Reviewerly/exHarmony huggingface dataset:
ROI Selection Criteria for Finding the Abnormal Tissues from Breast Magnetic Resonance Imaging

The imaging methods in breast diagnostics play a preeminent role in the early detection and finding out the exact location &amp; area of the suspicious breast tissues for malignancy. The further treatment significantly depends on the tumour-tobreast size relationship. The tumor size considered as the most influential factors for pathological/clinical assessment of breast cancer. In general, localization of the tumor’s location and also the selection of a region of interest (ROI) were performed manually by an experienced radiologist. The objective of this paper is to propose an effective criterion for selection of ROI for abnormal tissues detection from breast MRI. This paper implements an efficacious ROI selection criterion for finding the exact location &amp; area of the breast abnormal tissues from magnetic resonance imaging automatically. The proposed algorithm integrates the simple techniques like filtering, edge detection and morphological operations for inner segmentation. Outer breast region segmentation is performed by selecting the peak and valley points and then connects the selected points by applying fit to circle function which makes the MR image rotation invariant. The method is implemented on the 80 images contained in S1 dataset i.e. multi-parametric breast MRI dataset and the evaluation is done through comparative analysis of predicted image with manually segmented images. The experimental results in terms of evaluation matrices i.e. Precision, Recall and Score depict the efficacy of the proposed work.
A New Feature based Scoring Technique to Discover Sentiments Present in the Online Product

The increasing usage of internet, online stores and social media has provided the users to express their opinion, attitude and views without any reluctance and fear on the World Wide Web. These opinions expressed by the users can be related to a product or service as well as any global issues. The colossal growth of the web technology has offered the consumers to know more about the products they intend to buy from the existing customer’s reviews. This paper focuses on analyzing the opinion by splitting the positive and negative opinion and then guides the user about the ground truth regarding the performance and quality of the product. The important idea here is to categorize the important features of the product and then accordingly provide the feature wise computation instead of roughly promoting a product as good or bad.
New Polyalphabetic Substitution Scheme for Secure Communication

The internet is a very powerful and useful tool for communication, information and connectivity. So it is very important to keep yourself safe and secure online. The best way of secure information is encryption; there are many cryptographic algorithms available for encryption. These cryptographic algorithms are classified according to their encrypting process; as substitution cipher or transposition cipher. In Polyalphabetic ciphers, the substitution rule changes continuously from character to character according to the keyword and plaintext. Vigenere cipher is considered to be the most efficient Polyalphabetic substitution cipher. But it is vulnerable to attacks, due to its repeating nature of the keyword. To overcome this vulnerability, here we are presenting a new Polyalphabetic substitution scheme which uses infinite number of 26 x 26 random tables for encryption. During encryption, whenever the keyword repeats, this proposed Polyalphabetic substitution cipher generates a 26 x 26 alphabetical random table. Instead of using the same Vigenere Table here we are using an infinite number of alphabetical tables depending on the length of the plaintext and keyword. Each random table will be completely independent from the previous table. This will reduces the repeating sequences in the ciphertext. The repeating nature of the keyword does not help the crackers to break this code. So this proposed Polyalphabetic substitution cipher is considered as an unbreakable cryptosystem. The Proposed Polyalphabetic cipher can provide security for many applications such as web transactions, web transactions, personal emails, secret information transmitted between public or private organization, military application etc.
Automation and Enhanced Service Delivery through Process Improvement in Hospitality Industry

Automated technology is revolutionizing the service industry and is a necessity in order to provide quality service. There are several ways in which hotels can incorporate the use of automated processes to improve service delivery, efficiency to customers and profit to the organization.Many areas in the hotels are explored for automation to analyze the role played by it. This study was pursued to understand the perspectives of operational heads who are implementing automation hands-on, which is important for the success of automation for enhanced service delivery through process improvement. About 30 senior executives from different categories of star hotels who handle day to day operations were selected and a semi structured questionnaire was administered. The findings indicate that there is a high prevalence of usage of function based software’s that has resulted in process improvement, customer outreach through GDS, increased revenue and enhanced service delivery. However challenges prevail in the areas like front office areas where there is a high level of personal interaction with customers. There is a positive perception about automation, but training and customization have been indicated as key for success.
From 2D to Next Generation VR/AR Videos: Enabling Efficient Streaming via QoE-aware Mobile Networks

Ranging from traditional streaming to Virtual Reality (VR) videos, the demand for video applications to mobile devices is booming. In the context of mobile operators a challenging problem is how to handle the increasing video traffic while managing the interplay between infrastructure optimization and QoE. Solving this issue is remarkably difficult, and recent investigations do not consider large-scale networks. In this dissertation paper we explore the solution space of efficient video streaming over mobile networks.
Aligning GBIF and the Atlas of Living Australia

The Global Biodiversity Information Facility (GBIF) and the Atlas of Living Australia (ALA) are two interconnected leading infrastructures serving the biodiversity community. Recognising that significant overlap exists in the function of the systems run by both organisations, and that advancement in technology allows GBIF to offer more functionality, we have initiated a process to align these infrastructures. Such a move is expected to bring the benefits of consistent data handling, improved bibliographic citation tracking, coordinated deployment of new features across the entire data publishing community, better reuse of modules and an overall reduction in cost of development, deployment and operation. This year, work has commenced to align these two infrastructures, focussing initially on data ingestion pipelines. The GBIF and ALA teams are collaborating closely, working on the same codebase, developing common working practices and agreeing on tools and coding standards. This focus on collaboration will lead to a defined model for the Living Atlas community to provide contributions. This work will also further the efforts to hand ownership of core ALA systems to the Living Atlas community and pave the way for the Living Atlas community to transition to the adoption of GBIF systems. Later this year, efforts will move towards use of a common registry for organisations, collections, datasets and associated metadata, which will reduce the effort spent in curating content, while also improving consistency by removing the need for synchronisation.
Privacy Protection for E-Health Records Over Mobile Cloudlet

Preparing of therapeutic data for the foremost half incorporates operation, data storage and data sharing etc. Usual social services framework often wants the conveyance for restorative data to cloud which incorporates purchasers touchy information and cause correspondence. For intents and functions, restorative data sharing is basic and testing issue. Be that because it could, there has been protection worries as on the brink of home well-being information can be bestowed to those outsider servers, and to unapproved parties. To ensure the patient's authority over accessing their Personal Health Records (PHR), it is a promising strategy to cipher the PHR before reappropriating. However issues, as an example; danger of protection introduction, ability in key administration, adaptable access, and skillful client denial, have remained the foremost very important difficulties towards accomplishing fine-grained, typographically approved data gets to regulate. During this paper, we tend to propose a completely unique patient driven system and a set of parts for data gets regulate to PHR place away in semi confided in servers. To accomplish fine-grained and versatile data gets to regulate for PHR, we tend to influence Attribute based encryption coding (ABE) strategies to cipher each patient's PHR document. Distinctive in respect to past works in secure information redistributing, we tend to center on various data owner state of affairs, and gap the purchasers within the PHR frame-work into numerous securities areas that very lessens the key administration many sided nature for proprietors and purchasers transportable cloud let. A high-level of patient protection is ensured whereas by misusing multi-specialist ABE. Our commit to boot empowers dynamic modification of access strategies or record qualities, bolsters effective for the asking client/characteristic repudiation and break glass access below crisis things. Broad scientific and trial results as displayed that demonstrate the protection, ability, and productivity of our set up.
The Information Geometry of Space-Time

The method of maximum entropy is used to model curved physical space in terms of points defined with a finite resolution. Such a blurred space is automatically endowed with a metric given by information geometry. The corresponding space-time is such that the geometry of any embedded spacelike surface is given by its information geometry. The dynamics of blurred space, its geometrodynamics, is constructed by requiring that as space undergoes the deformations associated with evolution in local time, it sweeps a four-dimensional space-time. This reproduces Einstein&rsquo;s equations for vacuum gravity. We conclude with brief comments on some of the peculiar properties of blurred space: There is a minimum length and blurred points have a finite volume. There is a relativistic &ldquo;blur dilation&rdquo;. The volume of space is a measure of its entropy.
Classification of Breast Cancer using Deep Learning Architecture

Human beings are affected by several diseases nowadays. All those diseases are healable with minimal amount of treatment when they are identified at its early stage. Several patients were not serious enough in diagnosing the disease initially, which makes the disease incurable for the patient lifelong. Hence in recent days number of death rates are getting increased. Cancer is the most dangerous diseases. Among several types of cancers women are mostly affected by breast cancer. In most of the developing and under developing countries breast cancer is the most prominent reason for women mortality. It is also curable when it is identified at its starting stage. During the later stages the cancer cells will be disseminated all over body hence it is difficult to remove it completely. Hence it has to be identified at its initial stage in order to give best treatment for the patient at right time. In this paper , Convolution Neural Network (CNN) a deep learning model is proposed for the investigation of breast cancer images for finding whether the person is affected by cancer or not. In the proposed work , features from images are extracted using convolution layers and then it is passed to the fully connected layer where it classifying the images as either malignant or benign. Experiments using standard benchmark datasets for the proposed CNN Model and standard Visual Geometry Group Network (VGGNet) has been conducted to measure its performances. From the results ,it is clear that CNN outperformed with the accuracy of 86.32% when compared to VGGNet which provides only 50% accuracy for the identification of breast cancer.
A Novel Model for Explainable Hostel Recommender System Using Hybrid Filtering

Recommender systems help humans in filtering and finding the right information from the enormous amount of data. Hostels are more famous than hotels for solo travelers, but no prior research related to recommender systems has been conducted in this domain. Hostels allow users to provide multi-criteria ratings and traditional recommender systems are not able to provide effective recommendations in case of multi-dimensionality i.e. contextual information and multi-criteriaratings. So, we have proposed a novel hybrid recommender system (SAFCHERS) that chooses the hostel's features for computation dynamically and provides explainable and better recommendations than the traditional recommender systems.
The Use of Mind Map Technique to Improve Study Group Students' Skill in Writing Descriptive Text

This study was conducted to improve the study group students’ skill in writing descriptive text using mind map technique. The subjects of the study were 9 students in Dana Punia Orphanage Singaraja. The data obtained was descriptively analyzed. The mean score of the pre-test was 54.5%, which was categorized as being poor to fulfill the students’ minimum standard score. After the treatment was conducted, the mean score of the students increased to 69.6% in the first cycle, and then increased to 75.3% after conducting cycle 2. The result of the study showed that the students’ achievement in writing descriptive text improved, it meant that the Mind Map technique was a very effective technique to be applied in writing descriptive text. This study is expected could be used as a reference for other researchers in conducting further study related to the teaching of writing in school, also as a comparison study for conducting technique in teaching writing especially using mind map Technique.
Optimization of Enhancement of Lecturer Professional Commitment using Path Analysis and Sitorem Method

Professional commitment of lecturers is an important element in the achievement of educational goals in universities, but from the initial survey at Pakuan University, it was shown that the current situation is still not as expected. Therefore, Professional commit-ment of lecturers is interesting to be studied. Based on the above background, the purpose of this research is to seek efforts to increase the professional commitment of lectures through the development of empowerment and trust. The study was conducted using path analysis method to determine whether other variables, namely empowerment and trust, had a positive effect towards professional commitment of lectures. The population in this research is permanent lecturer at Pakuan Uni-versity with functional position of Asisten Ahli up to Lektor Kepala amounting to 337 people with sample determined from popula-tion randomly amounted to 135 people. To obtain optimal results in an effort to increase the professional commitment of lecturers used Sitorem Method. The results showed that : (a) there is a positive direct influence of empowerment to organizational commitment, (b) there is a posi-tive direct effect of empowerment to organizational commitment, (c) there is a direct positive influence of trust on organizational commitment. From Sitorem's analysis it is concluded that there is a preserved indicator, i.e. open communication, readiness to accept occupation risks, sooth, and improvement desire, and indicators that need to be improved in order of priority of treatment is as follows: 1. au-thority, 2. discretion, 3. creativity and innovation, 4. confidence in ability and strength, 5. openness, 6. partnership strength, 7. awareness, 8. dedication and devotion, 9. consistency, 10. skills development..
Sociocultural dominants of developing students’ value intentions: context of civilization challenges

The study of the influence of sociocultural dominants on value intentions formation in young generation of specialists (teachers) is important for identifying useful ideas that can be implemented to improve axiological situation in the country and the world in accordance with civilization challenges. The article highlights a wide range of theoretical achievements and presents results of empirical research, which confirms positive dynamics of value intentions development in students of pedagogical and art specialties. Generalized conclusions about development of this important phenomenon in the context of declining demand for value dominants, are confirmed by statistics. The study was based on axiological, socio-cultural, systemic and interdisciplinary research. The research field consisted of educational institutions in Kyiv (Ukraine), the sample was 356 respondents (students of the first bachelor’s level). The adequacy of the applied experimental tools (questionnaires, Pedagogical essays) is proved. The experimental work was conducted online using Google services. The results of the study show positive dynamics of the value intentions development and a significant correlation between students’ motivation to value-oriented activities and sustainability of this direction in the future. The importance of sociocultural determinants in the development of value intentions in students of pedagogical specialties based on sociocultural knowledge is proved.
Pengukuran Metrik Kompleksitas Web Service Sekolah

The Complexity Metric Diagram is a method of measuring software complexity. This method uses Class Diagrams as test parameters. This study uses test data from previous research regarding the design of Information Systems accompanied by Class Diagrams with case studies of School Academic Information Systems. The facts found in the field that school software developers do not conduct application audits so it is not ripe to face problems that will arise in the future. The results of the calculation of the complexity metrics in the School Academic Information System produce an output of 993.32 units.
Encryption and Decryption Techniques in Cloud Computing

While big data applications in cloud computing are rapidly growing in popularity, privacy issues have increased dramatically. Encrypting data in real time is one of the most important issues during data processing and transfer. In order to reach an acceptable performance level, many modern applications forego data encryptions, which is incompatible with privacy concerns. This article covers several virtualized processes and analyses the cloud technology safety challenge and way to solve in brightness of cloud technology ideas and characteristics. Information confidentiality and dependability of services are major cybersecurity problems in internet applications. A singular monitoring platform will not address the cloud hosting privacy challenge; to defend the whole clouds infrastructure, a mix of old and new methods and technology must be employed in harmony. The author demonstrates the use of encoding and decoding techniques in aspects of the data confidentiality, computation time, and virtualized systems effectiveness. On top of this infrastructure, they may enable dynamically data storage functions on encoded information sections for inclusion, deleting, and updating, which we think will be future work for improvement.
Sistem Pakar dengan Metode Forward Chaining untuk Diagnosis Penyakit dan Hama Tanaman Semangka

Watermelon crops are in demand by farmers to cultivate. Diseases and Pests are not separated from watermelon crops experienced by farmers. To overcome this, farmers rely solely on rough living and getting information from others, this is ineffective because watermelon plant experts are very limited. An expert system is the solution to the limitations of an expert in their field. In this expert system use advanced chain methods and website-based applications. This expert system can be accessed online for users who need information, consultation of diseases and pests on watermelon plants. The expert system will diagnose the symptoms that will be answered by the user of the application and will produce conclusions along with solutions from diseases and pests of watermelon plants. With expert limitations online system is no longer an obstacle for watermelon plant farmers. Information and consultation of diseases and pests of watermelon plants biased online without having to meet with experts.
Implementation of Xor and Edge Identification Method in Steganography

In this paper, a novel imagesteganography algorithm that combines the strengths of edge detection and XOR coding, to conceal a secret message either in the spatial domain or an Integer Wavelet Transform (IWT) based transform domain of the cover image is presented. Edge detection and XOR coding are used in to conceal the secret message. Edge detection enables the identification of sharp edges in the cover image and this when embedding results in good image quality. Edge detection method presented here is capable of estimating the exact edge intensities for both the cover and stegno images (before and after embedding the message), which is essential when extracting the message. The XOR coding, on the other hand, is a simple, yet effective, process that helps in reducing differences between the cover and stegno images. Experimental results are observed using XILINX ISE and demonstrated that the proposed method has achieved better imperceptibility results than other popular steganography methods.
Foreground Moving Object Detection using Support Vector Machine (SVM)

Detect the existence of an object and to locate it in a video is called object detection. In the process of tracking an object we first segment the given frame and then track its position, motion and occurrence. Before tracking any object the process of object detection and object classification are done. Once we detect any object we have to classify the object into several categories like humans, vehicles, animals etc. There are many applications in which object tracking is being used such as robotics, traffic monitoring, security, video surveillance and animations. In this paper, we proposed a framework to detect the foreground moving object in a video scene at real time. Firstly preprocessing the given video is divided into frames to detect the object. Next morphological filter is used to remove the Nosie after detect the object. In this step, frame is divided into pixels. Here optical flow method is used to segment the given frames. After that, canny edge detector is used to detect the edge of object from segmented image. Finally, classify the object using Support Vector Machine (SVM).