Reviewerly/exHarmony huggingface dataset:
Multiple Sequence Alignment by Differential Evolutionary Algorithm with New Mutant

Multiple Sequence Alignment (MSA) is vital in Bioinformatics, helps in finding evolutionary relationships among multiple species. MSA is a NP-complete problem. Though there are a number of tools recent Meta-heuristics are found to be effective in solving MSA problem. Differential Evolutionary Algorithm (DE) is one of the optimization algorithms with various mutants. This work proposes a new mutant for DE, defined using local best and worst chromosomes with current generation population. The performance of the new mutant is evaluated using 50 well known bench mark data sets in sabre (SABMARK v1.65). The results are matched with all the other DE mutants, Genetic Algorithm (GA) and recent Teacher Learner Based Optimization algorithm (TLBO). The proposed DE mutant outperformed all the other DE mutants, GA and TLBO in solving MSA problem.
A Systematic Data Mining Method for Clustering of Data using Map-Reduce Model

Data mining is an important research concept that has a vast scope in future. Data mining is used to find the unseen information from the data. In cluster, main half is feature choice. It involves recognition of a set of options of a set, because feature choice is taken into account as a necessary method. They additionally produce the approximate and according requests with the initial set of options employed in this kind of approach. The most construct on the far side this paper is to relinquish the end result of the bunch options. This paper conveys the cluster and the clustering process. The processing of large datasets the nature of clustering where some more concepts are more helpful and important in a clustering process. In clustering methodology many concepts are very useful. The feature selection algorithm which affects the entire process of clustering is the map-reduce concept. Here time needed to seek out the effective options, options of quality subsets is capable of providing effectiveness. The paper discussed map-reduce feature selection approach, its algorithm and framework of implementation.
Human respiratory system: designing student worksheet based on inquiry to promote 21st-century skills

A student worksheet is one of the learning resources containing work intended for students to be more active in learning. A student worksheet is designed based - inquiry so that learning is more meaningful and student-centered. Investigation optimally involves all students' ability to search and investigate systematically, critically, logically, analytically, so that they can formulate their findings confidently. This study aims to produce student worksheet based - Inquiry with profiles and qualities that are feasible to use in classroom learning, developed by adapting the ADDIE model. The validity of the worksheet development results is measured from the result of validation by the expert validator, the quality, and practicality of the worksheet seen from the responses given by students and teachers. The data of the development results were analyzed descriptively qualitatively. The results showed that the worksheet based-Inquiry had fulfilled the three requirements for proper worksheet preparation that is didactic, constructive, and technical requirements. Student worksheet based-Inquiry declared very valid with an average value of 3.70 and is feasible to use. A student worksheet is also in a first category based on the responses of students and teachers with scores of 82.92% and 83.50%, respectively, so it is concluded feasible to be used in learning.
STANDARDIZATION OF FORENSIC EVIDENCE, ITS PROCUREMENT, PRESERVATION AND PRESENTATION IN COURT USING FBI's TECHNIQUES BY FIA

Abstract&#x0D; &#x0D; The purpose of this paper is to present the some feasible standards used by US Federal Bureau of investigation (FBI) to enable Federal Investigation Agency (Pakistan) to enhance the authenticity of evidence and its consistency with the existing law. There are examples of several hundred cases, where the courts refused to punish the offender due to unauthentic inconsistent or naive evidence. The investigator is normally responsible to procure and preserve the forensic evidence to strengthen the case of the prosecutor. The investigator has follow up the legal procedure, technically in technically correct manner and consistent with provisions of Law, circumstantial and oral evidence. The inherent deficiencies and faults render the forensic evidence invalid sometimes and no use in the court. The approach of the paper is to standardise and synchronise the working as for as dealing with forensic evidence is concerned. The FBI provides very useful methodologies for procuring evidence from the sconce of offence, forensic services, examination of evidence, rendering forensic evidence,
Response to the interactive comment on “Remote monitoring of seismic swarms and the August 2016 seismic crisis of Brava, Cape Verde, using array methods” by Carola Leva et al.

Response to the interactive comment on
Histological grading of the prostate carcinoma using deep learning: an unsupervised approach (Erratum)

Publisher’s Note: This paper, originally published on 15, February 2021, was replaced with a corrected/revised version on 24 June 2021 If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
Term Charters

Expressions in specification and programming languages often extend algebraic terms by additional term formation rules and enlarged evaluation domains. For use in different contexts, the semantics of these expressions must allow for interface modification, that is, evaluation must be compatible with signature translation and with variable renaming. This work introduces term charters as an abstract framework for terms and expressions following the slogan “evaluation is invariant under change of notation”. Several examples illustrate the use of term charters. Different term charter representations are discussed and morphisms between term charters are defined. Finally, the relation of term charters with institutions in general and with context institutions in particular is demonstrated.
Discovering Constraint-based Sequential Patterns from Medical Datasets

The problem of mining sequential patterns from medical data has received a lot of attention as it aims to discover the causal relationship between different diseases or symptoms that are present in the patient’s body. Medical data contains the records pertaining to the information of the diseases or the symptoms of the patients besides the patients’ personal information. The records are ordered in accordance with the time and date of the patients’ visit in the hospital. Such data may offer precious information related to the cause and effect of a disease on the human body. Although, the date and time gives us chronological ordering of the occurrence of the diseases in the human body, it does not provide the information about the time intervals within which the successive diseases may occur. If the time gap of cause and effect is found to be too large, the concerned sequential pattern would be un-realistic. Considering, the time attributes of medical data, we try to address the above-mentioned problem on the sequential patterns. In this paper, we propose a method of extracting sequential patterns from medical dataset, with time-restrictions. The method extracts all sequences of diseases which occur within user-specified time intervals. The efficacy of our method is established with an experiment conducted on real life medical datasets.
Image Water-Marking/De-Watermarking using Spatial Domain Technique

There are various existing techniques for cryptography and watermarking. The multimedia data security can be achieved by means of encryption and decryption i.e. cryptography. While watermarking is employed for hiding multimedia data using images. The proposed work focuses on the new method combining these strategies for producing effective solution to improve security of secrete multimedia data. In the proposed dissertation work the images will be used as multimedia data. The proposed method involves the encryption of data to be hid. The cover image is then used as the media for hiding encrypted data. The encrypted data combined with cover image is treated as embedded image. The embedded image then compressed using wavelet transforms compression.
Blockchain-based Intelligent Monitored Security System for Detection of Replication Attack in the Wireless Healthcare Network

Wireless sensor networks have revolutionized the way healthcare works replacing the traditional methods with sensor-enabled IoT devices that help in monitoring the data. The data is collected by these sensors that are there on the body of the user, the data is transmitted over the network to the healthcare monitoring systems. The transmission follows the route of the wireless channel that is not secure as it can be accessed by legitimate as well as illegitimate users. These pose security threats; one such attack is a replication attack. This makes the replicas of the original node, replaces the data with the malicious content for attacking the system, and deploys the node back to the network making it difficult to detect. The aim of the work is to review the Blockchain-based intelligent monitored security system for the detection of replication attacks in the wireless healthcare network. The method used for review is the secondary research method. The main focus of the work is kept on the literature review for obtaining insights and knowledge. The results show that blockchain provides the required security to the data carried by the sensor-enabled IoT. The result contributed to the understanding of the different blockchain techniques in securing data. The system component is farmed in the work and verified in the results.
Eunomos: visually augmented natural soundscapes

Eunomos is an audio-reactive sonic art installations which features a traveling group of "electronic creatures" called SpeculÄtors. The SpeculÄtors are placed within a natural environment where they react using illuminated visual feedback according to environmental conditions.
Human Movement Detection using Recurrent Convolutional Neural Networks

Human Movement detection is vital in Tele-presence Robots, Animations, Games and Robotic movements. By using Traditional methods with the help of sensor suits it is difficult to find and interpret the movements. As it includes so much sensor data which is difficult to interpret, find the action and send to long distances. It is also very expensive and bulky too. Image processing and computer vision provides a solution to detect and interpret Human movement based on R-CNN approach. It is cheap, easy and light weight algorithm. It takes the video input and divides it in to frames, then it is Human body is separated for the background image. This paper mainly focused on skeleton, its major points and its relative positions in successive picture frames. A set of frames (Video) is given as input to the model, so that the model compares the coordinates of the successive frames and estimates the movement. First, the human is identified and separated from the rest of the image by drawing a bounding box around the human by using CNN (Convolution neural networks), then by applying R-CNN human is segmented and converted to skeleton. From the shape of the skeleton we can identify whether the skeleton is that of a human or not. Comparing the relative coordinates of skeletons extracted from frames photographed over time gives the movement of the human and its direction.
LIDAR-based surface following control for unmanned aerial vehicles

A simulation study is performed on a quadcopter which uses a LIDAR sensor to allow a quadcopter to navigate along and maintain a set distance from an unknown vertical surface. The dynamic equations of a quadcopter are linearized about the hovering equilibrium. For the purpose of design, all surfaces are assumed to be flat and any variations in shape are considered to be disturbances. The design process begins with the development of a potential field control design to allow the quadcopter to autonomously follow a flat surface, while maintaining a desired distance from the surface. To allow the quadcopter to follow a curved surface, the potential field technique is modified to maintain the xb axis parallel to the surface. Finally a wall following technique that directly uses the minimum range measurement to maintain the distance from the surface is developed. To simulate the control designs, a non-linear quadcopter model is used along with a model of a 2D scanning LIDAR sensor. The potential field control technique tracks flat surfaces with no steadystate error, though when curved surface following is added, a tracking error problem occurs due to measurement noise. The wall following design proves to be the superior surface following technique with greater robustness to steady-state error and results in relatively small tracking errors when navigating sinusoidal surfaces and corners.
Object Removal using a New Exemplar-Based Image Inpainting Algorithm and Seam Carving

This paper proposed a new object removal techniques based on exemplar-based technique and seam carving. Exemplar- based inpainting technique has been a point of attraction due to its moderate computational task an its performance. Moreover in this paper object removal technique for image based on discontinuous by seam carving has been introduced. Image inpainting is an approach fro restoring the damage part of an image in reference to the information from the undamaged part to make the restored image continuous, natural and to look complete. In this method patches are used to fill the target region in the image. Both texture synthesis and structure propagation are used simultaneously. Here robust exemplar method has been used avoiding dropping effect by using robust priority function. We have also used seam-carving for object removal. The PSNR values of the proposed model have been calculated and is also compared with the previous techniques’ results.
Ecological education activities at Russian National Public Library for Science and Technology: The Group of Ecology and Sustainable Development Projects

The experience of RNPLS&amp;T in ecological education of 1998 till nowadays is discussed, in particular the projects developed by Ecology and Sustainable Development Group.
Evaluation of Community Participation and Fire and Rescue Sub-dept. In Fire Prevention Tanjung Priuk District

This study aims to determine the level of community participation in fire prevention and management in Tanjung Priuk Subdistrict, the City of Administration against Fire Disasters in North Jakarta, the theory used in this research is the opinion of M. Nuh Minister of Education in the era of President Bambang Yudhoyono in Climbing the Amstein ladder to organize an ideal participation. The research method used is a qualitative method to obtain key data from interviews with legitimate sources that are directly involved in fire prevention and management and are supported by data from field observations. The data is then analyzed by the triangulation process. To find out the level of community participation. The results showed that the level of participation in fire prevention in Tanjung Priuk District had a range of information, consultations and appointments. the training program, which is carried out as an annual program, is provided for the community to provide information one way. In the management process, the community is at the second level of the seventh stage because the community is already a partner in the fire department before the fire department arrives at the fire location, the community has tried to extinguish the fire independently. To increase community participation in fire prevention and management, the Fire Department of the North Jakarta City Administration Office must optimize human resources, as well as other fire management resources, to be able to act also to provide costs for Balakar (Voluntary Fire) every month.
"Clicker" Technology

Keeping students engaged during orientation presentations and activities is a constant challenge to orientation professionals.In an effort to combat disengagement in Orientation, Washtenaw Community College (WCC) decided to borrow an instructional tool from the college classroom: clicker technology.Clicker technology (also called student response systems, classroom response systems, or audience response systems) is a classroom communication tool designed to solicit and report feedback from students during presentations.To use clicker technology, instructors pose a question to students using presentation software (usually built around PowerPoint) and students submit responses using a remote control that somewhat resembles the one you might use to change channels on your television (hence the name "clicker") (Bruff, 2007).These responses are then beamed via radio or infrared signal to a receiver on the instructor's computer and compiled and displayed graphically in the presentation (Bruff, 2007).By using this technology, orientation presentations at WCC have become more interactive as well as dynamic.This brief article explores why WCC chose to explore this new technology, how we use it, and how students and parents have responded to it.The decision to explore clicker technology in Orientation was driven by three main factors: mission, theory, and practical application.The mission of WCC's orientation program is to help students integrate into the community both academically and socially-two critical components in retention (Tinto, 1975).As higher education practitioners, we know that this can be a complex process and that the methods that have helped us do this in the past may not be the methods best suited for today.The literature related to active learning (Astin, 1999) and learning styles (Dunn & Dunn, 1992;Oblinger, 2003;Oblinger, 2004) has important implications for how we help students engage in their own learning.Active learning, a concept originally introduced by Astin (1999), involves engaging students physically and psychologically in the academic and social aspects of collegiate experience to enhance learning outcomes.However, many researchers believe that the learning process is mediated by a student's preferred learning style.Learning style is the way in which individuals begin to construct knowledge (Dunn & Dunn, 1992).Of specific interest to us was how to incorporate different preferences for learning modalities, the student's preference for visual, auditory, kinesthetic, or tactile learning (Dunn & Dunn, 1992) as well
Noise Removal Process from Label Classification using Machine Learning

Text classification and clustering approach is essential for big data environments. In supervised learning applications many classification algorithms have been proposed. In the era of big data, a large volume of training data is available in many machine learning works. However, there is a possibility of mislabeled or unlabeled data that are not labeled properly. Some labels may be incorrect resulted in label noise which in turn regress learning performance of a classifier. A general approach to address label noise is to apply noise filtering techniques to identify and remove noise before learning. A range of noise filtering approaches have been developed to improve the classifiers performance. This paper proposes noise filtering approach in text data during the training phase. Many supervised learning algorithms generates high error rates due to noise in training dataset, our work eliminates such noise and provides accurate classification system.
The Relationship Between Student’s Interest in Learning English And Their Speaking Ability at Muq Langsa

This research was conducted to investigate the relationship between students’ interest in learning English and their Speaking Ability. Interest is a tendency that the people know things or love some activities. Then, learning English is the important aspect to communication. The objective of study was to find out the relationship students’ interest in learning English and the impact of students’ interest in learning English. This research used qualitative research with descriptive design. The number of subjects were 15 students and only one teacher as informant. The research instrument was observation and interview. The result of research based on the researcher interview and observation, the researcher found that there is relationship between students’ interest in learning English and their speaking ability at the second-grade students at MUQ Langsa. The reason of students’ interest in learning English would like to try practice every time and also mastery speaking skill were important for students. Furthermore, there were impact of students’ interest in learning English for their speaking. It can be concluded that the relationship of students’ interest in learning English gave impact for students speaking ability.
Klasifikasi Teks Berbasis Ontologi Untuk Dokumen Tugas Akhir Berbahasa Indonesia

In this research, the classification of the final project document in Informatics Engineering UMM. The problem faced is the difficulty of finding relevant information and the difficulty of categorizing the TA documents according to areas of interest if it should be done manually. The purpose of this research is to get information based on abstract TA according to the category and make it easier to classify the TA document according to the field of interest. The categories used are the areas of interest in the study program: RPL, Computer Networking, Intelligent Game and Data Science. The data used TA documents as many as 500 data. The stage is to build and model ontology rules according to the data obtained with reference data of UMM Informatics Engineering Curriculum 2017 sourced from the Association for Computing Machinery (ACM) of the IEEE Computer Society. Ontology aims to classify the objects that exist in the collection without requiring the data train. To support the classification process used dao method. The dao method is used to calculate the similarity between documents from an existing node on the ontology by looking at the closest distance. Stage testing system using accuracy obtained result of 87%. This shows that ontologists are able to classify documents without using train data.
Load balancing of fog computing centre and its security using elliptic curve cryptography

The internet of things (IoT) and the fog computing paradigm are the next wave in the era of computing and have been emerging technologies in the fields of computer science and information technology. Prior research concentrates on the integration of IoT and fog computing but is limited because it cannot be extended to all applications due to inadequate security architecture. In this paper, we propose a biocryptography approach using biometric key generation for elliptic curve cryptography (ECC) based on the authentication of fog computing. In biometric-based ECC, a private key is generated via the fingerprint of the user ensures complete protection against security risks such as confidentiality, authentication, integrity, and privacy. The security strengths of various public key cryptosystems are analysed, and ECC is one of the best cryptosystems for fog-based IoT middleware.