bluuebunny/crossref_metadata_2025 huggingface dataset:
A LITERATURE REVIEW AND CLASSIFICATION OF BOOK RECOMMENDATION RESEARCH
Authors: Wang Feng , Zhang Lingling , Xu Xin
Published: July 2020

The act of reading has benefits for individuals and societies, which can be a long-term commitment. While the overload of books information and readers’ specific needs make book recommendation (BR) in demand, BR is receiving great attention from the research community with different perspectives. The increasing amount of research conducted with BR calls for a classification methodology regarding trends and distribution in this field. This paper presents a study of recommender systems in the domain of BR. The main goal of this work is to provide authors with insights on the trends of academic literature reviews in the proposed context and to present a comparison of different research approaches. The authors searched for up-to-date research papers related to recommender systems for BR within a time period of eighteen years, from 2000 to 2018. Starting from 2000, a significant amount of research related to the subject field of recommender systems was conducted, which led to the first ACM Conference on Recommender Systems. After the filtering process, 39 papers were finally selected from journals, conferences and theses in five different academic databases (i.e. IEEE, ACM, Science Direct, Springer and ProQuest). The general classification is presented in this work, in order to describe the recommendation approaches for BR. This work can be extended in the future to include novel methodologies and trends of recommender systems for BR or other fields.
URBAN PUBLIC SPACE AS SOCIAL INTERACTION SPACE: CASE STUDY IN PETALING STREET
Authors: Amir Syakir , Azizan Ainina , Zahari Rustam Khairi , Asmawi M. Zainora
Published: July 2020

Despite the fading cultural value as a Chinatown, the relationship of the society and its public space is a form of a natural phenomenon that is inseparable. The changing functions of public space in Malaysia were identified to decrease the quality of social and cultural activities in Petaling Street. Therefore, this study aims to explore urban public spaces as the main social driver in crating interaction in Petaling Street, Kuala Lumpur. The relationship between attributes of the urban public space and visitor retention were analyzed in this study. In terms of social interaction, the user activities were interrelated with the sociability of the urban space. The questionnaire survey was selected as the main medium for data collection distributed to the visitors and locals within the Klang Valley who have visited Petaling Street Chinatown. A total of 150 respondents involved and the analysis shows that street furniture does affect their preferences in an urban public space. Furthermore, the time spent by respondents will increase depending on the external factors such as weather and aesthetics. On the other hand, the internal factor that contributes to the number of visitors in Petaling Street Chinatown is their accompanying traveler which in the context of a solo traveler, the street should be celebrated with vibrancy.
POLITICAL AND LEGAL IDEAS DISCOURSE IN A NETWORK SOCIETY: SOCIAL-PHILOSOPHICAL ANALYSIS (PART 2)
Authors: N.N. Ravochkin N.N. ч
Published: July 2020

The article continues to define new essential features of the discourse of political and legal ideas realized by the authorities of modern states, which they acquire in the realities of a network society. It is shown that for the states to acquire an evolutionary vector and at the same time sustainability of social development, the authorities need to implement political and legal ideas depending on the context. As a research methodology, the author turns to his own synthetic epistemological methodological foundations, focusing on the provisions of social realism by R. Collins and N.S. Rozov, as well as theses of actor-network theory. In this part of the study, the author analyzes the leading trends in the development of network society, in accordance with which an updated manifestation of the discourse of political and legal ideas at the micro and macro levels is shown. The dependence of changes in the content of the discourse of ideas on increasing mobility, loss of identity, computerization, social memory and the social environment in which actors are presented is discussed in detail. In conclusion, the author notes that the ontology of the discourse of political and legal ideas in the context of a network society is only one of the private ontologies.
PSYCHOLOGICAL ANALYSIS OF FAMILY VALUES AND ATTITUDES OF YOUNG PEOPLE
Authors: Kiseleva T.G. , Enzeldt N.V. , Gileva E.N.
Published: July 2020

Fertility decline in Russia makes us look for ways to change this negative trend. The authors analyze the psychological causes affecting reproductive attitudes of young people. The sample of the study was made of students of pedagogical University, as they will form family values and reproductive attitudes in the younger generation. The study obtained data indicating the impact of integration and balance of the system of value orientations on the readiness of young people to family life. As disintegration of values increases, the desire and willingness of young people to build family relationships and to educate children decrease. The authors note a higher level of readiness for family life and family values in men, while for girls the intrapersonal conflict between work and family is resolved in favor of a career to the detriment of the family and children. The system of youth values is dominated by consumer orientation, entertainment orientation of life values and interests, which leads to a weakening of reproductive attitudes and behavior. The authors believe that the work aimed at the integration of values among young people will increase the value of family and procreation.
MAIN DIRECTIONS OF BIOMECHANICAL CHARACTERISTICS Of JAVELIN THROW
Authors: Al-Lami Wael Abdullah Hussein , Severukhin G.B.
Published: July 2020

At present, the effectiveness of training an athlete should be based not only on the experience and methodological skills of a trainer, but also on the ability to use modern technical tools, equipment that allows to receive urgent information about the various components of the training process in javelin throwing this should be based on equipment allowing to obtain biochemical analysis data. The article shows the possibilities of using biomechanical models in the training of athletes. Approaches to the construction of biomechanical models are considered. A biomechanical model of javelin throwing has been developed. The solution of the dynamics problem is given: the range of the spear’s flight depends on the absolute initial departure speed, departure angle, and spear release height. The most significant biomechanical characteristics of the “athlete-spear” system are determined. The possibilities of using the individual characteristics of an athlete in achieving the best results are shown.
PROMISING MODELS OF ETHNOCULTURAL EDUCATION (FROM THE PRACTICE OF PRESCHOOL EDUCATION IN THE UDMURT REPUBLIC)
Authors: Borodina A.E. , Nikolaeva E.A.
Published: July 2020

The article discusses the situation of preschool ethnocultural education in the Udmurt Republic. The theoretical aspects of the use of models in education are presented. To solve problems in the system of ethnocultural education, the Institute of National Education of the Republic of Udmurtia organized innovative activities in the preschool educational organizations. In order to improve the development of the native Udmurt language and culture in kindergardens, models of ethnocultural education created for the use of the “Zarni Bugor” educational complex in kindergardens of the Udmurt Republic are proposed. The analysis of educational models for the use of this educational and methodical complex in innovative kindergardens of the Institute of National Education of the Udmurt Republic is carried out. The prospects of ethnocultural education models for children in various individual educational situations are revealed. It is assumed that the proposed models of preschool ethnocultural education can be used by kindergardens of the Udmurt Republic and other regions interested in the preservation and development of native languages and cultures.
HUMOR AND VIOLATION OF SOCIAL NORMS IN STUDENTS
Authors: Artemyeva T.V. , Garanina Ya.G.
Published: July 2020

In researches of Russian and foreign scientists it is noted that humor as a cultural phenomenon is capable to symbolically break social norms without consequences and restrictions, to raise and discuss a wide spectrum of social problems without fear of punishment for it. By regulating the relationship between people, humor helps to relieve tension and enjoy the game, operating with opposite meanings, breaking stereotypes. The study attempted to explore the relationship between different styles of humor and the tendency of students to break social norms and rules. The study was attended by 309 students: 249 girls, 60 boys. Differences in the use of different humor styles by students as well as their propensity to deviate were identified. Affiliated and self-sustaining humor is used by students who do not show any desire to deny social norms and values, patterns of behavior. The desire to violate norms, to come into conflict with generally accepted norms of behavior arises among students who prefer aggressive humor. Girls with a tendency to ignore and violate norms and rules have a tendency to use self-deprecating humor and to seek other people's favour to the detriment of themselves.
Hemorragia alveolar por montelukast: reporte de caso
Authors: Martínez Montalvo Carlos M. , Gutierrez Rueda Laura C. , Flórez Remolina Daniela
Published: July 2020

La hemorragia alveolar difusa es un hallazgo clínico patológico, consecuencia de una lesión en la microcirculación pulmonar que se presenta con sintomatología inespecífica e incluso en pacientes asintomáticos. Se diferencian tres diagnósticos histopatológicos, siendo la capilaritis el más común y secundario a patologías autoinmunes. Se presenta el caso de un paciente, con hallazgo imagenológico y en lavado broncoalveolar, compatible con hemorragia alveolar difusa en quien se descartó como causa, enfermedades autoinmunes e infecciosas; durante la anamnesis, se identificó inicio reciente de montelukast, con relación temporal, respuesta a suspensión, cambio imagenológico y escalas de probabilidad de reacción adversa de Naranjo que apoya el diagnóstico.
Importancia de la implementación de la tomografía de tórax para coadyuvar al diagnóstico precoz y triaje oportuno de pacientes con la COVID-19 en hospitales del Perú
Authors: Pareja-Ramos Juan J. , Anicama Sue E. , Perez-Urrutia Percy , Pecho-Silva Samuel , Amado José
Published: July 2020

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Pengaruh Latihan Satu Sentuhan Diam Dan Bergerak Terhadap Peningkatan Passing Futsal
Authors: Mudian Deni , Risyanto Aris
Published: July 2020

Penelitian ini bertujuan untuk mengetahui Pengaruh Latihan Satu Sentuhan Diam Dan Bergerak Terhadap Peningkatan Passing Bawah Permainan Futsal. Metode yang digunakan eksperimen dengan membandingkan dua jenis latihan. Populasi dan sampel penelitian ini berjumlah 30 orang.Berdasarkan hasil penghitungan dengan menggunakan Uji t didapatkan hasil kelompok A diperoleh nilai t: thitung = 2,50 dan ttabe1  = 1,70, pada taraf nyata α = 0,05 dengan dk =14 ini berarti thitung lebih besar dari ttabe1 dapat disimpulkan Ho ditolak dan menerima Ha, yang berarti Latihan satu sentuhan diam memberikan pengaruh yang signifikan terhadap passing pada klub Futsal ‘Alamy Subang.Sedangkan kelompok B diperoleh thitung = 2,10 dan ttabe1 = 1,70, pada taraf nyata α = 0,05 dengan dk =14 ini berarti thitung lebih besar dari ttabe1 dapat disimpulkan Ho ditolak dan menerima Ha, yang berarti Latihan satu bergerak memberikan pengaruh yang signifikan terhadap passing pada klub Futsal ‘Alamy Subang.Berdasakan penghitungan data dan analisis data, penulis mengambil kesimpulan latihan satu sentuhan diam dan latihan satu sentuhan bergerak sama-sam memberikan pengaruh yang signifikan terhadap passing dalam permainan futsal klub Futsal ‘Alamy Subang, tetapi latihan satu sentuhan diam memberikan pengaruh yang lebih berarti dibandingkan dengan latihan satu sentuhan bergerak.
Six Years Monitoring of the Promising Low Grain-Cd Accumulating Rice, RD15 Cultivar Grown on Cd-contaminated Paddy Soils
Authors: Sriprachote Anongnat , Kanyawongha Pornthiwa , Boonplang Nutcharee , Phanchindawan Naree
Published: July 2020

The experiment was conducted on the Cd-contaminated paddy field, two of Thai rice cultivars, the prevailing KDML105 and RD15 were included together with determining grain-Cd accumulation. The results had revealed that the RD15 contained Cd in grains not only lower than KDML105 but also lower than the critical level as proposed by Codex (0.4 mg kg-1 polished rice). Thus, the RD15 was selected as the promising low grain-Cd accumulating rice cultivar, and farmers were encouraged to grow this cultivar. The grains of prevailing and promising rice cultivars were annually collected for Cd analysis. After six-years monitoring, the results revealed that the average concentration of Cd in KDML105 was 0.658 mg kg-1, which exceeded the critical level. On the other hand, the average concentration observed in RD15 (0.127 mg kg-1) was lower than the critical level. The human dietary intake of Cd through rice consumption was calculated, comparing to the provisional tolerable weekly intake (PTWI) as adopted by FAO/WHO (7 ug Cd kg-1 BW per week), the PTWI of KDML105 was far exceeded the critical level. Contrary, the RD15 had the PTWI lower than the critical level. Present results indicated that, by cultivating RD15 the promising low-grain Cd cultivar, Cd intake together with health risk of human could be reduced.
Influence of Coconut Fiber and Shell on Concrete
Authors:   UG Student, Department of Civil Engineering, Netaji Subhash Institute of Technology, Bihta (Patna), India., Prateek Prem , Srivastava Sukriti ,   UG Student, Department of Civil Engineering, Netaji Subhash Institute of Technology, Bihta (Patna), India., Kumari Priti ,   PG Scholar, Department of Nano Science & Nano Technology, AKU (Patna), India., Kumar Chandan ,   Assistant Professor, Department of Civil Engineering, Netaji Subhash Institute of Technology, Bihta (Patna), India., Murari Dr. Krishna ,   Professor, Department of Civil Engineering, BIT Sindri, Dhanbad (Jharkhand), India.
Published: July 2020

Concrete is a Composite material which is composed of Cement, fine aggregate, coarse aggregate binded together with a definite proportion of water. Concrete is widely used in every single construction work around the world. Due to large scale construction activities using conventional coarse aggregate such as granite as a constructional material extreme reduction in the natural stone deposit has been encountered and is affecting the environment, hence causing ecology imbalance. In current situation of construction, price factor and the wide range of extraction and processing of materialsis matter of great concern for the people as well as environment. Therefore, introduction of alternate waste material in place of natural aggregate in concrete production not only protects environment but also make concrete a suitable, economical and environment friendly construction material. Different material like Coconut Shell and Fiber can also be used alternatively. In this project CoconutShell and fiber are used as partial replacement for coarse aggregate as well as fine aggregate, respectively. To study characteristic properties of concrete 10% and 20% for coarse aggregate and 1%, and 2% for fine aggregate are replaced by its weight with coconut shell and fiber.
Predicting Alert Source Device using Machine Learning Algorithms
Authors:   Dell EMC Software & Services India Pvt. Ltd, Bangalore, India., B.* Bharath M. , Ashoka Dr. D. V. ,   JSS Academy of Technical Education, Bangalore, India.
Published: July 2020

In a large distributed virtualized environment, predicting the alerting source from its text seems to be daunting task. This paper explores the option of using machine learning algorithm to solve this problem. Unfortunately, our training dataset is highly imbalanced. Where 96% of alerting data is reported by 24% of alerting sources. This is the expected dataset in any live distributed virtualized environment, where new version of device will have relatively less alert compared to older devices. Any classification effort with such imbalanced dataset present different set of challenges compared to binary classification. This type of skewed data distribution makes conventional machine learning less effective, especially while predicting the minority device type alerts. Our challenge is to build a robust model which can cope with this imbalanced dataset and achieves relative high level of prediction accuracy. This research work stared with traditional regression and classification algorithms using bag of words model. Then word2vec and doc2vec models are used to represent the words in vector formats, which preserve the sematic meaning of the sentence. With this alerting text with similar message will have same vector form representation. This vectorized alerting text is used with Logistic Regression for model building. This yields better accuracy, but the model is relatively complex and demand more computational resources. Finally, simple neural network is used for this multi-class text classification problem domain by using keras and tensorflow libraries. A simple two layered neural network yielded 99 % accuracy, even though our training dataset was not balanced. This paper goes through the qualitative evaluation of the different machine learning algorithms and their respective result. Finally, two layered deep learning algorithms is selected as final solution, since it takes relatively less resource and time with better accuracy values.
Establishment of Solar –Wind –Biogas –BESS Based Hybrid Micro-grid
Authors:   mechanical department, RKDF University, Bhopal, INDIA., Kumar* Neeraj , Tiwari Sachin ,   electrical department, Lakshmi narain college of technology, Bhopal, INDIA., Sethi V. K. ,   energy department, R.K.D.F University, Bhopal, INDIA
Published: July 2020

The demand for energy increased due to industrialization, urbanization and population growth. In order to meet the demand for energy, Renewable Energy Sources (RES) are exploited because of its advantages such as developed economic growth and sustainability etc. The micro-grid implemented with isolated distributed generators (DGs) of coordinated operation within it. A hybrid system with all available sources of renewable energy such as solar PV, wind, biogas and battery energy storage system (BESS) for the purpose of 24hrs uninterrupted power supply for the no grid or weak grid regions of rural sectors of India has been recently established in IIEST Shibpur. The design and establishment of solar-wind-Biogas with battery energy storage-based hybrid micro-grid system presented. In this paper design, development and installation of micro-grid consisting of 10kWp solar PV plant, 1kW wind generating system, 35 cubic meter bio digester with 15kVA biogas engine and 1kW, 6kWh VRF battery are described.
Virtual By-passing of Query Server for Privacy of Users for Continuous Location Based Services
Authors:   Assistant Professor, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology Hyderabad, India., Poornima* P. , Vastari Mayur ,   Student, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology Hyderabad, India.
Published: July 2020

Location Based Services anticipate that customers should continually report their zone to a possibly untrusted server to get organizations reliant on their territory, which can open them to security risks. Tragically, existing security defending strategies for LBS have a couple of requirements, for instance, requiring a totally trusted in outcast, offering confined insurance confirmations and realizing high correspondence overhead. In this errand, A customer portrayed security organize structure called dynamic grid system (DGS) is proposed; the important sweeping structure that fulfills four central requirements for insurance shielding delineation and industrious LBS. The structure just requires a semi-trusted in outcast, at risk for doing clear planning undertakings viably. This semi-accepted pariah doesn't have any information about a customer's region. Secure delineation and steady zone assurance is guaranteed under the described enemy models. The correspondence cost for the customer doesn't depend upon the customer's optimal insurance level, it just depends upon the amount of huge central focuses in the area of the customer. Notwithstanding the way that the consideration is on range and k-nearest neighbor requests in this work, This structure can be easily connected with assistance other spatial inquiries without changing the estimations run by the semi-trusted in outcast and the database server, gave the essential interest an area of a spatial request can be engrossed into spatial regions. Experimental results show that the DGS is more productive than the best in class protection saving strategy for LBS.
Tuning Random Forest Parameters using Simulated Annealing for Intrusion Detection
Authors:   Research Scholar, Faculty of S&H(Computer Applications), Sathyabama University, Chennai, India., Ambikavathi*  , Srivatsa S. K. ,   Professor (Rtd.), MIT, Anna University, Chennai, India.
Published: July 2020

Intrusion detection system (IDS) security model is successfully utilized in static, distributed and dynamic network environments. Generally IDS needs a classification method for the decision of normal and abnormal events. This classification task is based on a set of features and massive amount of samples. However, all the features do not contribute the same level of prediction during classification. Hence feature selection (FS) has to be done before classification to select best features. Random forest (RF) does the dual role of FS and classification. Experiments have been done to prove that RF is the best classifier among other machine learning (ML) algorithms such as SVM classifier and C5.0 decision tree algorithm. However, the default parameter values of RF are not well suited for distributed environments such as cloud. It leads to poor accuracy and less efficiency in intrusion detection since enormous events have to be analyzed. So the parameters of RF have to be optimized by an efficient method. The important parameters of RF are number of trees, maximum depth of a tree, sample size, number of features considered to split a node (Mtry), node size and maximum leaf nodes. Among these parameters the hyper parameters are selected based on three decision factors, randomness; split rule; tree complexity. The issues to be considered during parameter tuning are to avoid over-fitting and under-fitting. Therefore Simulated Annealing (SA) is utilized for tuning these hyper parameters of RF which leads to improve detection accuracy and efficiency of IDS. The idea of using SA for parameter optimizing process is to avoid those issues since it never struck in local optimum. The proposed system significantly boosts the results of IDS. The efficiency of the proposed SA-RF is validated using CICIDS2017 dataset.
On the Development of an Empirical Model for Carcinomic Treatment using Chaotic Hyper-Heuristic Algorithm
Authors:   Department of Computer Engineering, Kalinga Institute of Industrial Technology, [Deemed To Be University], Bhubaneswar, India, Vijayeeta* Prachi , Das M. N. ,   Department of Computer Engineering, Kalinga Institute of Industrial Technology, [Deemed To Be University], Bhubaneswar, India., Mishra B. S. P. ,   Department of Computer Engineering, Kalinga Institute of Industrial Technology, [Deemed To Be University], Bhubaneswar, India.
Published: July 2020

A new dimension in the field of computational intelligence was introduced in the late nineties to comprehend a vivid combination of several multi-disciplinary areas. The coalescence biology along with data mining and statistical learning have given birth to Bioinformatics that provides various paradigms for studying the behaviour of unknown patterns at the micro level. In the present work, a recently developed human inspired optimization algorithm called search and rescue (SAR) optimization is employed with an improved version of parameters using Chaos theory. CSARO (Chaotic search and rescue optimization algorithm) unlike other existing algorithms has proven to be a better choice for optimising the gene selection mechanism as well as the control parameters of the learning model. This hyper heuristic algorithm obtained by the inclusion of chaos in SAR mainly aims at enhancement of its global search mobility and prevents from getting trapped in the local optimum. A comparative study with other existing techniques on seven benchmark datasets is performed. The performance of the algorithm is tested using evaluation metrics.
Development of a New Blind Watermarking for Medical Images
Authors:   Department of ECE, Lendi Institute of Engineering & Technology, JNTU Kakinada, Vizianagaram India., Paramkusam* Dr A. V. , Geetha M. ,   Department of ECE, Lendi Institute of Engineering & Technology, JNTU Kakinada, Vizianagaram India., Sailakshmi K. ,   Department of ECE, Lendi Institute of Engineering & Technology, JNTU Kakinada, Vizianagaram India., Mohansai M. ,   Department of ECE, Lendi Institute of Engineering & Technology, JNTU Kakinada, Vizianagaram India., Sowmya L. ,   Department of ECE, Lendi Institute of Engineering & Technology, JNTU Kakinada, Vizianagaram India.
Published: July 2020

Securing the data of patient and keeping the information confidential has become a challenging task at present days. More number of chances are available for information alteration or security breach. When the information is transferred from source to destination digital image watermarking technique is most commonly used to secure the patient’s information watermarking provides the copy right protection, authentication proof and detection of tampering. This paper presents a watermarking technique to embed patient’s information in a medical image so that information can be transferred securely and information alteration would be prevented. An Arnold Chaotic Map is applied to the sensitive watermark image to scramble the pixels in the sensitive watermark image. The cover medical image is partitioned into non overlapping blocks and DCT is applied to each block. Each and every bit of the watermark image is embedded into block by using Weber Descriptor. By using this Weber Descriptor robustness of an image will be increased. An experimental result shows that the proposed algorithm improves the robustness against various attacks like compression, filtering and noising.
Production and Utilization of Useful Fuel from Waste Cooking Oil and Waste Lubrication Oil: Performance and Emission-Quality in a Naturally Aspirated Diesel Engine
Authors:   Department of Mechanical Engineering, Global Academy of Technology, Bengaluru, India., B* Ghaleppa , Hiremath Suraj N ,   Department of Mechanical Engineering, Global Academy of Technology, Bengaluru, India., Pratapreddy Dr. Rana ,   Department of Mechanical Engineering, Global Academy of Technology, Bengaluru, India.
Published: July 2020

Increase in the demand for the alternative fuel for diesel engine as led to quest for feasible fuel with competitive cost and environmental friendly compared to petrolium fuel. This article deals on waste energy recovery. The aim of this experimental work is to find an attractive alternative fuel for the diesel engine by harnessing fuel from waste disposed oils. Waste Cooking Oil (WCO) and Waste Lubrication Oil (WLO) energy sources are used for fuel production. Collected WCO stored in a container, mixed and cleansed by removing solidified fats and other food leftovers before the transesterification. The acid followed by base catalyst transesterification processes carried out for biodiesel production. The WLO oil cannot be used directly in diesel engine and hence it is processed to be used like DLF using pyrolitic vacuum distillation method. The characteristics test such as flash point, fire point, density; viscosity and calorific value of the produced biodiesel, DLF, B10, B20, B30 and B40 were determined & compared with standards. Performance and Emission characteristics conducted in a single cylinder, free aspirated, water- cooled computerized diesel engine setup and results discussed. Results outcome shows that B30 exhibits the similar performance as pure diesel. The results show an improvement in brake specific fuel consumption, thermal efficiency. The unburned hydrocarbons, carbon monoxide emissions less but increase in the NOx.
Vision-Based Hand Gesture Recognition Techniques using Smartphones
Authors:   Department of Information Technology, MIT College of Engineering Pune, India., Devangan* Sachin , Joshi Omkar ,   Department of Information Technology, MIT World Peace University, Kothrud, Pune, India., Jaiswal Shanu ,   Department of Information Technology, MIT World Peace University, Kothrud, Pune, India., Gholap Apratim ,   Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India., Lokhande Dr Netra ,   Associate Professor, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
Published: July 2020

In the past few years, the computational performance of smartphone devices has seen tremendous growth. Due to which the smartphone has become a suitable platform for various computer-vision based applications which earlier was not possible. In this paper, we study various methods through which we can achieve computer vision-based hand gesture recognition natively on smartphones. If smartphones can support hand gesture recognition it can provide a new way to interact with mobile devices and overcome the hurdles of voice and touch-based user interface improving the user experience at the same time also supports other gesture-based applications. The techniques we study are mainly vision-based since camera module is present on most of the smartphones and it does not require other additional sensors or other hardware. We have compared the various methods available based on algorithms used and corresponding accuracy.
Artificial Intelligence based Pacman Game
Authors:   Department of Computer Science and Engineering,,VRSiddhartha Engineering College, Kanuru, India., Maddipati* Himakar Sai Chowdary , Kundurthi Aravind ,   Department of Computer Science and Engineering,,VRSiddhartha Engineering College, Kanuru, India., Raaj Pothula Mahima ,   Department of Computer Science and Engineering College,VR Siddhartha Engineering College ,Kanuru, India., Srilatha Kapudasi ,   Department of Computer Science and Engineering ,VR Siddhartha Engineering College,Kanuru,India., Surapaneni Ravikishan ,   Department of Computer Science and Engineering, VR Siddhartha Engoineering College, Kanuru, India.
Published: July 2020

This paper is about implementing pacman game with AI.The Game Pac-Man is a very challenging video game that can be useful in conducting AI(Artificial Intelligence) research. Here,the reason we have implemented various AI algorithms for pacman game is that it helps us to study AI by using visualizations through which we can understand AI more ef- fectively.The main aim is to build an intelligent pacman agent which finds optimal paths through the maze to find a particular goal such as a particular food position,escaping from ghosts.For that, we have implemented AI search algorithms like Depth first search,Breadth first search,A*search,Uniform cost search.We have also implemented multi-agents like Reflex agent,Minimax agent,Alpha-beta agent.Through these multiagent algorithms,we can make pacman to react from its environmental conditions and escape from ghosts to get high score.We have also done the visualization part of the above AI algorithms by which anyone can learn and understand AI algorithms easily.For visualisation of algorithms,we have used python libraries matplotlib and Networkx.
Application of Corrugated Core Sandwich Structures in Thin Cylindrical Pressure Vessels
Authors:   M.Tech Student, Department of Mechanical Engineering, Sri Vasavi Engineering College, Pedatadepalli, Andhra Pradesh, India, Vivek* T.N.S.K. , Murthy K. Sri Rama ,   Assistant Professor, Department of Mechanical Engineering, Sri Vasavi Engineering College, Pedatadepalli, Andhra Pradesh, India., Mamilla Dr. Venkata Ramesh ,   Professor & Head, Department of Mechanical Engineering, Sri Vasavi Engineering College, Pedatadepalli, Andhra Pradesh, India.
Published: July 2020

the need for the high strength to weight structures is increasing day by day. The structures with high strength to weight ratio helps in reducing the costs in transport of materials. The sandwich structures are being developed to meet this criterion. A sandwich structure consists of two flat sheets with core between them. The material of core and outer flat surfaces may or may not be the same depending upon the application of the structure. In this project, the corrugated core sandwich structure will be used for the cylindrical shell of the pressure vessels. Pressure vessel with corrugated core sandwich structures will be designed and various analyses will be performed. The results will be compared with thin cylindrical shell pressure vessel under similar conditions. The pressure vessels will be designed in solidworks software and structural analysis will be performed in ansys workbench.
Analyzing the Performance Factors of Machine Learning Algorithms for COVID'19 Data
Authors:   Assistant Professor & Department of Computer Science and Engineering & KSR Institute for Engineering & Technology, Venkatesan* R. , Nandhagopal S. ,   Assistant Professor & Department of Information Technology & KSR Institute for Engineering & Technology, Sabari A. ,   Professor & Head Department of Information Technology & K.S.Rangasamy College of Technology
Published: July 2020

Machine learning is a branch of Artificial intelligence which provides algorithms that can learn from data and improve from experience, without human intervention. Now a day's many of the machine learning algorithms playing a vital role in data analytics. Such algorithms are possible to apply with the recent pandemic COVID situation across the globe. Machine learning algorithms are classified into 3 different groups based on the type of learning process, such as supervised learning, unsupervised learning, and reinforcement learning. By considering the medical observations on the COVID across the globe it has been discussed and concluded to analyze under the supervised learning process. The data set is acquired from the reliable source, it is processed and fed into the classification algorithms. Since learning behaviors are carried out by knowing the input data and expected output data. The data is labeled and has been classified based on labels. In the proposed work, three different algorithms are used to experiment with the COVID'19 dataset and compared for their efficiency and algorithm selection decision is made.
Recognition of Face Emotion using Convolutional Neural Network
Authors:   Professor, Department of ECE, Chaitanya Bharathi Institute of Technology (A), Hyderabad, India., Sastry* Dr. Panyam Narahari , Syed Mohammed Sameer ,   PG Scholar, Department of ECE, Chaitanya Bharathi Institute of Technology (A), Hyderabad, India.
Published: July 2020

Recognition of face emotion has been a challenging task for many years. This work uses machine learning algorithms for both, a real-time image or a stored database image in the area of facial emotion recognition system. So it is very clear that, deep learning technology becomes important for Human-computer interaction (HCI) applications. The proposed system has two parts, real-time based facial emotion recognition system and also the image based facial emotion recognition system. A Convolutional Neural Network (CNN) model is used to train and test different facial emotion images in this research work. This work was executed successfully using Python 3.7.6 platform. The input Face image of a person was taken using the webcam video stream or from the standard database available for research. The five different facial emotions considered in this work are happy, surprise, angry, sad and neutral. The best recognition accuracy with the proposed system for the webcam video stream is found to be 91.2%, whereas for the input database images is found to be 90.08%.
Word and Chracter Segmentation in Devnagari and Odia Script – A Comparitive Analysis
Authors:   M.Tech Computer Science, C-DAC, Noida, India., Pattnaik* Ipsita , Patnaik Tushar ,   Research & Development, C-DAC, Noida, India.
Published: July 2020

Optical Character Recognition has been an active research area in computer science for several years. Several research works undertaken on various languages in India. In this paper an attempt has been made to find out the percentage of accuracy in word and character segmentation of Hindi (National language of India) and Odia is one of the Regional Language mostly spoken in Odisha and a few Eastern India states. A comparative article has been published under this article. 10 sets of each printed Odia and Devanagari scripts with different word limits were used in this study. The documents were scanned at 300dpi before adopting pre-processing and segmentation procedure. The result shows that the percentage of accuracy both in word and character segmentation is higher in Odia language as compared to Hindi language. One of the reasons is the use of headers line in Hindi which makes the segmentation process cumbersome. Thus, it can be concluded that the accuracy level can vary from one language to the other and from word segmentation to that of the character segmentation.
Speech Based Depression Detection using Convolution Neural Networks
Authors:   Department of Computer Science, Lal Bahadur Shastri Institute of Technology for Women (LBSITW), Thiruvananthapuram, Kerala, India., Krishna* Swathy , J Anju ,   Assistant Professor, Department of Computer Science, Lal Bahadur Shastri Institute of Technology for Women (LBSITW), Thiruvananthapuram, Kerala, India.
Published: July 2020

Depression has become a serious mental disorder nowadays affecting people of almost all age groups. Loss of interest in daily activities, constant feeling of being isolated, hopelessness etc. causing significant impairment in life. This illness will affect the physical and mental health of the individual affecting his/her emotional stability. Emotions are a way of expression of one’s state of mind in the form of thoughts, feelings or behavioural responses. For a depressed individual, the emotions are often negative in nature. Diagnosis of depression is a complex task as the disease may be unidentified by the patient itself. Sometimes the patient may be reluctant to consult a doctor. The long term ignorance of the illness may worsen the mental health of the one suffering from it. Thus the early diagnosis of depression is of great significance. With the emergence of neural networks and pattern recognition, many researchers have put effort in detecting depression by analysing non-verbal cues, such as facial expressions, gesture, body language and tone of voice. Recent studies have shown that the speech emotion analysis can effectively be used in distinguishing emotional features and a depressed speech varies from that of a normal speech to a great extent. The depressed patient normally speaks in a low voice, slowly, sometimes stuttering, whispering, trying several times before they speak up or become mute in the middle of a sentence. This paper proposes a CNN architecture for learning the audio features in the speech for detecting depression, identifying the emotions and to infer the emotional severity of the individual. This paper also reviews some of the existing research methods in the field of depression analysis.
Automatic Grading of Diabetic Retinopathy through Machine Learning
Authors:   M.Tech understudy, Department of Electronics and Communication at SDM College of Engineering and Technology, Dharwad, Karnataka, India.., Kamatgi* Supriya Sangappa , Hosur Dr. K. N. ,   Assistant Professor, Department of Electronics and Communication Engineering at SDM College of Engineering and Technology, Dharwad, Karnataka, India.
Published: July 2020

Diabetes Retinopathy (DR) illness refers to a group of eye issues that can happen because of diabetes. It's the medical phenomenon within which a person’s retina is broken by the diabetes. During this stage the tinny blood vessels present within the retina get damaged due the high glucose level. This ends up damaging the tiny blood vessels within the retina leading to the loss of vision. Different complications occur due diabetes a number of them are upset, neuropathy, nephropathy, retinopathy, skin damages, hearing ailments. Globally, diabetic eye disease has become the fifth most common reason for blindness. Early identification of DR is important to forestall vision loss or blindness. In this paper the strategies like Naïve Bayes classifier, Bagged Decision Tree and Support vector machine are implemented and are used for the classification of data based on the training and testing datasets. The errors and accuracy of all the three classifiers are figured and the best among three is considered for the future application. This implementation is done in the MatLab software and results shows that the Bayes classifier gives the error 0.2, Bagged Decision Tree Classifier gives the error of 0.1 and the Support Vector machine gives the error of 0.04 is observed. Hence these observations shows that the Support Vector machines are good classifiers with the accuracy of 96%.
MQTT Protocol based Smart Greenhouse Environment Monitoring System using Machine Learning
Authors:   Department of Electronics and Communication, CBIT, Hyderabad, INDIA, Teja* G. Sai , Sathish P. ,   Department of Electronics and Communication, CBIT, Hyderabad, INDIA.
Published: July 2020

Internet of Things (IoT) allows connections among various devices using the internet with the ability to gather and exchange data. IoT has various connecting protocols like HTTPS, MQTT, CoAP, SMCP, etc. A lightweight protocol of all these protocols is the Message Queuing Telemetry Transport (MQTT) protocol. Agriculture is the backbone of India it plays a significant role in the growth of the economics of the country. The majority of the population in India focused on developing a good yield of the crop at their available space which is leading to the development of various greenhouse and smart farming methods. The technology developments will be enabling to design and develop a simple intelligent system for smart farming and maintaining the greenhouse environment. The proposed system is designed using an ARM Cortex processor with the other supporting peripherals for monitoring and constantly updating and controlling environmental parameter values to achieve optimal growth and yield of plants. In this paper, the proposed system consists of several sensors for measuring different parameters including temperature, humidity, soil moisture, air pressure, and fertilizer content. Further, the obtained data is sent to the cloud by using IoT based ThingSpeak with the secured MQTT protocol to monitor the parameters. An efficient Machine Learning algorithm is developed to predict the parameters like soil moisture, fertilizer content sprayed and weather data i.e., humidity, and temperature. The accuracy obtained using Machine Learning algorithm i.e. Decision Tree method is 97%.
Covid-19 Impact: Indonesia Tourism in New Normal Era
Authors:   S. E., M. Si. M., Assistant Professor, National University, Jakarta, Indonesia., Guridno Dr. Eddy , Guridno Aberar ,   M. AP., Secretary of Professional Development Board, National University, Jakarta, Indonesia.
Published: July 2020

This study examines the problem of the impact of Covid-19 on the Tourism Industry in the New Normal Era, which is a previously unusual or unfamiliar situation which is then made into a standard of habit or expectation. This research is expected to be able to further explain the impact of Pandemic Covid-19 on the tourism industry which must recover immediately from the slump in Post Covid-19 or in the New Normal Era, able to explain where the tourism industry is going, how governance and how the tourism industry will be able to adapt with the dramatic restructuring of the economic and social order in business and society. The method in this research is a qualitative method with case studies to describe the complete picture of the events under study. Data obtained from various sources, documents, and other written data. The findings of this study explain that all components of the tourism industry both government, hospitality, travel businesses, tourism objects and various other supporting institutions as a whole must be able to have protocols as a standard that must be adhered to in providing services and services in all sectors of the tourism industry. Meanwhile the governance of the tourism industry must be able to optimize marketing strategies by making full use of the various advantages of information communication technology that will be very dominant in all sectors of activity which will thus be able to adapt to various global economic and business restructuring.
A SALA DE AULA INVERTIDA COMO ALTERNATIVA INOVADORA PARA A EDUCAÇÃO BÁSICA
Authors: Andrade Luiz Gustavo da Silva Bispo , Jesus Lucas Antônio Feitosa de , Ferrete Rodrigo Bozi , Santos Ronney Marcos
Published: July 2020

Este artigo trata das metodologias ativas de aprendizagem, especificamente a sala de aula invertida e o que ela pode significar no processo de ensino-aprendizagem. Essa abordagem é conhecida como Flipped Classroom, na qual o aluno tem contato com o conteúdo escolar antes de estar na sala de aula, fazendo uso da internet como recurso de aprendizado. Pautou-se numa pesquisa bibliográfica, seguido de um estudo de caso sobre o uso da metodologia em sala de aula, na qual fizemos a articulação das ideias de respeitados autores que tratam de metodologias ativas e inversão da sala de aula. O trabalho foi desenvolvido em uma escola pública da Rede Estadual de Sergipe, em cinco turmas de Língua Portuguesa da terceira série do Ensino Médio. Através do trabalho desenvolvido, percebemos o interesse dos alunos, quando elogiavam o fato de já irem à aula sabendo o que seria discutido, o que nos fazia ganhar tempo para as discussões, como também para amadurecê-las, elevando o rendimento dos estudantes. Desde 2017, que as notas de redação das turmas, em avaliações internas e externas, cresceram exponencialmente, comprovando mais uma vez a eficácia do método.