Reviewerly/exHarmony huggingface dataset:
Fuzzy Magic and Bi-magic Labelling of Intuitionistic Path Graph

A graph labelling is an assignment of integers to the vertices or edges, or both, subject to certain conditions. Fuzzy labelling models precision, flexibility and compatibility to the classical models. The objective is to discuss about the magic and bi-magic labelling of fuzzy graphs. In the beginning the magic labelling of fuzzy path graph is discussed followed by the bi-magic labelling of fuzzy path graph. The next main purpose is to introduce the Intuitionistic path graph and examine the existence of fuzzy magic and bi-magic labelling.
AI Improves Tumor Origin Prediction Using Histology Images

Clinical OMICsVol. 8, No. 4 NewsAI Improves Tumor Origin Prediction Using Histology ImagesPublished Online:26 Aug 2021https://doi.org/10.1089/clinomi.08.04.02AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"AI Improves Tumor Origin Prediction Using Histology Images." Clinical OMICs, 8(4), p. 4FiguresReferencesRelatedDetails Volume 8Issue 4Jul 2021 InformationCopyright © GEN PublishingTo cite this article:AI Improves Tumor Origin Prediction Using Histology Images.Clinical OMICs.Jul 2021.4-4.http://doi.org/10.1089/clinomi.08.04.02Published in Volume: 8 Issue 4: August 26, 2021PDF download
Assessing Effectiveness of Exercised Variants of Machine Learning Techniques

Currently, the research field of machine learning is receiving more attention due to the automatic visual inspection of different tasks. Thus, the machine learning scheme is incorporated with deep learning and artificial intelligence technology. However, there are different schemes (perception based, instance-based and logic based) to provide an effective classification, prediction, and data recognition in terms of characterizing the features at different conditions to design a suitable module. This investigational study provides a comprehensive study on different algorithmic approaches which are categorized in terms of classification-based, prediction-based and segmentation based approaches. Also, this study evaluates the performance of various machine learning methods and their applications in different fields and also their limitations. Finally, this study leads to identifying the research gaps in the machine learning approach, which can be addressed by further research.
Dropout in Testing Phase Makes Adversarial Samples Generation Difficult

Deep neural network (DNN) brings the rapid development of pattern recognition algorithm.However, experiments show the vulnerability of deep neural network.This paper studied the problem of generating adversarial samples when we adopt dropout in testing phase.Based on MNIST database, we test four adversarial generation algorithms, two types of adversarial samples, and dropout in different layers of DNN.Several conclusions are obtained: (1) Dropout in testing phase makes DNN more robust with tiny performance loss.(2) Dropout in fully connected layer is the most efficient manner to improve the robustness of DNN.(3) Dropout has different impact on different adversarial samples generation algorithms.
Efficient Classification Rules for Complex Data in Decision Making

Information mining in enterprise applications facing challenges due to the complex data distribution in large heterogeneous sources. In such scenario, a single approach or method for mining limited the information needs and it also will be a high processing and time consuming. It is necessary to develop an effective mining approach which can be useful for the real time business requirements and decision making tasks. This paper proposed an efficient classification rules generation mechanism for complex data association and information mining using Multi-Features Patterns Combination (MFPC) method. The approach builds a strong association rule between multi features patterns using Feature reduction which will be used for efficient classification for complex data. The approach is evaluated in comparison with the existing feature reduction and classification approaches and measure the classification accuracy to show the flexibility and capability of the proposed mechanism in data classification.
IMPLEMENTASI SISTEM INFORMASI SKRIPSI PADA STIKOM DINAMIKA BANGSA JAMBI

The process of undergraduate thesis activities of STIKOM Dinamika Bangsa is still carried out conventionally starting from the notification of thesis information in the wall magazine to manual registration and the data collection process still uses Microsoft excel whose files are stored in each part that processes the activity. In the process of the thesis activity there are several problems encountered, namely the limited time available resulting in the accumulation of data, data input errors, delays in the process of making the proposal seminar schedule, the determination of the thesis guide and the thesis trial schedule. In addition because there is no student thesis information system, there is also someone who is cheating by changing the title of the thesis unilaterally, and also fake signatures for the proposal revision sheet and guidance cards for submission of thesis hearings. The data submitted by students when registering is also often incomplete, this results in delays in making the schedule of existing activities. To overcome the existing problems, a thesis information system is needed that can be used by every actor involved in this activity according to their respective needs. The purpose of this research is to implement the thesis information system using the object oriented approach method with PHP programming language and the MySQL Database that is directly connected to the SISFO STIKOM Dinamika Bangsa.&#x0D; Keywords : Information System, Thesis, UML, Academik
Heat Exchanger Process Optimization in A Typical Brewery Plant

The research attempts to improve upon the performance efficiency of the heat exchanger network system of Pabod Brewery, Port Harcourt, Rivers State, Nigeria. It swaps the heat system of the plant by the use of Pinch Technology to recover waste heat and integrating the recovered energy for process application. The application software is Microsoft Excel and Problem Table Method was employed in the numerical analysis of data. The gross energy expenditure by the plant is 10.44MW at production capacity of 400,000 liters of beer per day. On quantitative aggregate 6.157MW goes for heating and 4.267MW for cooling. A temperature pinch or minimum approach temperature (?Tmin)of 100C was used in the pinch analysis of the heat exchangers performance. The research findings confirmed minimum heating utility of 5.04MW and cooling utility of 3.09MW. with energy upturn of 1.08MW and 1.23MW for the hot and cold flows respectively. This correlates to energy conservation of 18% for hot utility and 21% for the cold utility. The hot stream pinch temperature is 710C while that of the cold stream is 610C. Heat exchangers network configuration design were performed above and below the pinch The network designs were produced and integrated to produce improved heat exchanger network system for the Brewery plant.
Applying distance sorting selection in differential evolution

Differential evolution is eligible for solving continuous optimisation problems. So far, the imbalance between exploration and exploitation in DE runs often leads to the failure to obtain good solutions. In this paper, we propose distance sorting selection where the individual has the best fitness among parents and offspring is selected firstly. Then, the genotype distance from another individual to it, which resembles the distance in their chromosome structure, can be estimated to decide whether the former individual is selected. Under the control of an adaptive scheme as proposed in the paper, we use it to replace the original selection of the CoBiDE in runs from time to time. Experimental results show that, for many among the 25 CEC 2005 benchmark functions, which have the similar changing trend of diversity and fitness in runs, our adaptive scheme for calling selection based on distance sorting brings improvement on solutions.
Cloud Computing

Cloud computing is a platform that provides state of the art information technology resources which are cheaper, scalable and easy to manage. But the cloud properties such as high scalability, quick deployment, dynamic resource range, high computing power, high bandwidth, etc. are exploited by cyber criminals as the tools for introducing new cybercrimes. These cybercrimes include DDoS as a service, Botnet as a service, Malware as a service, password cracking, BotClouds, C&C servers, Warez as a service, etc.
Penentuan Tingkat Kerusakan Peralatan Labor Komputer Menggunakan Data Mining Rough Set

Equitments of computer laboratory have a function as an important tools in supporting pratical lecturing. These facilities should always be on a condition like ready are proper to use both computers and others. To avoid equipment detriment, it is necessary to do early identification in which prevent the worse condition of equitments. The method use in this study is rough set method wich consists several stages such as Decision System, Equivalence Class, Discernibility Matrix, Discernibility Matrix Modulo D, Reduction, and Generate Rules. From this study, it was found that 14 rules in making decisions for equipments treatment of computer laboratory such as use, repair and replace. Thus, this mrthod is very capable in determining the detriment level of laboratory equipment.
Graduate studies in acoustics at Northwestern University

Northwestern University has a vibrant and highly interdisciplinary community of acousticians. Of the 13 ASA technical areas, 3 have strong representation at Northwestern: Speech Communication, Psychological and Physiological Acoustics, and Musical Acoustics. Sound-related work is conducted across a wide range of departments including Linguistics (in the Weinberg College of Arts and Sciences), Communication Sciences &amp; Disorders, and Radio/Television/Film (both in the School of Communication), Electrical Engineering &amp; Computer Science (in the McCormick School of Engineering), Music Theory &amp; Cognition (in the Bienen School of Music), and Otolaryngology (in the Feinberg School of Medicine). In addition, The Knowles Hearing Center involves researchers and labs across the university dedicated to the prevention, diagnosis and treatment of hearing disorders. Specific acoustics research topics across the university range from speech perception and production across the lifespan and across languages, dialect and socio-indexical properties of speech, sound design, machine perception of music and audio, musical communication, the impact of long-term musical experience on auditory encoding and representation, auditory perceptual learning, and the cellular, molecular, and genetic bases of hearing function. We invite you to visit our poster to learn more about the “sonic boom” at Northwestern University!
Research work presentation with Cards Diagram

In this paper, we proposed appropriate diagram to present and converted research work or data into information base of cards is called Cards diagram. It provide meaningful summary and very helpful for researchers/ students to decide and define research work in meetings. The concept of a diagram within diagram is being introduced the first time through it. The logic of a conceptual model, modelling language, meta-model and tool also explained with details.
Opening the Blockchain Ecosystem in Construction

Construction is undergoing digitalisation through innovations such as Building Information Modelling (BIM), Internet of Things (IoT) and blockchain. Various countries attempt to regulate, standardise and mandate such technologies. For example, various institutions, e.g. government, policy, businesses, and industry consortia, actively developed BIM implementation processes and pushed its use. However, in the lower tiers of the construction supply chain, the democratisation of BIM was problematic and Small and Medium Enterprises (SMEs) lagged behind due to limited resources. The digital divide reinforced mistrust in improvement agendas. This paper problematises around leadership necessary for democratising blockchain, an emerging digital technology.
Optimal integrity Policy for Secure Storage of Encrypted Data using Cloud Computing

Cloud computing is very common at reduced price because of its computing and storage ability. To reduce storage costs, an ever increasing number of information are being moved to the cloud. Then again, since the cloud isn't completely dependable, they are usually encrypted before uploading to shield information protection from outsiders and even the cloud server. However, many activities on encrypted information, such as searching, are difficult to conduct. Searchable encryption has emerged to solve this issue. It is much less effective to search for encryption in multi-user environment than in single-user environment. As a foundation of attribute-based encryption to solve this issue a multi-user searchable system is suggested. Our system also keeps information safe in opposition to the cloud server in the cloud. It enables users with suitable permissions to conduct encrypted information search activities. Furthermore, customers generate search tokens instead of information holders. We demonstrate that in our system, token privacy and index privacy are all around ensured. No helpful data about search tokens and ciphertexts can be obtained from the cloud server and illegal users. Our scheme's ciphertexts are constant in size, reducing our scheme's time-complexity and bandwidth overhead. Keywords : Token privacy , Index privacy, Cloud Computing, Encryption and Decryption.
An Effective Scheme for Shot Boundary Detection and Key Frame Extraction for Video Retrieval

The rapid development of devices for image capture and information sharing has resulted in the availability of huge amounts of online video for various applications such as education, news, entertainment, etc. This leads to problems and difficulties when users query any content-related video. The reason for this scenario is that the presently available techniques of content representation and retrieval are based primarily on annotation. It therefore provides insufficient information for understanding and retrieving the content to match the query of the user. Content Based Video Retrieval (CBVR) is one of the promising new ways for finding content in a large video archive, rather than simply searching terms. The primary steps for indexing, summarizing and retrieving video are shot transition recognition and representative frame extraction. We have proposed a key point matching algorithm for a superior and robust Scale Invariant Feature Transform (SIFT) followed by the collection of representative frames from each segmented shot using the Image Information Entropy method. By using the Rough Set Theory, we can get better the concert of this scheme through removing unnecessary representative frames. All the methods suggested to prove the efficacy were tested on TRECVID datasets and contrasted with state-of - the-art approaches.
Reviving Stories And Space Of The Past: Exploring New Opportunities In Mixed Media Storytelling

This project presents the idea that historic house museums (HHMs) can use Augmented Reality (AR) and physical interactive space to bring stories and characters of the past back to life. Designed to foster self-directed discovery and informal learning of the space and story, this project uses a historically factual AR character to reanimate the sense of human presence within the space. Rather than disrupting the traditional narratives of HHMs, this mixed media storytelling experience extends historical stories by making them more personal and relatable. Using tangible stories, multisensory interactions, and an AR experience to extend the historical narrative, this form of museological work creates more opportunities for empathic character-driven storytelling. Lastly, I identify that this proof of concept could be used in multiple applications, as both a storytelling medium and a communication tool.
Guidelines produce positive outcomes all round in advertising campaign

Media Officer Charlotte Raynsford explains how an unexpected call from Fidelity International made for a successful collaboration and an approved dog breed in a new TV advertising campaign.
M-Commerce for Agriculture Commodities using Android Application

Agriculture is the art of cultivation on soil. Agriculture acts as the evolution in the rise of human civilization, whereby farming local species created food supplies that enabled people to live in cities. E-agriculture is recent term in the field of agriculture and rural development practices. It is the global body of practice where people exchange information and ideas related to the Information and Communication Technologies (ICT). The issue faced by the farmers in today’s world is that they are not getting enough credits for their own crops. The middleman takes all credits in between the communication. Here, we develop a mobile app that establishes direct communication in between the merchant and the farmer with no middleman in act.
«Un arancio in gennaio». La Vita del beato Giovanni Colombini di Feo Belcari da racconto agiografico a testo di lingua

Composed between 1448 and 1449, the Vita del beato Giovanni Colombini by Feo Belcari was printed for the first time in 1477 and was destined to growing publishing success over the following centuries both as an independent text and in miscellany dedicated to the blessed. It will be the third edition of the Accademia della Crusca Vocabolario, published in 1691, to increase its affirmation by admitting the entire poetic and prose work of Belcari among the privileged references for the Tuscan vernacular and the Italian language. A recognition that will lead to a Veronese edition of the work in 1817, edited by authoritative scholars of Italian humanistic literature, which will condition many reprints of the work during the first half of the nineteenth century and which will persist even later, when it will be included in series very different, between religious and linguistic / literary interests.
Blockchain and Identity Persistence

Blockchain technologies are being touted as a way to protect individual privacy. Blockchain app developers and theorists, often out of a genuine desire to protect people and their privacy, have devoted considerable efforts to devising ways that the blockchain can be used to verify aspects of a static digital identity. However, these notions of a static, single, and accurate digital identity ignore the reality of how people's identities work, and especially the plural, time-varying, and fictionalizing elements of personal identity. This chapter charts out ways that people’s multiple identities may be affected and undermined by the development of public and unmodifiable ledgers of transactions and contractual undertakings. Following on from this discussion, the chapter applies a clearer model of identity to the blockchain use-cases of marriage, money laundering, and criminal justice records, and draws conclusions for regulators, blockchain applications developers, and the general public.
Arbitrary Quadrilateral Planar Object Tracking in TV Program via Shallow and Deep Models Ensemble

Being accurate and efficient arbitrary quadrilateral planar object tracking in TV program has a huge commercial prospect. This is a challenging problem because blur, rotation, scaling, occlusion, visual context and shot change are common phenomena in TV videos. In this paper, we present a practical ensemble method to tackle these challenges. This method is built upon several typical shallow and deep object tracking algorithms. An ensemble strategy is proposed which can fuse different trackers’ results by comparing the difference between different trackers without any human intervention. Different tracking algorithms are able to play their advantages and restrain others’ disadvantages, simultaneously. Moreover, a practical shot boundary detection method is utilized to refine the fused tracking results. Extensive experiments on the large scale real TV program dataset are conducted to demonstrate the effectiveness of the proposed ensemble method.
Finite-Time Synchronization of Chaotic Memristive Multidirectional Associative Memory Neural Networks and Applications in Image Encryption

Traditional biological neural networks lack the capability of reflecting variable synaptic weights when simulating associative memory of human brains. In this paper, we propose a novel memristive multidirectional associative memory neural networks (MAMNNs) model with mixed time-varying delays. More precisely, the proposed model is investigated with time-varying delays and distributed delays. Then we design two kinds of delay-independent and delay-dependent controllers to analyze the problem of finite-time synchronization. Based on the drive-response concept and Lyapunov function, some sufficient criteria guaranteeing the finite-time synchronization of the drive-response system are derived. With the removal of certain constraints on the weight parameters, the results we obtained for synchronization are less conservative. To illustrate the chaotic characteristics of the memristive MAMNNs, an image encryption scheme is designed. Meanwhile, the effectiveness of the proposed theories is validated with numerical experiments.
Design of Parity Preserving Reversible DIF-FFT using 90nm Technology

Reduction of power consumption is the major goal in modern circuit design. Reversible logic gate do not lose any information &amp; thus have zero power dissipation. In all signal processing applications, the most important computation involved is Fast Fourier Transform (FFT). For the fault tolerance computation parity preserving logic can be used .The authors present an efficient parity preserving reversible DIF-FFT using 90nm technology. The implementation involves the design of DIF-FFT with reversible P2RG along with Fredkin gate over different combinations of adders (Carry look ahead adder (CLA), Carry save adders (CSA), Carry skip adder (CSK) &amp; Ripple carry adder (RCA)) &amp; multipliers (Array Multiplier (AM), Carry Save Multiplier (CM), Parallel Multiplier (PM), Wallace Tree Multiplier (WM)). DIF-FFT Architectures of different combinations were coded using Verilog &amp; the same was simulated by Modelsim 6.3f. Parameters such as Hardware Device utilization &amp; Power analysis were done using Quartus II 9.0 with respect to Stratix II device which works on 90nm technology. It was found that DIF-FFT Architecture designed using CSA &amp; CM uses lesser resource utilization whereas architecture designed using CSA &amp; AM has lesser Power dissipation by 72% &amp; 81% respectively.
Linkage of Similar Code Snippets Assessed in the Micro Benchmark Service jsPerf

Welcome to the 21st IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2021)! We hope that you enjoy the conference and that it will inspire you in your future research. Should you require a certificate of participation please contact Alexander Serebrenik, the general chair of SCAM, at a.serebrenik@tue.nl. For questions related to the Morressier virtual platform please contact support@morressier.com.