attack. In this paper, we revisit technical challenges that were neglected when applying this protection to real applications. These challenges include the secure input channel, granularity conflict, and sensitivity conflict. We summarize the causes of them and propose corresponding solutions. Then we design and implement a prototype system for selective data protection and evaluate the overhead using the RISC-V Spike simulator. The evaluation demonstrates the efficiency (less than 3\% runtime overhead with optimizations) and the security guarantees provided by our system.
Development of an image enhancement method forandroid applications

Digital image processing plays a vital role in enhancing images as it issaid that a picture is worth a thousand words. Image enhancement is the process ofimproving digital image quality. There are tremendous growths in the techniques usedto enhance images due to the advances in technology. Client in today’s world usesvarious tools for different image processing features while operating in the same digitalimage. In this paper, an enhancement image method is proposed and implementedas an android application. Few techniques of image enhancement are being applied inthe code construction together with another additional features to relocate image position.To test the effectiveness of this application, PSNR comparison test betweenoriginal and enhanced image and Application user-survey have been conducted.
Steel Cello and Bow Chimes

Freely suspended flexible metal sheets are wonderfully efficient resonators. Strike them, shake them, flex them; they readily produce a remarkable array of sounds. For musical purposes, though, they are hard to discipline. The sheet by itself lacks mechanisms for controlling the exuberant sound it produces. Robert Rutman’s best known instrument is the steel cello. It employs a metal stand to support an eight foot by two-and-a-half foot sheet of stainless steel. His bow chime uses five metal rods as initial vibrators. The rods are mounted upright on a horizontal bar set on a stand, attached to the bar by a mechanism which allows their length above the bar to be adjusted for tuning. Rutman creates music for the steel cello and bow chimes not by conceiving a musical idea and applying it to them, but by doing his best to allow the instruments to suggest the content of the composition.
SECURE USER AUTHENTICATION BY ENCRYPTED NEGATIVE PASSWORD

Secure password storage is a one of the main aspect in each and every system during password authentication, which is not at all stored in current systems.Almost all the systems try to encrypt the data which is to be stored into the database but they are not bothered about the password field which is to be stored into the database for user authentication. Hence in this proposed application, we try to apply Encrypted Negative password (ENP) in order to encrypt the plain password and then store the password in a secure manner.The main scope or objective of designing this current application is to apply multi stage security for password authentication by encrypting the given password and also try to apply hash generation technique on that encrypted password and try to generate a negative password which make the intruder so confuse to break the pattern.
METHODS FOR GRAPHING FUNCTIONS IN COMPUTERS USING WEB TECHNOLOGIES: METHODS FOR GRAPHING FUNCTIONS IN COMPUTERS USING WEB TECHNOLOGIES

This article describes the structure and various tools for developing websites and plotting the functions studied in the course of mathematics using Internet technologies. Markup and web programming languages, tools for site design and the use of a database to store information are considered. The presented program codes, in which the construction of graphs of a function with given coefficients is considered, can be used as a visual aid for those of interest, students, applicants, etc.
Polynomial Entropy of the Logistic Map

We study the polynomial entropy of the logistic map depending on a parameter, and we calculate it for almost all values of the parameter. We show that polynomial entropy distinguishes systems with a low complexity (i.e. for which the topological entropy vanishes).
A Framework for Satellite Imaginary using Deep Sat-4 and Deep Sat-6 Datasets

Satellite image classification is important for many real-time applications like environmental monitoring, disaster response and law enforcement.  These real time applications require the manual identification of objects. Satellite imaginary sorting is an vital task for remote sensing, machine learning and computer vision applications. The high variability of data most of the latest categorization approaches not appropriate for handle the imaginary  datasets. In this proposed system proposes the SAT-4 and SAT-6 deep sat datasets imaginary classifications using deep learning algorithms. In this proposed produces the classifications accuracy 98.3 %. Its more accuracy compared to the previous systems. Also in this paper we describe the dataset SAT-6 sand SAT-6.The proposed approach better representations for satellite imaginary.
PENINGKATAN KETERAMPILAN MENULIS CERITA PENDEK MELALUI STRATEGI PEMBELAJARAN BERBASIS MASALAH

The purpose of this research was to describe the improvement of short story writing skills of students in class IX-8 SMP Negeri 6 Balikpapan through problem-based learning strategies. The research method used is Classroom Action Research, abbreviated as PTK or Classroom Action Research, a form of research that occurs in the classroom in the form of certain actions taken to improve the teaching and learning process in order to improve learning outcomes better than before. Increasing the score indicates that the implementation of actions in the cycle I and cycle II, were able to improve students' abilities in learning and practice of writing short stories. The application of problem-based learning strategies is also able to provide motivation and pleasure in the Indonesian language learning process, especially writing short stories. Students appear to be more active and more enthusiastic in participating in the short story writing learning process.
Performance Measurement of Cloud Service Suppliers and Cloud Supply Chain

Over the past decade, cloud computing has received much consideration from both practitioners and academics. Nonetheless, the rapid increase in the industrial use-cases of cloud computing and the sharp increase in the number of cloud service providers (CSPs) have resulted in many challenges in performance measurement and the selection of the optimal CSPs according to quality of service (QoS) requirements. To date, there is no reliable approach for the performance assessment of CSPs and quantitative models are rarely used to support such decisions. In addition, the existing approaches to CSP performance measurement suffer from several limitations and drawbacks such as requiring complex calculations, being effort-intensive and being time-consuming. Furthermore, the existing approaches are unable to find slight differences between CSPs in a cloud marketplace owing to the high level of competition. These limitations are major obstacles to applying the existing approaches to assess CSPs. To address these issues in the existing literature, the objective of this study is to develop performance evaluation models based on the Data Envelopment Analysis (DEA) approach that can act as a proxy for many conventional performance assessment problems in cloud computing. The obtained results show that the models proposed in this study are extremely effective in measuring the efficiency of CSPs. Furthermore, the proposed models can deal with different types of data simultaneously in the efficiency measurement of CSPs and cloud supply chains, giving decision makers the ability to estimate the performance of CSPs efficiently.
Managing Cloud Services: Pricing, Strategy, Customers, and Operations

Cloud services have experienced a decade of explosive growth. With such expansion, cloud services eliminate barriers in reaching users and enable real-time interchanges and intelligence. Using business analytics, cloud services are increasingly embedded in the day-to-day activities of businesses and consumers with competition and innovative pricing. Due to the evolution in cloud business models, new issues are surfacing to challenge practitioners and scholars. A number of issues encountered in the practice have not been properly addressed or even recognized. In this paper, we attempt to fill this important gap. Based on our understanding of this industry's development and what is happening in practice, we propose a framework of recent business research on cloud services in light of wide adoption of the Software-as-a-Service business model. This framework broadly classifies cloud service research into four basic themes. For each theme, we review past work that has been instrumental in setting the direction of this line of research and discuss how emerging research opportunities can be addressed. For each research opportunity, we also propose an initial model and the applicable methodology. Further, in order to aid researchers, we identify the data sources wherever applicable, and even present some of the initial results. We conclude by describing promising directions on a roadmap for future research and explain why an integrative perspective of operations, marketing, and information systems is critical to cloud services. In this paper, we bridge the gap between research and practice by identifying the relevant industry problems that would help researchers who are interested in working in this area both to get a starting point and to address important theoretical and practical challenges.
Distributed Collaborative Framework for Deep Learning in Object Detection

Object detection has gained much attention in recent years because of its ability to localize and classify the objects in videos and images that can be incorporated into many applications. Traditional object detection algorithms need substantial computational resources to build a model. There is an increasing demand for a practical approach to constructing object detection models adapted to the local context, limited computing resources, and application logics while supporting real-time inferencing without degrading accuracy and performance. In this thesis, we proposed a distributed-collaborative framework to build practical object detection models. The framework is based on a novel approach for collaborative group inferencing that is designed with a single-class-single-model mechanism for multiple objects in a distributed manner. For useful grouping, we made use of the intraclass correlation from existing models during inferencing. Results from the case studies with Pascal VOC 2007 and our data collected through Google Street View showed that the proposed model significantly improved performance while making it potentially suitable for customized application building with limited computing resources. A prototype for the proposed model has been built, and a neighborhood application has been demonstrated to validate the proposed work.
IoT Security Function Distribution via DLT

With the rapid deployment of IoT devices, there is an increasing concern on the security and privacy of the devices.We are now witnessing newer and higher intensity attacks that exploit IoT devices.Although security-by-design is important and necessary, the effectiveness and sustainability of the buildin security defense may still be questionable.This has created new opportunities for third-party security service providers to enter the market.In this work, we leverage the distributed ledger technology (DLT) to propose a solution for distributing IoT security functions.We design the system architecture and describe the different types of operations to be executed.Our system also allows for reputation scoring that further adds credibility to the security functions distributed in the network.
A Framework for Improving Information Security Using Cloud Computing

The main objective of this paper is to propose a cloud based framework handling security issues in the existing data storage systems. There are various cyber security threats to existing storage systems because of their traditional architecture and operations applied on them for managing the data within Bahrain. Migration of local storage services to cloud environment is found to solve numerous related cyber security issues within Bahrain. On the other hand, a number of cyber security vulnerabilities are found to be emerged as a result of this migration such as public networks exposure and multitenant shared infrastructure. The vulnerabilities due to this transition introduce the security breaches and hence cause a threat to the underlying confidential information. The significance of migrating storage services to the cloud environment and the emerging cyber security issues in such a transition are analyzed thoroughly. The proposed framework is intended to support the existing information systems security schemes. It also provides the cyber security professionals with the ability to design, and customize cloud services that better suits the needs of organizations.
Searching harsh documents

Conventional, textual document search is arguably well understood. Traditional and modern (neural) algorithms are available; benchmark collections and evaluation metrics are prevalent. However, not all documents are conventional or purely textual. We explore what is takes to search "harsh" document collections. Such collections comprise potentially of documents that are natively non-digital, are multilingual, include components that are not strictly textual, are corrupted, or are a combination thereof. We address machine readability and its implication on search. We overview component segmentation and integration as a search process. We describe the processing of search queries that are informationally deficient or corrupt. We then comment on the evaluation of the selected efforts presented and highlight their history from concept to practice. We conclude with a brief commentary on ongoing efforts.
SEMANTIC AWARE SEARCHING OVER ENCRYPTED FOR CLOUD COMPUTING

In current day's the cloud based assistance is generally received by human services suppliers so as to store and access the significant wellbeing data of patients under secure way. Consequently is essentially appeared because of the explanation like part of end clients or E-Health frameworks attempt to trade the PHRs among each other and this might be inside separation or some of the time more far separation. Henceforth we proposed a novel technique called Secure Patients Health Records for putting away the patients wellbeing data in a safe way. In this proposed application a semi-believed intermediary called Setup and Re-encryption Server (SRS) is acquainted with set up general society/private key sets and to create the re-encryption keys. Additionally, the procedure is secure against insider dangers and furthermore authorizes a forward and in reverse access control
Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks

The pressure of ever-increasing patient demand and budget restrictions make hospital bed management a daily challenge for clinical staff. Most critical is the efficient allocation of resource-heavy Intensive Care Unit (ICU) beds to the patients who need life support. Central to solving this problem is knowing for how long the current set of ICU patients are likely to stay in the unit. In this work, we propose a new deep learning model based on the combination of temporal convolution and pointwise (1x1) convolution, to solve the length of stay prediction task on the eICU critical care dataset. The model - which we refer to as Temporal Pointwise Convolution (TPC) - is specifically designed to mitigate for common challenges with Electronic Health Records, such as skewness, irregular sampling and missing data. In doing so, we have achieved significant performance benefits of 18-51% (metric dependent) over the commonly used Long-Short Term Memory (LSTM) network, and the multi-head self-attention network known as the Transformer.
Preparation principle for Mohallah Playground Design, With Emphasis on Revival of Irainian Native Games; Case Study: Mohallah of Bagh-feyz in Tehran

Based on today’s scientists point of view, playing is not only a joy for children but also their life. He will gain and improve his needed future life skills by playing .hence it is important to pay extra attention to children’s playgrounds especially in scale of a muhallah which is their main social life base ground. This project has two main goals: 1) to find urban designing basics in order to improve quality of children and juveniles play grounds in scale of muhallah area. 2) some steps forward to revive domestic persian games by providing proper places for muhallah. in the beginning of this project the method of study was based on “quality meta analysis “ and in the following SWAT analysis method was chosen in order to make structured analysis of case studies. According to results of this study ,there are bunch of factors that matter to be able to meet all the requirements. Safety and security are the very first thing parents ask beside that a play grounds should be interesting for kids too. The key to make a play ground interesting is to meet variety. Absence of diversity is the main reason children focus on computer games and stay less in the play fields and fewer age groups get involved .in the mean while using persian games ,as an intangible heritage of our culture and history can insert a little bit of culture to games atmosphere and reduce Individualism, as our culture propunds social activities a lot.
Introducción al estudio del audiovisual: una experiencia de enseñanza innovadora en el contexto de la pandemia en el Uruguay

The pandemic forced educational actors to transform their practices to adapt them to the context. One advantage of the University of the Republic is that it already had a consolidated path regarding the incorporation of the Virtual Learning Environment (VLE). However, its use is still considered as «a repository to support face-to-face teaching» and distance education implies the development of pedagogical strategies with specific dimensions and approaches that lead to process transformations. It is possible that truly online teaching practices have existed with the use of EVA or that «successful» distance courses have been developed after the incorporation of educational innovations. Introduction to the study of audiovisual language is a curricular unit in the first year of the Bachelor’s Degree in Communication with an enrolment of more than 1500 students. During the pandemic, it proposed an inverted classroom modality that focused on the students’ process through: the diversification of didactic resources, contents and activities; the incorporation of instances of exchanges; and the change in the role of the teacher and the student. These innovative aspects, which are not limited to the use of the EVA, imply a modification in the organisation of the course and in didactics. This allowed for a better link between teacher – student – content and a higher percentage of passes. The above results in an innovation with relevant positive results, even in times of pandemic, in which socio-economic aspects are involved that further condition the particular characteristics of the educational contexts.
Safe Learning in Robotics

In many applications of autonomy in robotics, guarantees that constraints are satisfied throughout the learning process are paramount. We present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory. Then, we present methods for combining reachability with learning-based methods, to enable performance improvement while maintaining safety and to move towards safe robot control with learned models of the dynamics and the environment. We will illustrate these "safe learning" methods on robotic platforms at Berkeley, including demonstrations of motion planning around people, and navigating in a priori unknown environments.
Smart Routine Planner using Artificial Neural Networks

The disruptions caused by the COVID-19 pandemic have dramatically altered many of our normal routines, thus making it harder for most of us to cope with boredom, stress, and unpredictability. So, we came up with the idea of a smart routine planner, an application that will assist users to set realistic goals and create feasible plans to achieve them. Our goal is to bring a perfect balance between work and leisure by keeping a check on users’ work efficiency, eating and sleeping patterns, fitness routine, hobbies, and other recreational activities.
Development of Literation based Thematic Integrated Teaching Materials using Microsoft Sway for Class V Students of Elementary Schools

The integrated thematic textbook developed by the government and becoming a learning resource for elementary students already has the characteristics of literacy learning. However, using them for studying online is less effective. Therefore it is necessary to develop a teaching material that uses an online program/media which can be a reading source as well as a place to do exercises. This research is a development research using the Borg and Galls design. The evaluation method used refers to a formative evaluation design consisting of expert reviews and small group evaluations. The validity data were collected through the validation of teaching materials by 5 experts and analyzed using quantitative descriptive techniques. Practicality data were collected through observing the implementation of learning, and filling out questionnaires by teachers and students. The collected data from observations and questionnaires were analyzed descriptively and quantitatively. The results showed that the average expert and practitioner assessment of the content validity was 3.12 with the valid category and the construct validity 3.15 with the valid category. The average practicality assessment by students was 3.24 and by the teacher 3.25. This shows that the teaching materials developed are very practical. It can be concluded that literacy-based integrated thematic teaching materials using Microsoft Sway for grade V elementary school students developed are valid and very practical.