bluuebunny/crossref_metadata_2025 huggingface dataset:
Systematic Review of Agile Methodologies for Software Development
Authors: Fotariya Mr. Anuj , Mandge Mr. Omprakash
Published: June 2022

Abstract: With the increase in complexity and innovation in IT products and services, developing them, that to by the shared efforts of team members brings in the need of some standardized development model or approach. Due to several advantages of agile methodologies over the traditional waterfall based models, it is the preferred choice. Many a times, a single agile method is also not enough to meet the current scenario of product development. We therefore propose a Competitor Driven Development (CDD) model, a hybrid agile process model for IT product development by abstracting practices from Extreme Programming (XP) and Feature Driven Reuse Development (FDRD) agile methods. This model is based on self-realizing requirements generation for Product development by keeping an eye watch on competitor’s upcoming launch of the product and market response to it rather than customer explicitly specifying the requirements. This development model can be generally used by the organizations who intend to develop IT product for mass targeted customers rather than an individual or an organization.
Solar Based Smart Corridor System
Authors: Kumbhar Aishwarya J.
Published: June 2022

Abstract: This paper presents a Solar Based Smart Corridor System. The system provides an automated lighting system and charging circuit. This detection is based on the motion sensor. The whole system is automated by ESP32 microcontroller. Admin can control the lighting system remotely as the controller has a wi-fi module. The goal of a microcontroller is to interface with sub-systemsand provide suitable decisions for efficient working of the system. The system will use solar energy from solar panels to perform its work. In the absence or failure of it, the system will work on a battery which is charged with the help of solar power. In failure of these both the system will work on traditional state electricity supply. This system is made to work on hybrid mode of power supply. To get this system to work efficiently, we have prepared a set of rules. So that entire system will work according to the algorithm developed. So this system uses eco-friendly energy sources with good efficiency. Also, as the system is robust, scaling of the system based on the need of energy required is relatively easy
Apple Leaf Diseases Classification Using CNN with Transfer Learning
Authors: Charan Merugu Sai , Abrar Mohammed , Devi Bejjam Vasundhara
Published: June 2022

Abstract: The Foliar diseases of the apple trees commonly reduce the crop Yield and photosynthesis which affects their productivity. Diagnosing foliar damage is not easy if there are no distinct patterns that would be fungal fruiting bodies it will. spread to the rest of the crops. The foliar disease of the apple trees is carried out due to biotic and abiotic causes, some of the biotic causes of foliar damage are - Bacterial Disease, Fungal Diseases, Viral Diseases, Insects, and Mites That Damage Foliage. some of the Abiotic causes are - Iron Chlorosis, Misapplied Herbicide, and Winter Desiccation of Evergreens. Traditional approaches rely on visual inspection by an expert and biological examination is the second choice .these approaches are time-consuming and expensive. we use machine learning methods to classify the disease in apple trees. we use some pre-trained CNN models to extract features from the dataset, we applied the CNN model and compared them with Pre-trained Models, and we achieve accuracies of over 93% with CNN, among the Models We achieved 92% with the Inception V3 model,62% with VGG16, 63% with VGG19.
Fashion Recommendation System Using Machine Learning
Authors: Singh Anjali
Published: June 2022

Abstract: Lately, the business and dress have shown quick improvement in design. An online business website with a wide scope of choices requires a decent method for sending, sort, and successfully convey items and data to clients. Online display is a program that is utilized to feature and sell clothing at closeout, paying little heed to identity, orientation, or different qualities. Individuals can join online to become individuals, and everybody can send an advanced duplicate of their work by classification. They can organize their drawings at sell off or at assigned costs. Every client can set up their own store to get their number one plans and access them with next to no issues. Picture based directing frameworks (FRSs) draw in an ever-increasing number of individuals to quick design retailers since it permits shoppers to shop. With the progression of innovation, the best-in-class innovation offers numerous amazing open doors for picture handling, investigation, sequencing, and detachment. In spite of the numerous open doors, the quantity of investigations on this theme is little. Potential investigations won't think about the plan of the innovation and the separating strategies. As the creators know, this is the primary point in the exploration of the new plan of the drawing framework and the strategy for separating. Moreover, this audit inspects the different potential ways that can be executed in the future to give a model. This article will help specialists, researchers, and professionals intrigued by AI, PC vision, and dress deals to figure out the idea of various advising frameworks.
Review of Image Recognition from Image Repository
Authors: Thakur Manish Kumar , Gondkar Raju Ramakrishna
Published: June 2022

Abstract: The work mainly focuses on the need of building a hybrid model by combining the different available method and techniques used for features extraction, detection, and matching. The enhanced model developed is used to identify the objects based on shape. The features are extracted from universally accepted images considered as candidate object. Number of works on image extraction has pointed out the difficulties in extracting the needed image. The paper highlights the shortfalls and the need to address the shortfalls. The review conducted provides the research gap in the industry and various directions the work is heading
Review on Change the Properties of Concrete by Adding Rice Husk Ash and Metakaolin
Authors: Thakur Shivani
Published: June 2022

Abstract: In this study the influence of partial relief of Ordinary Portland cement by Metakaolin and Rice Husk Ash were delved. In the last decade the use of supplementary bonding accoutrements has come an integral part of high strength and high performance concrete blend design. Rice hull ash is a by- product material attained from the controlled combustion of rice hull which consists of non-crystalline silicon dioxidewith high specific face area and high pozzolanic reactivity. Metakaolin helps to reduce the quantum of calcium hydroxide, therefore performing in stronger and durable concrete. OPC was replaced with these mineral admixtures at 2, 4, 6 and 8% by weight. 0% relief served as the control. Compressive Strength test was carried out on hardened 150 mm concrete cells after at 7 and 28 days curing in water. Compression strength test confirms its felicity as a partial relief mineral amalgamation.
Crime Prediction and Analysis
Authors: Gajendra Amshu S , S Aruna , R Malini
Published: June 2022

Abstract: Crimes are treacherous social problems which are faced worldwide. It is the most serious and predominant issue of our society. It affects various key features bound to the society and an individual’s life like the quality of life, reputation, economic growth and societal safety. With the advancement of technology there is an enormous growth in the crime rate. There arelaws that have been enforced to take preventive measures but there is a need for advanced approaches for protecting the society and the individuals in the society. Hence analyzing of crime helps in detecting the patterns and trends in crime. The real time crime predictions will be a helping hand to reduce crime rate. Various visualization approaches and algorithms are used in this study to anticipate the distribution of crime in a given area. This paper's pre-processed dataset was obtained from Kaggle. After that, the system is trained using the ARIMA model. The next step is Visualization of data after which the result is predicted after analyzing the data with many machine learning calculations and modules.
Analysis and Design of Cold-Formed Z Purlins
Authors: Shambharkar Rashmi
Published: June 2022

Abstract: Structures built by cold-formed segments of primary members secondary members and roof panels provide a different solution for a great variety of areas such as housing, storage, education, etc The design of cold-formed sections has obvious complexity in view of the buckling of sections vis-à-vis stress in the compression element, especially in flexure. In this study, effective section properties of the Z section are calculated for a wide range of configurations with different b/t ratios for flange subjected to maximum allowable stress. The section properties are being used to develop the optimum section configurations for constructing a structure in different regions. . The study gives different formulae for quick assessment of parameters and also presents simple design tools and a few standard cold-formed sections having similar configuration but for thickness to be used for residential or community shelters for different zones. Recourse is made to compare the results with similar studies using AISI code and compare the results of lapped purlin and purlin without laps design. The whole course is mainly focused on analyzing and designing cold-formed section purlin.
Detectsy: A System for Detecting Language from the Text, Images, and Audio Files
Authors: Menon Riya
Published: June 2022

Abstract— Language detection is a natural language processing task where we need to identify the language of a text or document. As a human, we can easily detect the languages we know. However, it is not possible for an individual to identify many languages. This is where the language identification task can be used. The proposed solution is a complete system that detects language from the text, images, and audio files. Language identification task from text is carried out by training a Multinomial Naive Bayes classifier model. In the case of image and audio inputs, Python libraries are used to achieve the goal of language detection.
Creative Cooperation
Authors: Xudoshukirovich Bobojanov Sharipboy
Published: June 2022

Annotation: This article reflects the Uzbek folk baxshi and baxshi traditions, the art of badiha, and the relationship between baxshi. The article describes in detail the creative cooperation between Bakhshi and Bola Bakhshi and Qadir Bakhshi.
Batasan Tanggungjawab Notaris Terhadap Akta Autentik Yang Dibuatnya
Authors: Ardiansyah Erlan , Saleh Mohammad , Rachman Rahmia
Published: June 2022

This research examine the legal consequences of a sale and purchase deed canceled by the court on buyers who have good faith. This research purpose to analyze and criticize the PPAT responsibilitie of the land deed whose deed was canceled by the court as well as legal protection for buyers with good intentions as a result of the sale and purchase. This research uses a normative juridical research method, which is carried out by examining legal materials, such as research on positive law. This research uses three legal approaches, namely the legal approach, the conceptual approach and the case approach. The legal materials used in this research are primary legal materials, secondary legal materials and tertiary materials. Analysis of legal materials is carried out by interpreting all laws and regulations. This research concludes that PPAT can be held accountable individually and legally. Legal responsibilities are in the form of civil and administrative responsibilities. PPAT civil liability can be held accountable for returning the status of ownership rights in administrative responsibility in accordance with the PPAT Code of Ethics may be imposed in the form of reprimands, warnings, temporary dismissals from members as contained in article 7 paragraph (1) of the Profession Code of Ethics PPAT
Abstrak
Kewenangan Notaris dalam membuat akta autentik sebanding dengan tanggungjawabnya, karena pertanggungjawaban tersebut terus melekat kepada notaris meskipun notaris tersebut sudah pensiun. Namun, adakalanya notaris khilaf dan membuat kesalahan dalam membuat akta autentik baik yang disengaja maupun yang tidak disengaja. Apabila hal tersebut terjadi dan dikemudian hari ternyata karena perbuatan notaris tersebut menimbulkan kerugian kepada para pihak, apakah notaris wajib mempertanggungjawabkan hal tersebut? Sejauh mana batasan tanggung jawab notaris?. Penelitian ini menggunakan metode Yuridis Empiris. Hasil dari penelitian ini apabila Notaris membuat kesalahan dalam membuat akta autentik sehingga merugikan orang lain, sepanjang pihak yang dirugikan dapat membuktikan kesalahan itu akibat kelalaian maupun kesengajaan Notaris, maka Notaris dapat dimintakan pertanggungjawaban dari sudut pandang keperdataan yakni dengan membayar ganti rugi, selanjutnya pertanggung jawaban administrasi apabila Notaris tersebut terbukti melakukan maka dapat dikenakan sanksi berupa peringatan tertulis, pemberhentian sementara, pemberhentian dengan hormat dan pemberhentian dengan tidak hormat, sedangkan dari sudut pandang hukum pidana apabila Notaris terbukti sengaja atau disadari membuat atau bekerja sama dan menandatangani suatu akta palsu maka dikenakan pidana penyertaan pemalsuan akta.
EVALUATION OF WEB INTERPRETATION ISSUES AND NAVIGATION TECHNIQUES IN FACEBOOK AMONG VISUALLY IMPAIRED USERS
Authors: Ramayah Bavani , Jaafar Azizah
Published: June 2022

Facebook is an important communication medium among all of us. While Facebook provides an effective way for people to communicate online, it also creates challenges for people with blindness. This causes frustration among visually impaired users who are not able to participate in web interaction. The content arrangement of the Facebook page is the main barrier for Visually Impaired users. Therefore, a detail study is needed to explore the interpretation issue in Facebook. This study aimed to examine visually impaired users’ navigation techniques and the reason of having interpretation issues in Facebook. For the comparison purpose, both observation and analysis were based on visually impaired users’ navigation activities in the desktop version (represents complex layout) and mobile version (represents non-complex layout) of Facebook. Cognitive Walkthrough (CW) and spectrum was used to observe and analyse visually impaired users’ navigation activities during experimental session. This study revealed that visually impaired users overcome their interpretation issues in complex layout by adapting multiple navigation techniques compare to non-complex layout. This study also discovered that information scent has influenced visually impaired users' navigation method. This become the main cause of web interpretation issues in Facebook since the content arrangement does not consistent with their navigation method.
GAME REQUIREMENTS GATHERING AMONG HOSPITALISED PAEDIATRIC CANCER PATIENTS: A THEMATIC ANALYSIS
Authors: Nordin A. Imran , Hamzah Irna Hamil , Rasid Nadhirah , Baharin Hanif , Nohuddin Puteri Nor Ellyza , Alias Hamidah , Mohamed Hafsah Nor Hazla , Abdul Kadir Nor Ba'yah , Mohammad Yatim Maizatul Hayati , Kassim Mohd Yazid
Published: June 2022

This paper presents a study that analyzes hospitalized pediatric cancer patients' routines and activities to inform the game design to be used for the development of a digital game to empower them. This study focuses on discovering patients' experiences while being hospitalized. The patients' activities throughout their hospital stay are recorded through non-participatory observations strategy and their experiences inward are gathered through interview sessions with their parents or guardians who have been nursing them during their entire stay in the hospital. The findings suggest that the patients' experiences are divided into two main themes, namely positive and negative affect. These two themes are depending on the patients' treatment phases: before, during and after receiving medical treatments. These findings are crucial to being translated into design principles to inform game design. It is important to ensure that the digital game for pediatric cancer patients is designed properly to ensure its suitability to be played by them. The ability to understand the actual routines and experiences in the hospital would help designers and developers of digital games to develop a digital intervention to empower pediatric cancer patients while being hospitalized
THE NEW METHODOLOGY FOR VEHICULAR NETWORK WITH FUZZY TIME WINDOWS
Authors: Kantawong Krittika , Pravesjit Sakkayaphop , Chaisricharoen Roungsan
Published: June 2022

This work proposes the new methodology for the vehicular network with fuzzy time windows. The Fuzzy technique is applied to produce an initial population and then the evolutionary algorithm is employed to improve the solution. In this work, the inter-route crossover, intra-route mutation, elitism strategy, and onlooker bee probability selection method were enhanced in the original processes of the evolutionary algorithm. The proposed algorithm is tested on 56 datasets of Solomon. The results from the proposed algorithm are shown in comparison with other algorithms in the literature. The findings from the computational results are very inspiring, it shows that the algorithm is very competitive. Comparing with the algorithm in the literature, the proposed algorithm obtains the best solution in terms of the coefficient of variation values for almost 40 instances from the 56 problem instances. In addition, the information regarding the p-value was resolved by the Wilcoxon signed-rank test for the considered testing instances that display statistically superior performance at the 95% significance level (Î± = 0.05) on comparing algorithms.
EVOLUTIONARY COMBINATORIAL OPTIMIZATION FOR WORD EMBEDDING (ECOWE) IN SENTIMENT CLASSIFICATION
Authors: Gunasegaran Thineswaran , Cheah Yu-N
Published: June 2022

Word embedding is widely used in various natural language processing (NLP) tasks, especially sentiment classification. Huge computational costs for training new embeddings from scratch have made pretrained word embeddings such as Word2Vec and Glove popular for reuse of word vectors. Inadequacy of a single embedding necessitated newer techniques to combine two embeddings. However, the combined embeddings proposed in existing works are static and only provide a one-size-fits-all solution regardless of the problem and dataset at hand. Optimization is a more promising technique to overcome the limitations of simplistic techniques in existing works related to combined word embeddings because optimization provides unique and optimal solutions according to the problem and dataset at hand. In this paper, a new genetic algorithm based combinatorial optimization algorithm called Evolutionary Combinatorial Optimization for Word Embedding (ECOWE) is proposed to produce combinations of word embeddings, which yield optimal accuracy for the specific sentiment classification dataset that is used. Results show that absolute percentages of improvement ranging from 1.7% to 12.9%, averaging around 5.5% and relative percentages of improvement ranging from 2.4% to 19.5%, averaging around 8.1% have been achieved over the benchmark model accuracy values for all datasets. The ECOWE accuracy values for all datasets have also been found to be statistically significant compared to benchmark accuracy values with a z-score of -2.2014 using two-tailed Wilcoxon signed rank test with 5% significance level.
POWER CONDITIONING OF SOLAR PHOTO VOLTAIC, BATTERY WITH FUEL CELL UNDER DYNAMIC SWITCHING OF LOADS
Authors: Dharavah Ravi , Raglend I. Jacob
Published: June 2022

The renewable sources integration with the DC micro grid is playing vital role in the current distribution system for providing the necessary clean power. The available of abundant renewable sources can be integrated through the DC link medium. The intermittent nature of renewable sources and dynamic switching of loads affects the quality of supply and DC link voltage respectively. It may fails to supply the power continuously. Reliability of power supply can be achieved with the use of integration of storage system. Here, the solar photovoltaic (SPV) array is fed with battery storage, fuel cell through the DC link medium. Utilizing SPV array maximum power is tracked using intelligent controller based maximum power point tracking (MPPT) technique. The battery storage with the DC link integration made through the bi-directional DC-DC converter with the help of the battery charge controller. Fuel cell is used as a base source and it’s fed with the DC link system. Finally, the simulation of SPV array, battery storage with fuel cell integration is performed under dynamic switching of loads. The variations in the source and switching of load performance are simulated in the MATLAB/Simulation software.
PREDICTION OF CYCLONE USING KALMAN SPATIO TEMPORAL AND TWO DIMENSIONAL DEEP LEARNING MODEL
Authors: Rajesh K. , Ramaswamy V. , Kannan K.
Published: June 2022

Cyclone Classification and Prediction models rely on large intensity based on the maximum speed of the wind, along with the classification of intensity. The computational constraints blended with the formation of those intensities, cyclone classification and prediction firmly depreciate the full range of optimal features required for classification and hence accurate representation is less possible. Keeping this point, our study inspects the potential of Spatio-temporal features using a machine learning algorithm as an alternative to the current study of cyclones. This method is called, Spatio-Temporal Kalman Momentum and Two Dimensional Deep Learning (SKM-2DDP) for cyclone classification and prediction. To start with, pre-processing is performed by applying the Kalman Momentum Conservation Filter mechanism based on the design of the Dvorak technique to obtain optimal estimates of state variables and reduce the computational burden involved to remove noise from input cyclone images. With the resultant denoised input cyclone images, Spatio Temporal Feature Extraction is performed. Features obtained from the inherent intrinsic properties of pre-processed cyclone images of several weather conditions result in successful classification. Followed by pre-processing, in this work, features constituting both pixel-wise intensities over time and the directional length are being considered. The dependency of autocorrelation with each pixel’s intensities over time and two temporal features are helped for coarse classification of weather conditions according to their visual effects. Finally, with the inherent intrinsic features extracted, a Two Dimensional Deep Learning model is utilized to foretell the cyclone intensity. Experimental evaluation of the proposed SKM-2DDP method is accomplished using images of cyclone dataset with many factors just as peak signal to noise ratio, prediction accuracy, prediction time and false-positive rate. Our own selves have considered with several cyclone images acquired from two different cyclone image datasets namely OCKHI_DEC2017 and VARDAH_DEC2016.
STUDENTS’ PREFERENCES OF LEARNING MATERIALS DURING UNPRECEDENTED ONLINE LEARNING DUE TO COVID-19
Authors: Rosli ‘Atifah Hanim , Abdul Wahab Norshahriah , Alsagoff Syed Nasir , Mohd Isa Mohd Rizal , Mohd Shukran ‘Afizi
Published: June 2022

Teaching and learning processes in higher education have been affected due to the COVID-19 pandemic. Face-to face learning has been transitioned to online learning. This study explored student preferences for online materials during unprecedented online learning due to COVID-19. Through an online questionnaire, quantitative data was collected from 104 students from the Department of Computer Science, Faculty of Defence and Science Technology. The factors focused on in analysing the student’s preferences in online learning material include the layout, and multimedia analytics approach. The results present how multimedia analytics such as video, audio, graphic, and animation in online learning material play a significant role in the cognitive engagement and student’s motivation in online learning. Also, respondents preferred online learning materials with element of multimedia such as video and audio, rather than text only. This study presents suggestions on how to enhance online learning materials to improve online learning.
HOW POPULAR IS SOCIAL MEDIA IMAGE GRATIFICATION AS A RESEARCH THEME IN TOP JOURNALS?
Authors: Che Ilias Irma Syarlina , Ramli Suzaimah , Wook Muslihah , Hasbullahi Nor Asiakin
Published: June 2022

Understanding why people use social media provides an insight into the nature of behaviours in social networking where sharing images or photos and like other users’ posts are some preferred social media user’s behaviours. Theory of Uses and Gratifications posits that the audience actively chooses a type of media that suits their needs. Motivations are explained by the questions of why users use social media and what gratifications they derive from their use, and whether they prefer to use images rather than texts or even videos. Prior studies found that there are distinctly different gratifications resulting from the use of images in social media. This research paper hereby explores a thematic review of the top journals regarding the motives of image use in social media from the year 2017 to 2020. The strategy of the research was to investigate through a comprehensive number of review articles on the images used in social media and the result was then analysed. From the literature, the findings of the code-to-document report have highlighted several research patterns or themes in the motives of image use in social media. The results benefit the future direction of later research and narrow the gap between research solutions on image use in social media in the context of gratifications.
PREDICTIVE ANALYSIS OF HEART DISEASES WITH MACHINE LEARNING APPROACHES
Authors: TR Ramesh , Lilhore Umesh Kumar , M Poongodi , Simaiya Sarita , Kaur Amandeep , Hamdi Mounir
Published: June 2022

Machine Learning (ML) is used in healthcare sectors worldwide. ML methods help in the protection of heart diseases, locomotor disorders in the medical data set. The discovery of such essential data helps researchers gain valuable insight into how to utilize their diagnosis and treatment for a particular patient. Researchers use various Machine Learning methods to examine massive amounts of complex healthcare data, which aids healthcare professionals in predicting diseases. In this research, we are using an online UCI dataset with 303 rows and 76 properties. Approximately 14 of these 76 properties are selected for testing, which is necessary to validate the performances of different methods. The isolation forest approach uses the data set’s most essential qualities and metrics to standardize the information for better precision. This analysis is based on supervised learning methods, i.e., Naive Bayes, SVM, Logistic regression, Decision Tree Classifier, Random Forest, and K- Nearest Neighbor. The experimental results demonstrate the strength of KNN with eight neighbours order to test the effectiveness, sensitivity, precision, and accuracy, F1-score; as compared to other methods, i.e., Naive Bayes, SVM (Linear Kernel), Decision Tree Classifier with 4 or 18 features, and Random Forest classifiers.
DETECTION OF BIO ELEMENTS PRESENT IN HUMAN BIOLOGICAL TISSUE-TOOTH AND ITS USAGE FOR ELEMENT BIOMETRIC AUTHENTICATION
Authors: Ambiga N. , Nagarajan A.
Published: June 2022

Biometric authentication system uses some technique that measures the physical and biological characteristics of human to identify individuals and thus provide security to a system against fraud or intrusion. Common biometric authentication processes are vulnerable and possibility for imitation. Teeth are an important biological entity that plays a major role in forensic research to identify an individual whom cannot be identified visually. There are different algorithms used in biometric authentication. This paper proposes a unique method to recognize the human teeth by using a combination of Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) to extract significant features and an improved version of Binary Particle Swarm Optimization (BPSO) for feature selection is employed to search the feature vector space in order to obtain optimal feature subset to increase the performance rate. A combination of image pre-processing techniques like background removal, gamma intensity correction and Laplacian of Gaussian (LoG) filter are used to help in correct feature extraction. Using the shift invariance property of DFT, a circular feature extraction technique and the energy compaction property of DCT, a circular sector feature extraction method is presented. Experimental results on IvisionLab/dental-image standard database are shown which exhibit promising performance of the teeth recognition system.
AN IMPROVED SECURITY FRAMEWORK IN HEALTH CARE USING HYBRID COMPUTING
Authors: Devi B. S. Kiruthika , Vijayakumar V , Suseela G , Kavin B. Prabhu , Sivaramakrishnan S. , Rodrigues Joel J. P. C.
Published: June 2022

Cloud computing is a new category of service that gives each customer access to a large-scale computing network. Since most cloud computing platforms provide services to a large number of people who aren't considered to be trustworthy, various cyber attacks may potentially target them. As a result, a cloud computing system must provide a security monitoring mechanism to protect the Virtual Machine from attacks. In this case, there is a tradeoff between the security level of the security system and its performance. If we need strong security, we'll need more laws or patterns, which means we'll need a lot more computational resources in proportion to the strength of security. As a result of the declining number of resources allocated to customers, we will add a new protection scheme in cloud environments to the VM in this report. Hence, the proposed system Proposed Elliptic curve – Diffie Hellman EC(DH)2 Algorithm is designed and deployed to improve the security in healthcare domain using hybrid computing. The most popular and recent technologies such as cloud computing and fog computing are integrated to explore data movement and stable medical data health-care information. Based on the experimental results, it is inferred that the proposed system offers high security and less operating time while handling the data making its deployment in the healthcare domain.
INTELLIGENT DEEP LEARNING BASED PREDICTIVE MODEL FOR CORONARY HEART DISEASE AND CHRONIC KIDNEY DISEASE ON PEOPLE WITH DIABETES MELLITUS
Authors: Mohamed A. Thasil , Santhoshkumar Sundar , Varadarajan Vijayakumar
Published: June 2022

Presently, process analytics extracts the knowledge from the past data to explore, monitor, and improve the processes. The recently developed deep learning (DL) models find it helpful to analyse medical data and make decisions. Among various diseases, type 2 diabetes mellitus (T2DM) becomes a widespread disease over the globe and it leads to severe outcomes. Chronic kidney disease (CKD) and coronary heart disease (CHD) are the major illness occurred in people with T2DM. Since the earlier prediction of the risk factors related to CKD and CHD on T2DM persons is necessary, this study focuses on the design of intelligent feature selection with deep learning based risk factor prediction (IFS-DLRFP) model. The proposed IFS-DLRFP technique intends to determine the early warning to the patients with T2DM to develop CKD or CHD. In addition, the IFS-DLRFP technique includes the design of fruit fly optimization algorithm (FFOA) based feature selection technique to choose an optimal set of features. Moreover, firefly optimization with gated recurrent unit (FF-GRU) based classification technique is derived to allocate appropriate class labels to the input data. The FF-GRU technique performs the hyperparameter tuning process using FF technique. In order to ensure the better performance of the IFS-DLRFP technique, a wide range of simulations take place on benchmark datasets and the simulation outcomes reported the supremacy of the IFS-DLRFP approach over the recent techniques.
Panorama de la automedicación en estudiantes de educación superior: una mirada global
Authors: Martinez-Rojas Sandra Milena , Ruiz-Roa Silvia Liliana , Sánchez-Pérez Duglas Gerardo , Jiménez Castellanos María Natalia
Published: June 2022

Introducción: La automedicación es una práctica que llevan a cabo especialmente los jóvenes universitarios, al percibirse inmunes a enfermedades, sin tener en cuenta los efectos sobre el uso de fármacos sin prescripción. Objetivo: Analizar los hallazgos de la literatura existente sobre la automedicación en estudiantes de educación superior. Materiales y métodos: Se empleó la metodología Scoping Review, utilizando los términos DeCS y MeSH en español, inglés y portugués en cuanto a: “automedicación”, “estudiantes”, “educación superior”, “COVID-19”. A continuación, se articularon las ecuaciones de búsqueda empleando los operadores booleanos AND y OR, en las bases de datos: IBECS, Scielo, BVS, Google Scholar, LILACS, Science Direct y Pubmed. Al respecto se limitó el tiempo de publicación entre 2016 – 2021. Resultados: Se obtuvieron 23 artículos, consolidando seis núcleos temáticos: motivos para automedicarse; grupos farmacológicos que se consumen; fuentes de recomendación; factores sociodemográficos; semestres y programas académicos; y, conocimientos sobre los riesgos de la automedicación. Los analgésicos son los medicamentos que más se consumen, siendo el principal motivo de uso el dolor de cabeza. Los farmacéuticos junto con los medios de comunicación suelen ser fuentes de recomendación. Predominaron bajos niveles de conocimiento acerca de los riesgos de la automedicación. Conclusiones: La literatura indica que este problema de salud pública es cada vez mayor y evidencia la necesidad de abordarlo con estrategias eficaces.
50 Años de Formación Profesional en Enfermería con Excelencia Académica y Proyección Social
Authors: Bautista-Rodríguez Luz Marina
Published: June 2022

El Programa de Enfermería de la Universidad Francisco de Paula Santander (UFPS) cumple 50 años de creación; celebrar un nuevo aniversario es motivo de orgullo, reflexión y reconocimiento de la senda recorrida, que ha permitido el posicionamiento del programa y de los graduados a nivel regional, nacional e internacional.

Los logros y avances del programa inician desde que la Universidad Francisco de Paula Santander en rectoría del Dr. José Luis Acero Jordán (QEPD), mediante análisis previos y estudio de los diferentes sectores de salud en el Norte de Santander, creyó conveniente orientar mediante el Plan de Desarrollo 1969 – 1971 la creación de una carrera en el área de la salud; considerando Enfermería como una necesidad apremiante, ante el contexto de crecimiento de las Instituciones Prestadoras del Servicio de Salud, como la antigua Clínica del Seguro Social, Clínica San Antonio, Hospital Amelia, Hospital San Juan de Dios y los Puestos de salud existentes, que atendían a la población del departamento Norte de Santander.
Effect of different doses of dexmedetomidine on the median effective concentration of propofol during gastrointestinal endoscopy：a randomized controlled trial
Authors: Chen Hai-yan , Deng Fang , Tang Shu-heng , Liu Wen , Yang Hua , Song Jin-Chao
Published: June 2022

Background: Dexmedetomidine could be an ideal adjuvant to propofol
during gastrointestinal endoscopy because it provides both analgesia and
sedation without respiratory depression. This study investigates the
effect of different doses of dexmedetomidine on the median effective
concentration of propofol during gastrointestinal endoscopy. Methods: 90
adult patients were randomly assigned to Group Control , Group DEX0.5
(0.5 μg/kg dexmedetomidine), or Group DEX1.0 (1.0 μg/kg dexmedetomidine)
. Anaesthesia during endoscopy was implemented by plasma
target-controlled infusion (TCI) of propofol with different doses of
dexmedetomidine. TCI concentration of the first patient for each group
was 2.5 μg/ml and the consecutive adjacent concentration gradient was
0.5 μg/mL. EC50 of TCI propofol for gastrointestinal endoscopy was
determined by using the modified Dixon’s up-and-down method.
Cardiovascular variables were also measured. Results: EC50 of TCI
propofol and 95% confidence interval (CI) for gastrointestinal
endoscopy were, 3.77 (3.48-4.09), 2.51 (2.27-2.78) and 2.10 (1.90-2.33)
μg/mL in Group Control, Group DEX0.5 and Group DEX1.0. The average
percent change from baseline in HR was 2.8 (8.9), -7.4 (7.7) and -10.5
(8.8) (P＜0.001), and the average percent change from baseline in MAP
was -10.6 [-24.7; 3.5], -9.5 [-29.2; 11.4] and -4.0 [-27.3;
15.5] (P = 0.034) in Group Control, Group DEX0.5 and Group DEX1.0,
respectively. Conclusions: Dexmedetomidine reduced the EC50 of TCI
propofol. A 0.5-1 μg/kg dexmedetomidine caused a decrease in HR without
bradycardia. The decrease in dosage of propofol with increasing doses of
dexmedetomidine caused more stable MAP. Dexmedetomidine is an ideal
adjuvant drug to propofol during gastrointestinal endoscopy.
Highly selective water-compatible molecularly imprinted polymers for benzophenone-4
Authors: Pesic Milos , Krstic Jugoslav , Verbic Tatjana
Published: June 2022

Molecularly imprinting technology was applied for preparing selective sorbents for benzophenone-4 (BP4), an organic UV filter used in sunscreens and cosmetics. Several imprinted polymers were prepared by bulk polymerization, using BP4 as template. Combination of stability (mechanical and chemical), selectivity and robustness of the imprinted polymers with BP4 properties resulted in a successful imprinting process (imprinting factors in range 1.05?2.60). The prepared polymers were characterised by infrared spectroscopy, elemental analysis, conductometric titrations and nitrogen physisorption at 77 K. Adsorption capacities and selectivity towards 7 other organic UV filters (benzophenone-3, benzophenone-8, homosalate, butyl methoxydibenzoylmethane, ethyl hexyl salicylate, ethyl hexyl p-dimethylamino benzoate and ethyl hexyl p-methoxycinnamate) were determined, proving high adsorption capacity and high selectivity for BP4 binding. The highest adsorption capacity was observed for 4-vinylpyridine/ethylene glycol dimethacrylate co-polymer prepared in dimethyl sulfoxide (1.108 mmol g-1). The imprinted polymer with the highest binding capacity was applied to solid phase extraction of BP4 from aqueous solutions with 98.5 % efficiency.
Gondolatok az infokommunikációs hálózati szolgáltatásokról
Authors: Gulyás Attila
Published: June 2022

Az információs társadalom evolúciós vívmányai közül talán a legérdekfeszítőbb a mindannyiunkat körülvevő – ma még rétegesen létező – világ összekapcsolódásainak technológiai-műszaki oldala, mély integráltságú hálózatos kialakítása. Műszaki értelemben az infokommunikációs hálózatok is magas skálázhatósági szintű, többcélú rendszerek, amelyek alap- és funkcionális szolgáltatásaikkal megkönnyítik a katonai szervezetek és a polgári vállalkozások feladatvégzését. E tudományos közleményben a szerző röviden bemutatja az infokommunikációs hálózatok egyes szolgáltatáselemeit.
A bolygók radarcsillagászati vizsgálata
Authors: Novoszáth Péter
Published: June 2022

A radarcsillagászat a közeli égitestek megfigyelésének technikája, a mikrohullámok céltárgyakról történő visszaverődésének elemzése. Ezt a kutatási módszert több mint hét évtizede alkalmazzák. Míg a rádiócsillagászat passzív, a radarcsillagászat aktív tevékenységet jelent. A korszerű létesítmények, valamint az adó-vevő teljesítmények növekedése egyre jelentősebb megfigyelési lehetőségeket kínál.
A nagyhatalmak vegyiharcanyag-fejlesztései a két világháború között
Authors: Dauner Bernát
Published: June 2022

Az első világháborút követően, a gázháború tapasztalatai nyomán a nagyhatalmak igyekeztek fokozni a vegyi harcanyaggyártást. Ezek az államok olyan speciális létesítményeket építettek, ahol kipróbálták a vegyi harcanyagokat. Az ellenség vegyi harcanyagaitól való félelem miatt a haderőkben megindult a gázvédelem kiépítése. A nagyhatalmak a haderők irányításával kutatócsoportokat hoztak létre, amelyek feladata új harcgázok kifejlesztése volt.
Dualitites in quantum field theory from string theory
Authors:   , Akhond Mohammad R.
Published: June 2022

Quantum field theory (QFT), is a powerful framework to study diverse phenomena in physics. The range of topics includes the interactions of elementary particles, the continuum limit of condensed matter systems defined on a lattice, models of the expanding universe, as well as quantum gravity. Despite its enormous breadth of applications, it is still quite poorly understood. From a pragmatic point of view, a generic QFT is well understood in the per-turbative regime, where one has a small expansion parameter or coupling constant. That we have a satisfactory understanding of QFTs in the weakly coupled regime, is highlighted by the fact that we have a single formalism, namely feynman diagrams, that can be applied to any weakly coupled theory. Conversely, there is no universal framework to understand non-perturbative and strong coupling phenomena. Instead, we have a distinct set of tools, which apply to distinct sets of very special theories, such as those with supersymmetry or topolog-ical theories. From this perspective, to understand the strong coupling dynamics of a QFT, is to develop a unique formalism that can be applied to solve a generic strongly coupled QFT. The reader should be warned that this thesis will not achieve such an ambitious goal. How-ever, it is good to keep this general philosophy in mind, as a broader motivation for some of the work presented. We will provide, instead, a collection of data points for particular sec-tors of strongly coupled QFTs that are under analytic control. One can hope that some day, these data points can provide the foundations for a more systematic and universal approach. From a more formal viewpoint, quantum field theory, as of yet, has no rigorous mathemati-cal basis. This is particularly bothersome, given the deep interconnections between ideas in modern mathematics and those of QFT [1]. The goal of this thesis is to introduce its reader to a few notable examples, where the former issue can be overcome. The unifying theme of all these examples is their relation to brane dynamics in string theory [2]. We will make extensive use of the string theory embedding of the QFTs under consideration, in order to illuminate their strong coupling dynamics.
Modern Approaches to Topological Quantum Error Correction
Authors:   , Parrado Rodríguez Pedro
Published: June 2022

The construction of a large-scale fault-tolerant quantum computer is an outstanding scientiﬁc and technological goal. It holds the promise to allow us to solve a variety of complex problems such as factoring large numbers, quick database search, and the quantum simulation of many-body quantum systems in ﬁelds as diverse as condensed matter, quantum chemistry, and even high-energy physics. Sophisticated theoretical protocols for reliable quantum information processing under imperfect conditions have been de-veloped, when errors aﬀect and corrupt the fragile quantum states during storage and computations. Arguably, the most realistic and promising ap-proach towards practical fault-tolerant quantum computation are topologi-cal quantum error-correcting codes, where quantum information is stored in interacting, topologically ordered 2D or 3D many-body quantum systems. This approach oﬀers the highest known error thresholds, which are already today within reach of the experimental accuracy in state-of-the-art setups. A combination of theoretical and experimental research is needed to store, protect and process fragile quantum information in logical qubits eﬀectively so that they can outperform their constituting physical qubits. Whereas small-scale quantum error correction codes have been implemented, one of the main theoretical challenges remains to develop new and improve existing eﬃcient strategies (so-called decoders) to derive (near-)optimal error cor-rection operations in the presence of experimentally accessible measurement information and realistic noise sources. One main focus of this project is the development and numerical implementation of scalable, eﬃcient decoders to operate topological color codes. Additionally, we study the feasibility of im-plementing quantum error-correcting codes fault-tolerantly in near-term ion traps. To this end, we use realistic modeling of the diﬀerent noise sources, computer simulations, and most modern quantum information approaches to quantum circuitry and noise suppression techniques.
Comparative characteristics of morphofunctional state of organs in black-back herring (Alosa kessleri kessleri) caught in different years
Authors: Grushko Maria Pavlovna , Fedorova Nadezhda Nikolaevna
Published: June 2022

The purpose of the research was to consider pathological characteristics of tissues and organs of black-back herring (Alosa kessleri kessleri) in different years. Results of the comparative analysis of pathohistological changes

in the organs were taken into account, since this method allows revealing pathological changes in herring organs and tissues, and comparative analysis of histomorphological parameters of black back herring in different years allowed determining changes in the degree and level of a pathological process in the course of time. There were studied the matured species of black back herring Alosa kessleri kessleri (Grimm) caught for analysis during the spawning run in the Volga River in 2014 and 2021. Six hundred of histological sections of organs (liver, kidneys, spleen, intestines, and gills) in 37 species were prepared and analyzed. The species selected for the study were 2 and 3 years old. The material was processed by the classical histological methods. Pathomorphological study of black back herring’s organs in different years showed that the studied fish species experienced high stress. There has been found a wide range of pathologies which could be caused by a chronic ingestion of pollutants from the environment. It has been stated that the organs through which pollutants enter were most affected (gills, liver, kidneys). The main manifestations

of a pathological process were microcirculatory disorders, edema, necrosis, inflammation, connective tissue over-growth, epithelial hyperplasia. All the detected pathological changes in fish organs arose due to the modern environment, which is explained by the disturbances resulting from significant changes in aquatic and terrestrial ecosystems
PEMANFAATAN SELASIH DAN SERAI SEBAGAI ANTINYAMUK DEMAM BERDARAH HERBAL DI DESA CINUNUK, KABUPATEN BANDUNG
Authors: Herdiana Yedi , Ferdiansyah Ferry , Runadi Dudi
Published: June 2022

Penyakit Demam Berdarah Dengue merupakan penyakit yang prevalensi tinggi dan dapat menimbulkan kematian. Pencegahan DBD dengan meningkatkan kebersihan lingkungan dan penggunaan anti nyamuk. Pengunaan anti nyamuk yang banyak digunakan adalah anti nyamuk sintetis. Penggunanan anti nyamuk sistetis yang tidak tepat bisa mnyebabkan gannguan kesehatan pada manusia. Warga Desa Cinunuk biasa menggunakan antinyamuk sintesis. Kondisi inilah yang menjadi gagasan penelitian pemanfaatan selasih dan serai sebagai antinyamuk herbal. Hasil yang diperoleh pada pengabdian ini menunjukkan perubahan pemahaman tentang bahaya pemakaian yang tidak tepat dari anti nyamuk sintetis, pemanfaatan tanaman untuk anti nyamuk dan cara pembuatan antinyamuk dengan tehnik pembuatan yang sederhana. Ditunjukkan dengan peningkatan nilai hasil post test dibanding dengan pre test. Nilai postest yang diperoleh adalah 100% diatas nilai diatas 75. Adanya kegiatan penyuluhan dan edukasi dari kader PKK telah memberikan perbaikan dalam pencegahan penyakit demam berdarah. Setelah kegiatan KKN-PPM ini berakhir, diharapkan dapat meningkatkan pengetahuan masyarakat Desa Cinunuk mengenai pemanfaatan selasih dan serai sebagai antinyamuk herbal.