Reviewerly/exHarmony huggingface dataset:
Attribute Based Encryption in Cloud Computing

Cloud acts as a database for huge amount of data. It allows users to store the information or data related items in the cloud storage and allows them to use/ their data via network connection. There are different types of cloud, Public private hybrid and community. In case of public cloud the user rents the storage and stores the data in it. There exist some trust issues in storing data in the cloud since there are many untrusted users who also rented the cloud and there is need for the encryption of data there are many ways to encrypt the data the new trend in encryption is attribute based encryption. The main advantage in attribute based encryption is that it depends on the attributes of the user which differs vastly from one user to another. This paper explains about the use of attribute based encryption in cloud and how it differs from the other encryption algorithms and it advantages over other algorithms. This paper also explains about the cipher-text policy in ABE in various aspects
Active Safety with Traffic Sign Recognition System in Vehicular Ad-Hoc Network (Vanet) using Classifier Techniques

Intelligent Transportation System (ITS) is one of the major research areas where the researchers focus on Vehicle traffic prediction, efficient routing algorithms, security in vehicle communication, various QoS parameters and so on..Wireless technology is progressing faster with time. People are doing research these days generally in the field of Wireless communication. VANET is the most developing exploration territory in remote correspondence. With the headway and development of the VANET, there will be an incredible upheaval in the field of telecommunication regarding quick handovers, arrange accessibility, security, wellbeing with the utilization of cutting edge applications and so on. VANET innovation is progressing with the progression of time however there are numerous issues that must be routed to make the system more overwhelming. In perspective of aforementioned, in this paper we have proposed an effective mechanism for object detection in highways using Neural Networking and proving driver assistance to enhance the existing system to the next level as Intelligent Transportation System.
Light Cryptography

Physical cryptography provides cryptographic protocols using physical objects like cards and envelopes instead of using computers. In this paper, we introduce a new model for physical cryptography, called light cryptography. It uses transparent sheets and some properties of light and shadows. We design several secure light cryptographic protocols: one for set-intersection (which can solve the scheduling problem), one for maximum (which can solve the Yao’s Millionaires’ problem), one for computing the sum of integers. We believe that our protocols using light cryptography are a powerful tool for information security education because they are fairly simple and fun to use.
Design and Implementation of AES Algorithm

In this paper the Advanced Encryption Standard (AES) was endorsed by the National Institute of Standards and Technology in 2001. It was intended to supplant the maturing Data Encryption Standard (DES) and be valuable for a wide scope of utilizations with differing throughput, zone, control dissemination and vitality utilization necessities .Though they are very adaptable, FPGAs are regularly less effective than Application Specific Integrated Circuits (ASICs); There have been numerous AES executions that attention on acquiring high throughput or low region use, however almost no examination done in the territory of low power or vitality productive based AES; actually, it is uncommon for assessments on power dispersal to be made by any means. This postulation introduces new effective equipment usage to those propelled encryption standard (AES) calculation. Two primary commitments are introduced in this thesis, the initial you quit offering on that one will be a secondary speed 128 odds AES encrypted, and the second person is another 32 odds AES configuration. In 1st commitment An 128 odds circle unrolled sub-pipelined AES encrypted is exhibited. In this encrypted a effective blending to those encryption methodology sub-steps will be executed following relocating them. Those second commitment displays An 32 odds AES plan. In this design, the S-BOX is actualized for inward pipelining Furthermore it is imparted the middle of those principle round and the enter development units. Also, the way development unit is actualized will fill in on the fly What's more previously, parallel with the fundamental round unit. These outlines bring attained higher FPGA (Throughput/Area) effectiveness analyzing to past AES outlines.
Examining Hidden Meaning of E-commerce Platform

Different e-commerce companies try to maintain high importance for their customer satisfactions. It helps them to understand the performance of their products. Nowadays customers trust on the product reviews while shipping online. But it is a cumbersome task to handle millions of customer reviews within specific time period. Due to this problem consumers usually follow the set of reviews before taking decision for purchasing any products from online. Although, each consumer rates the product from 1 to 5 stars, these overall product rating judge products towards their customers satisfaction. Consumers also provide a text based summary as a review of their experiences and opinions about the products. Customer sentiment analysis is a method to process these customer reviews to summarize different products. In this manuscript, we analyzed the text summery of Amazon food products using NRC Emotion Lexicon to determine the overall responses of the products using eight emotions of the customers. Our result can be used to take further decision making for the future of the products.
High-Throughput Low-Area Hardware Design of Authenticated Encryption with Associated Data Cryptosystem that Uses ChaCha20 and Poly1305

In this paper, the hardware design of a low area and a high throughput ChaCha20-Poly1305 that performs the dual authentication-encryption function for a secured communication within hardware devices is presented. Cryptographic algorithms- ChaCha20 stream cipher and Poly1305, enhance security margins and achieve higher performance measures on a wide range of software platforms and has proven superior to its counterpart, the AES, in the software domain. This relatively new stream cipher is compared to the benchmark AES, has recently been standardized but their implementations in hardware have had very little to not very desirable results particularly in terms of area. For this reason, it is therefore an active field to make such algorithms hardware friendly. This research presents a compact, low-area and high throughput chacha20-Poly1305 Authenticated Encryption with Associated Data (AEAD) design. The core architecture consists of the ChaCha20-Poly1305 algorithm. The simplified quarter round designed in the proposed architecture uses the addition, rotation and exclusive-or algorithms operators (gates). This proposed architecture provides an improvement in the operating frequency and area. The architecture was modeled and simulated with Verilog HDL and Modelsim tools for functional and timing correctness. The hardware architecture designed was synthesized with Xilinx‟s Synthesis Tool (XST) and Synopsis‟ Design Compiler (DC) using the 0.18µm CMOS standard Cell library. The resulting hardware area in terms of gate equivalent is approximately 11KGE for chacha20 and 21KGE for Poly1305. The design operates at maximum frequency of 420 MHz and 870 MHz for the ChaCha20 and Poly1305 respectively. The proposed design presented in this paper additionally functions at a throughput of approximately 8 Gbps for ChaCha20 with an overall efficiency of 2.35 Kbps/GE when ChaCha20 and Poly1305 are combined into the AEAD_ChaCha20_Poly1305 authenticated encryption core.
A resource retrieval method of multimedia recommendation system based on deep learning

In order to overcome the problem of too much time and low efficiency in retrieval caused by fuzzy representation of word vectors in multimedia recommendation system, this paper proposes a method of resource retrieval based on deep learning. Firstly, this method preprocesses multimedia resources and retrieval sentences, including morpheme segmentation, stop word processing, term normalisation, stem extraction, word vector processing. In the end, a deep retrieval model is built, to calculate the similarity between multimedia resources and retrieval statements, so as to achieve resource matching. The experimental results show that, while ensuring the accuracy of retrieval, the MAP value of short, medium and long retrieval statement fields is the maximum, which is 0.95, 0.92 and 0.88 respectively. The retrieval time is shortened by 0.3-0.6 s, which improves the retrieval efficiency.
Re-Visits the Grand Theory of Geoffrey Leech: Seven Types of Meaning

Meaning is the field of the study discussed in semantic science. Semantics is a branch of linguistics that studies the meaning of words in languages. In contrast, linguistics is the study of oral and written communications ​​that have systematic, rational, empirical characteristics as a description of the structure and rules of language. This present study argues that the meaning of a word in language can be known with the foundation of semantic science. The problems this present study focused on are the seven types of meaning and their descriptions in the book of Semantics by Geoffrey Leech: 1981. The research aims to classify and to identify seven types of meanings, and also to analyze Leech’s book and three article reviews of his theory. This present study uses a qualitative approach focusing on the words, phrases, and sentences regarding the theory. The result of this research confirmed that there are seven types of meaning based on Leech’s theory, namely conceptual, connotative, collocative, reflective, affective, social, and thematic. A novelty that this present study found is that the seven types of meaning have variations in their descriptions.
CHATBOTS, CONVERSATIONAL INTERFACES, AND THE STEREOTYPE CONTENT MODEL

Chatbots are becoming increasingly common in web-based business-to-consumer (B2C) communication.However, this technology can have high failure rates when it comes to correctly processing consumer inquiries, as human interactions and conversational dialogues are complex and highly context dependent.Besides improving the technology behind the chatbots, companies may be able to enhance a client's chatbot experience by using insights from the stereotype content model (SCM).Hence, this paper seeks to find out whether the model can be applied to the domain of chatbots and whether it holds true in this context as well.An online survey was conducted, and the results showed that people perceived the chatbots according to the model.Therefore, companies are advised to use the "loveable star" stereotype in their chatbot communication.Trust did not score significantly higher for this stereotype than for the other SCM stereotypes.This contradicts existing theory and is therefore an invitation for further research.
Hierarchical reinforcement learning based on multi-agent cooperation game theory

Reinforcement learning is a good way for multi-robot systems to handle tasks in unknown or fuzzy models. MAXQ is a layered reinforcement learning algorithm, but some of its parameters are limited. In order to improve the ability of processing tasks, in this paper, the improved MAXQ method is employed to adjust the parameters of the collaborative rules. In addition, in order to improve the task allocation speed, a cooperative game method is used among multiple robots. Finally, to test our approach, we conducted a series of experiments. The experimental results demonstrated that our model achieved better as compared with other detection models. The convergence speed is increased, by about 26%. It shows that our model is effective and efficient.
An improved ACO-based decision tree algorithm for imbalanced datasets

Prediction of the minority class is challenging for classification of datasets with skewed class distribution. Bio-inspired classifier such as ant colony optimisation (ACO) decision tree could not provide effective decision boundaries since its entropy-based heuristics is affected by the strong presence of the majority class. Consequently, the developed trees were dominated by the likelihood of the majority class while the rare class being inadequately represented. This study proposes an improved algorithm called Hellinger-ant-tree-miner (HATM) which is inspired by the ant colony optimisation (ACO) meta heuristic for imbalanced learning using decision tree classification algorithm. The proposed algorithm was compared to the existing algorithm with entropy-based heuristics, ant-tree-miner (ATM) using nine publicly available imbalanced datasets and a simulation study. Simulation procedure reveals the superiority of HATM under imbalanced class environment as the sample size increased. Experimental results show that the performance of the existing algorithm evaluated via minority class prediction (MCP) and F-measure has improved due to the class skew-insensitiveness of Hellinger distance. The statistical significance test shows that HATM has higher mean in both performance measures than ATM, indicating a potential improvement of ACO decision tree structure for imbalanced class domain.
CKGECS: a Chinese knowledge graph for elderly care service

Developing high-quality elderly care services supporting with modern information techniques is important to solve the increasing aging problem. Knowledge base is essential to the development of elderly care services. In which, knowledge graph is the most promising knowledge representation methodology. However, there are still more challenges on construction of Chinese knowledge graph, especially for elderly care service. Thus, based on three existing knowledge graphs, we proposed a new knowledge processing and fusion method to construct the Chinese knowledge graph for elderly care service. The experiments show that the proposed method can construct knowledge graph in a rapid way and the knowledge graph has better quality for elderly care service.
Reasoning Using Data: Two Old Ways and One New

Instead of two cultures, the story of the last couple decades of data science is about the interplay between three different types of reasoning using data.Two of these types of reasoning were well known when Breiman wrote his Two Cultures paper -warranted reasoning (e.g., randomized trials and sampling) and model reasoning (e.g., linear models).Breiman, though he does not appear to have realized it fully, was in fact describing the dynamics arising in a data community that was making progress using the newest, third type of reasoning -outcome reasoning.In this commentary we clarify this dynamic a bit, and suggest some useful language for identifying and differentiating types of problems better suited for outcome reasoning.
Theses and Capstone Projects Plagiarism Checker using Kolmogorov Complexity Algorithm

In education, students attempt to copy previous works and are relying on prepared solutions available on the Internet in order to meet their requirements. This action leads to plagiarism, which is becoming part of educational institutions’ concern to reduce growing academic dishonesty. With regards to the aforementioned issue, this study aims to design and develop a plagiarism checker capable of registering documents, granting access to users, and calculating the similarity between documents. Thus, the software was constructed using HTML, PHP, JavaScript, CSS, and MySQL. The developed system is composed of three main modules; the Document Search which enables users to browse documents, the Document Registration which enables the administrator to add and manage the stored documents, and the document Comparison, which serves as the system plagiarism detection mechanism. The algorithm Normalized Compression Distance was used to measure similarity and the Boyer-Moore Algorithm to highlight the suspected plagiarized document. Moreover, tests were conducted to determine if the system is functioning as expected and to measure the accuracy of the output produced by the system. The developed system was evaluated using the ISO 25010 software quality model in terms of Product Quality and was rated by one hundred respondents. The system obtained a mean of 4.70 which is equivalent to “excellent” in descriptive terms. This validates that the objectives of the study were met and achieved. This further indicates that the system was developed according to its desired functions and requirements.
A hybrid framework for ranking reviewers based on interval type-2 fuzzy AHP and VIKOR

Online reviews are crucial resources both for users and business enterprises. However, the quality of online reviews varies greatly. To address the problem of low-quality reviews, we focus on the problem of reviewer credibility and propose a new framework. The proposed framework incorporates three main parts including identification of source credibility factors, preprocessing, and ranking via interval type-2 fuzzy analytical hierarchy process (IT2FAHP) and VIKOR method. A major distinction of the proposed framework is utilising multiple factors obtained from different sources, which leads to considerably improved reviewers ranking. Furthermore, we propose a new method for defuzzification of interval type-2 fuzzy sets that yields more reasonable results when compared with the existing methods. The framework is evaluated using real data crawled from Epinions. The results indicated that the proposed framework effectively ranks the reviewers based on their credibility.
Sequencing Technologies: Introduction and Applications

The aim was to evaluate the impact of ABCB1 polymorphisms, C1236T and G2677T/A on the incidence of depression, its progression and effectiveness of antidepressant treatment in Polish population.Analyses were performed in 92 patients with recurrent depressive disorder (rDD) using automated sequencing.The obtained data were correlated with the results for C3435T polymorphism published earlier.Following that, a haplotype analysis was performed.For G2677T/A, the severity of depressive symptoms was higher among patients with GG.The more severe course of disease, the more frequently the lack of A or T allele was observed.Moreover, better effectiveness of the therapy was indicated in individuals with 1236 CC as well as in 2677 GG.Additionally, association of C1236T and (C1236T-G2677T/A-C3435T) haplotype with depression development was observed.Simultaneously, G2677T/A was connected with the severity of depressive symptoms.Both of the examined polymorphisms have influence on the effectiveness of antidepressant medications.
Design of remote electronic fire monitoring system based on K-means clustering algorithm

In order to overcome the problem of poor real-time response and accuracy of remote electronic fire monitoring system, a remote electronic fire monitoring system based on K-means clustering algorithm is proposed and designed. The hardware of the system includes communication module, smoke sensor, temperature sensor and image collector. In the design of system software, firstly, the database is constructed, the information collected by system hardware is collected into the database, the fire characteristics are extracted, and the smoke, temperature and image data in the database are clustered by K-means clustering algorithm. The fused fuzzy reasoning is carried out to determine whether the fire occurs or not, so as to realise remote electronic fire monitoring. The experimental results show that the response delay of the system is always under 1.5 μs, the response delay is short, the response accuracy is always above 95%, the monitoring accuracy is high, and it is practical.
Formal methods in dynamic software updating: a survey

Dymanic software updating (DSU) consists in updating running programs on-the-fly without any downtime that leads to systems unavailability.The use of DSU in critical applications raises several issues related to update correctness.Indeed, an erroneous dynamic update may introduce safety vulnerabilities and security breaches.In this perspective, the use of formal methods has gained a large interest since they respond to the high need of rigor required by such applications.Several frameworks were developed to first express update correctness which is based on several criteria.Then, the proposed formalisms are used to specify DSU systems, express correctness criteria and establish them.In this paper, we present a review of researches on the application of formal methods to DSU systems.We give a classification of systems according to the paradigms of programming languages and then we explain the correctness criteria and categorise the articles regarding the approaches of formalisation to establish the correctness.This information is useful to help ongoing researches in having an overview on the application of formal methods in DSU.
Mobile Controlled Automated wheelchair for Disabilities

As the usage of the Android smart phones has been considerably increasing, a lot of applications have been developed for the benefits of mobile users. In the past, many applications have been designed aiming to help physically disabled persons. This paper presents an android application which providers several options for controlling the movement of wheelchairs effectively. The proposed application enables People with Disabilities (PWDs) to operate the wheel chair with minimum effort. Apart from voice commands, the proposed application detects and measures the tilt change, and moves the wheelchair based on the degree of the tilt. It also provides a soft joystick as in mobile games to ease the operation of the wheelchairs. Furthermore, sensors that are fixed in the wheelchair can detect and avoid obstacles when the chair is on the move. Hence, it ensures the safety while using the wheelchairs. The proposed application will help both physically challenged persons and elders to operate the wheelchairs more comfortably.
Real Time Object Detection System

It is realized that innovative progressions are expanding at a quicker pace. In any case, the usage of these innovations is less in different parts. It is realized that the general population of nowadays need help for doing a few works when they were matured. .It is troublesome for visually impaired individuals to recognize these articles whenever lostinside a home. But since of these actualities, we may encounter different pressure and issues identified with the loss of those items for individuals. So, we propose a framework where we can distinguish the lost articles with the assistance of our proposed framework utilizing Image handling procedures. That additionally ready to support the individual depend to the face recognized and confine or personal the passage of obscure people. The current framework distinguied she the lost articles with the assistance of GPS. Yet, the use off aceac knowledge ment for individual recognizable proof by robots is not being used. It doesn’t give proficient yield. This causes different slack in the circuit. So we propose a framework to upgrade the item following.
Why Python?

There are plenty of substantive open source software projects out there for data scientists, so why Python? After all, there is the R language. R is a robust and well-supported language written initially by statistician for statisticians. Our view is not to promote one language over the other. The goal is to illustrate how the addition of Python to the SAS user’s toolkit is a means for valuable skills augmentation. Besides, Bob Muenchen has already written R for SAS and SPSS Users.