bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptation of Coastal Fishermen in Pacitan Regency Due to Climate Change Through the Sustainable Livelihood Framework Approach
Authors: Choirunnisa Luthfi Alif Dinar , Purwaningsih Yunastiti , Prasetyani Dwi
Published: August 2022

The phenomenon of climate change is one of the events that affect the coastal communities of Pacitan Regency, especially their livelihoods as fishermen. The purpose of this study is to analyze the adaptation activities of fishermen due to climate change that affects fishermen's household income using a sustainable livelihood approach. Determination of respondents through purposive sampling technique, where the total sample is 104 fishermen. This study uses a survey method in the field with fishermen based on several questions through questionnaires submitted to coastal fishermen in the District of Pacitan Regency. Factor analysis and multiple regression were used to analyze the data. The results showed that simultaneously the variables of fishermen's adaptation choices, government adaptation choices, education level, age and experience as fishermen, fishermen's distance to the sea, location of mangrove areas, savings, asset ownership, credit, participation in fisherman group organizations, and ownership of tools. Simultaneous capture has a significant effect on the total income of fishermen. Partially, the variable of fisherman adaptation choice, education level, age, the distance of fishermen when fishing, location of mangrove area, savings, asset ownership, credit, and ownership of fishing gear have a significant and positive effect on the total income level of coastal fishermen in Pacitan Regency, while the experience variable as fishermen have a negative and significant effect on the total income level of coastal fishermen in Pacitan Regency.
The Influence of Motivation upon Performance: A Quantitative Research Conducted Among Software Developers
Authors: Pungan Andrei
Published: August 2022

In a complex and unpredictable business environment that is constantly changing, often the individual performance of software developers directly influences the performance of the entire organization. Thus, the more motivated employees (respectively software developers) are, the results obtained by them are higher, because the achievement of the individual objectives is closely related to the achievement of the organization's objectives. Therefore, this paper aims to study the link between motivating software developers and organizational performance for a multinational company in Romania using Charles Handy’s theory of motivation. Starting from the 4 “E” factors (energy, excitement, effort and expenditure), a quantitative research was carried out by applying a questionnaire among 32 software developers. The questionnaire was made up of Likert-scale questions, so that each software developer could choose the option that seemed most appropriate. The results revealed that there is a strong link between the four motivational factors (e factors) and organizational performance within software developers. Also, for the study of the concepts most often encountered together with motivation, software developers and performance, bibliometric research was carried out.
Through the Shanzhai Lens: Reframing the Transmedial Copying and Remaking of Games
Authors: Austin Hailey J. , Sloan Robin
Published: August 2022

China is one of the fastest growing games markets, housing not only some of the world’s largest video and computer games companies, but also millions of active gamers. From a Western perspective, engagement with China is considered essential to future growth for game developers and publishers, both in terms of inward investment from Chinese publishers and in growing sales with what will become one of the most important markets. However, Western perceptions of copyright, IP, and, copying of games in China can problematise game creators’ and consumers’ views of China. In this paper, we develop a framework for understanding the act of game copying in the West and in China that combines the Chinese concept of shanzhai with developing understandings of the concept “transmedia” and fan-created works. The aim of this framework is to introduce cultural and contextual awareness to our collective understanding of why game copies exist in the West and in China, and how they intersect with existing copyright and IP concerns. Through a case study of the 2018 game Among Us, we demonstrate that the reality of Western and Chinese game ‘copies’ is far more nuanced than is often depicted in Western media.
Issues and Strategies of Localising Sensitive Audiovisual Elements in Game Streaming: A Case Study on Overwatch League (OWL) Chinese Streaming
Authors:   University of Bristol, Chen Dody M.H.
Published: August 2022

This paper is a participant-observer case study of the Overwatch League (OWL) 2021 Chinese streaming. Within the contemporary dynamic and diversified mediascape of China, esports streaming has become increasingly popular (Taylor, 2018; Wohn & Freeman, 2020). Esports streaming allows spectators to watch esports players’ intense competitions in real time and interact through danmu (bullet comments), gift sending systems, or via streaming lotteries (Lee et al., 2019; Abarbanel & Johnson, 2020; Zhang & Cassany, 2020). The Chinese streaming of Overwatch League (OWL), a series of Overwatch (OW) esports tournaments owned by Activision Blizzard, on Bilibili can be considered a game streaming localisation practice which localises audiovisual content from the original English-language streaming source into Chinese and then innovates upon it in the form of a number of local streaming programmes. The OWL Chinese streaming has disclosed many issues and strategies taken toward sensitive elements like game slang, cultural differences, the presence of erotic or violent content, gambling, media accessibility and censorship laws. The analysis of the selected cases in this article extends the current theories dealing with game localisation (e.g. Zhang Xiaochun, 2012; O’Hagan & Mangiron, 2013; Mangiron et al., 2014) into a new layer, dealing with game streaming localisation. The findings suggest the complications of game streaming content, including the controversial impacts of localisation strategies on sensitive elements, cross-media marketing of streaming practices and the participation of various stakeholders (e.g. officials, sponsors, fans) in game streaming localisation.
Tech Otakus Save the World? Gacha, Genshin Impact, and Cybernesis
Authors:   Brunel University, Adams Matthew James
Published: August 2022

With the shift of life online, accelerated by the pandemic, cybernetic conceptions of personhood are becoming increasingly pertinent. The anthropological literature has yet to properly contend with Donna Haraway and Gregory Bateson’s challenges that the person might be best understood as a cybernetic organism. Based on eleven months’ ethnography during COVID-19, conducted in-person in Hong Kong and Korea, and digitally with communities in Taiwan and farther afield, this paper takes up that challenge in an intimate look at the cybernetic formation of personhood through videogames. I focus on the recent output of miHoYo’s Genshin Impact, which has a playerbase in the hundreds of millions. In two contrastive Chinese contexts, Taiwan and Hong Kong, I interrogate the effects of gacha monetisation on personhood. Through the activities in-world, and engagement in internal and adjacent communities, videogame identities become componential to personhood. However, so too do the players become components in the gacha characters, and even in miHoYo, as cybernetic organisms. Given the developers’ explicit ambitions – not least of all in their motto, ‘tech otakus save the world’ – and potential tensions with Mainland regulations, I explore the nascent Chinese metaverse from its present limits. In so doing, I show the significance of this game and its community for the future of all cyber society, and the utility of my conception of ‘cybernesis’ for understanding that future.
MAPPING THE CHATTER: SPATIAL METAPHORS FOR DYNAMIC TOPIC MODELLING OF SOCIAL MEDIA
Authors: Morandini L. , Mohammad A. R. , Sinnott R. O.
Published: August 2022

Abstract. Topic modelling is a branch of Natural Language Processing (NLP) that deals with the discovery of conversation topics in a given document corpus. In social media, this translates into aggregating social media posts, e.g. tweets, into topics of conversation and observing how these topics evolve over time (hence the “dynamic” adjective). Conveying the results of topic modelling can be challenging since the topics often do not lend themselves naturally to meaningful labelling. The volume of real world (global) social media also means that millions of topics can be ongoing at any given time and the relationships between them can involve hundreds of dimensions and relationships that continually emerge. The popularity of topics is itself subject to change over time and reflect the pulse of what is happening in society at large. In this paper, we propose a spatialization technique based on open-source software that reduces the intrinsic complexity of dynamic topic modelling results to familiar topographic objects, namely: ridges, valleys, and peaks. This offers new possibilities for understanding complex relationships that change over time whilst overcoming issues with traditional topic modelling visualisation approaches such as network graphs.
SEA WATER TURBIDITY ANALYSIS FROM SENTINEL-2 IMAGES: ATMOSPHERIC CORRECTION AND BANDS CORRELATION
Authors: Pisanti A. , Magrì S. , Ferrando I. , Federici B.
Published: August 2022

Abstract. Turbidity is a visual property of water, related to the presence of suspended particles in waters. This parameter is measured in different water quality monitoring programmes as it can determine negative environmental effects both on the biotic and abiotic marine ecosystem. Traditional methods, e.g., in situ monitoring, offer high accuracy but provide sparse information in space and time. On the other hand, Earth Observation (EO) techniques have the potential to provide a comprehensive, fast and inexpensive monitoring system to observe the biophysical and biochemical conditions of water bodies. In the present work, a method for seawater turbidity retrieval from Sentinel-2 multispectral optical images, freely available within the EU Copernicus programme, is presented. The study explores different atmospheric correction methods available in open source software (QGIS, GRASS GIS and SNAP), in order to convert Level-1C (L1C) Top-Of-Atmosphere (TOA) images to Level-2A (L2A) Bottom-Of-Atmosphere (BOA), when the latter is not directly available. Once the proper method for atmospheric correction was identified and applied, the correlation between the in situ dataset and the individual bands known to be most sensitive to water turbidity, i.e., blue (B2), green (B3), red (B4) and near infrared (B8 and B8A) bands, were investigated and a linear regression model between selected band values and turbidity was identified.
DIGITAL 3D INVENTORY FOR THE PROMOTION AND CONSERVATION OF THE ARCHITECTURAL HERITAGE
Authors: Quintilla-Castán M. , Martínez-Aranda S. , Agustín-Hernández L.
Published: August 2022

Abstract. Heritage graphic representation combining building spatial location and urban/land planning supports the decision-making of government agencies and simplifies the development of protection and conservation projects. The evolution of web-based open-source representation systems, able to store 3D graphics information and to make it accessible by web platforms, allows to develop novel heritage catalogues which simplify the exchange of information between administrations and citizens. This work is devoted to the creation of the Digital 3D Inventory of the Aragonese Mudéjar Architectural Heritage, a list of 225 buildings with unique architectural elements which are part of the UNESCO World Heritage. We propose a generalized methodology for collecting, store and disseminate friendly 2D geospatial and 3D geometric documentation of the historical buildings, ensuring that valuable information is stored and providing greater graphic and documentary resources than traditional inventories of architectural heritage. The main novelty is creation of a web platform which allows the exploitation of the architectural information through a cartographic webGIS viewer and a 3D environment based on webGL for rendering large point clouds. The proposed web platform enables to delivery 3D content through generic web browsers natively supported by all devices and without installing third-party applications neither downloading massive data files.
MAKING SENSE OF THE NOISE: INTEGRATING MULTIPLE ANALYSES FOR STOP AND TRIP CLASSIFICATION
Authors: Spang R. P. , Pieper K. , Oesterle B. , Brauer M. , Haeger C. , Mümken S. , Gellert P. , Voigt-Antons J.-N.
Published: August 2022

Abstract. Mobility research is mainly concerned with understanding mobility on a higher level, including environmental factors, e.g., measuring the time out of home or tracking revisited places. This requires preprocessing the raw data obtained from GPS sensors, like clustering significant locations and distinguishing these from periods on the go. We introduce a new stop and trip detection algorithm to transform a list of position records into intervals of dwelling and transit. The system is based on geometrical analyses of the signal noise: Imperfect GPS data tends to scatter around an actual dwell position in a star-like pattern, and this imperfection is what we leverage for our classification. The system contains four independent classification methods, comparing different aspects of the geometrical properties of a given trajectory. If available, accelerometer readings can be used to improve the system’s accuracy further. To evaluate the classifier’s performance, we recorded a large dataset containing gold-standard labels and compared the classification results of our system with the results of Scikit Mobility and Moving Pandas. Our Stop Go Classifier outperforms the traditional distance/time-threshold-based systems. The described system is available as free software.
THE STAGA-DATASET: STOP AND TRIP ANNOTATED GPS AND ACCELEROMETER DATA OF EVERYDAY LIFE
Authors: Spang R. P. , Pieper K. , Oesterle B. , Brauer M. , Haeger C. , Mümken S. , Gellert P. , Voigt-Antons J.-N.
Published: August 2022

Abstract. Identifying stops and trips from raw GPS traces is a fundamental preprocessing step for most mobility research applications. Thus, ensuring the excellent accuracy of such systems is of high interest to researchers designing such analysis pipelines. While there are plenty of GPS datasets available, these usually do not provide annotations and thus cannot be used for benchmarking stop/trip classifiers easily. This manuscript introduces a GPS & accelerometer dataset, including accurate stop/trip annotations. It contains 122,808 GPS samples as one continuous trajectory, spanning over 126 days. The recorded time frame includes working days, vacations, travelling, everyday life and all regular modes of transportation. During recording, a detailed mobility diary was conducted to capture each dwelling period’s exact beginning and end. The position and diary data combined contain 78,900 labelled stops and 43,908 labelled trips. This serves as ground truth for stop/trip classification algorithms to test existing tools or develop new analysis methods. The introduced dataset is freely available under a CC-By Attribution 4.0 International license, the annotation tool under the BSD 3-Clause license.
EFFECT OF WATER LEVEL ON MIGRATORY BIRDS HABITAT AT LAKE MAGGIORE
Authors: Tattoni C. , Giuntini S. , Gagliardi A. , Martinoli A. , Lardelli R. , Patocchi N. , Martinoli A. , Preatoni D. G.
Published: August 2022

Abstract. Migratory birds need to stop along their route to rest and feed at so called stopover sites. “Bolle di Magadino” is a protected wetland located near lake Maggiore (CH), an internationally recognized nesting and stop-over site for birds. The waters of Lake Maggiore are important resources for multiple usages, and are artificially regulated through a dam. Even slight variations in the water level are sufficient to cause flooding and draining of large portions of the wetlands, affecting foraging and resting opportunities for birds. We use open data and FOSS4G to study the effect of water level on bird migration. We compared the extent and type of flooded habitat using two approaches: Sentinel-1 remote sensing imagery and simulations based on the measured water level. The effect of type and extent of submerged vegetation obtained with both methods was tested against a time series of bird captures. Both methods had a similar temporal pattern of flooding in autumn, but nearly opposite in spring. The total extent and the type of submerged habitats showed significant differences. The results obtained by simulations based on water level were more correlated to birds captures and species richness than the estimations of flooded habitat derived by with Sentinel-1. The results presented here will contribute to the definition sustainable management tools of water management of lake Maggiore taking into account the effect of lake level on biodiversity.
EXPERIMENT ON PRODUCING DISPARITY MAPS FROM AERIAL STEREO IMAGES USING UNSUPERVISED AND SUPERVISED METHODS
Authors: Zhu L. , Hattula E. , Raninen J. , Hyyppä J.
Published: August 2022

Abstract. Recent advancement in hardware and software provides the possibility of realizing full automation in stereo-image tasks. This paper investigated disparity map generation from aerial images with different methods: unsupervised method and supervised methods. The datasets were from aerial stereo dense matching benchmark dataset for deep learning in ISPRS 2021: Vaihingen dataset and the WHU MVS/Stereo Dataset released in the CVPR 2020. Two neural networks: GC-net and PSMnet have been trained with the Vaihingen dataset and the WHU MVS/Stereo Dataset. With unsupervised methods, stereo block matching(StereoBM) and Stereo Semi-Global Matching (StereoSGM) methods from the OpenCV were studied. We selected seven image pairs from the Vaihingen dataset and six image pairs from the WHU dataset for testing and evaluation. Difficulty scenes such as textureless areas, reflective surfaces, and repetitive patterns were also included in our study. The performance from different methods was compared by both visualization and quantitative means. The advantages and disadvantages are presented.
Rethinking Higher Education Unit Design: Embedding Universal Design for Learning in Online Studies
Authors: Garrad Traci-Ann , Nolan Huw
Published: August 2022

Inclusive education in Australia has resulted in a concerted push for the differentiation of pedagogical teaching approaches by educators across Kindergarten to Year 12 (K-12) learning environments.  Such approaches have been shown to meet a diverse range of learner needs found in today's classrooms.  While progress is evident at the primary and secondary levels of education, implementing effective inclusive practices in higher education appears stagnant. Utilising the principles of Universal Design for Learning (UDL) in a fully online pre-service teacher training unit, multiple means of representation of the learning content and multiple means of engagement were explicitly incorporated into the online unit design.  This approach aimed to proactively support the engagement of all students in an online teaching and learning environment.  This study provides preliminary evidence that the application of UDL principles resulted in higher levels of student engagement and lower rates of student attrition.
Estudo bibliográfico sobre as potenciais interações medicamentosas envolvendo antidepressivos tricíclicos
Authors: Barros Landerson Guimarães , Rodrigues Junior Omero Martins , Oliveira Júnior José Reinaldo Ferreira de , Silva Alessandro Tavares da
Published: August 2022

A depressão vem atingindo uma considerável parte da população e representa uma das principais causas de incapacidade, resultando em aumento do uso de antidepressivos. Associações entre medicamentos podem ocasionar interações medicamentosas (IM), com potencial risco para o paciente.  Acredita-se que a incidência de IM é de 3 a 5% em pacientes que usam menos de 4 medicamentos, atingindo 20% entre aqueles que usam de 10 a 20 medicamentos simultaneamente. Desta forma, o objetivo deste artigo é: Identificar as potenciais interações medicamentosas envolvendo antidepressivos tricíclicos e discutir a função do farmacêutico na prevenção e no manejo dessas interações. A metodologia adotada para o desenvolvimento deste estudo foi a pesquisa bibliográfica de cunho qualitativo descritivo, fundamentada em estudos já desenvolvidos. Para tal, buscou-se os materiais por meio das plataformas de pesquisa acadêmica online: Google Acadêmico, LILACS, Scielo, Periódicos CAPES e Pubmed, no período de 2013 a 2022 e as estratégias de busca foram baseadas nas combinações das palavras-chaves e nos idiomas português e inglês, e os operadores booleanos AND e OR. Verifiou-se que dentre os antidepressivos mais envolvidos em interações medicamentosas destaca-se os antidepressivos tricíclicos. Contudo, por meio da assistência farmacêutica, pode-se prevenir e detectar reações adversas relacionadas a interações medicamentosas, alertar os prescritores e sugerir eventuais mudanças na posologia ou no esquema terapêutico, colaborando para melhorar a eficácia e segurança da farmacoterapia.
Unveiling 100 years of digitalization as a scholarly object
Authors: Gidlund Katarina L. , Sundberg Leif
Published: August 2022

Digitalization is frequently mentioned in government policies and academic discourse where it is often being associated with expectations of societal rebirth and large-scale changes. However, little attention has been given to evolutionary aspects of the phenomenon of digitalization. Thus, in this paper, we aim to contribute by focusing on the concept of digitalization in a structured manner and answering the following question: How has the concept of digitalization travelled throughout academic discourse? To focus on digitalization as a scholarly object, we utilized bibliometric analyses of research articles ranging across 10 decades. We produced bibliographic maps of keywords and co-citation networks of sources and performed visual cluster analysis of these maps using techniques from VOSviewer and ScientoPy bibliometric software. This operation was conducted to facilitate discussion on the evolution of digitalization from a semi-genealogical perspective and to open up a discussion on continuity, density, convergence, and digitalization as a signifier. By combining bibliometric data with genealogical analysis, we identified how digitalization has traveled from specific contexts (medical use and information conversion) to a more general use after the turn of the millennium. Moreover, a pattern of convergence during the last decade surfaced, where digitalization has become associated with ideas of a digitally transformed society. Through these findings, this paper contributes to current literature on digitalization with a novel analysis of the term’s evolution.
Facebook reactions as heuristics: Exploring relationships between reactions and commenting frequency on news about COVID-19
Authors: Masullo Gina M.
Published: August 2022

This study explores relationships between Facebook reactions and commenting frequency through the lens of a random sample of broadcast and newspaper news posts (n = 2,632) about COVID-19 in the United States. A main finding is that reactions on COVID-19 news posts in general — and the “like” and “angry” in particular — predict greater likelihood of comments on these posts. The topic of the post also plays an important role in both reactions and commenting frequency, suggesting people use these engagement tools in differing ways. Findings suggest that people may process reactions as heuristic cues that help them assess how much attention to pay to posts on Facebook.
Investigating the Effects of Electric Load Imbalance on Increasing Losses in the Electricity Distribution Network and Ways to reduce it
Authors:   Lecturer, Electrical Power Engineering Department, Ghazni Technical University, Ghazni, Afghanistan, Danishmal Massoud , Sarwari Mohammad ,   Lecturer, Electrical Power Engineering Department, Ghazni Technical University, Ghazni, Afghanistan, serat Zainullah ,   Lecturer, Energy Engineering Department, Ghazni Technical University, Ghazni, Afghanistan
Published: August 2022

One of the factors that cause energy losses in distribution networks is unbalanced loads. These losses, which weigh billions of afghanis on the country's economic charter, although impossible to completely eliminate, but its study can be the beginning of inventing ways to reduce it in different categories of the system. The phase between the feeder phases and the other is the random and asynchronous behavior of the subscribers is one phase. In load distribution networks, load imbalance has two important features, one variable with the amount and severity of load imbalance and the other its dispersion along the circuit. The purpose of this study is to investigate the losses due to load imbalance in the electricity distribution network. A large part of the nationwide network waste is generated in the secondary distribution network, part of which is due to load imbalance in distribution networks. In this paper, first the various problems that cause load imbalance are described, and then the calculations of energy waste and voltage drop due to unbalanced load are performed, and in the third stage, the status of a transformer with unbalanced load is investigated. Finally, practical solutions have been proposed to reduce waste due to unbalanced electrical load in the distribution network
Commitment in Pashto Short Stories
Authors:   Lecturer, Pashto literature Department, Ghazni University, Afghanistan, Asadi Nematullah , Khankhel Naqibullah ,   Lecturer, Pashto literature Department, Ghazni University, Afghanistan
Published: August 2022

The term commitment literature is often used in one language to refer to literature in which the creator has paid close attention to social aspirations and the aspirations of the deprived strata of their society. Some critics see this literature as part of a social ideology in which the creator seeks to break free from individualistic demands and isolation through his works and to express his commitment to his community and the people he addresses. Here art, according to the Russian writer Tolstoy, is not merely a means to get enjoyment but a means of strengthening human relations with the well-being of individual and human society. A good literary work needs to reflect the realities of the times point out its shortcomings and find solutions to its problems; otherwise, it will not be considered as good work. (Landy) or Pashto short story is one of the folk poems. Folk poems are poems that are based on the artistic experiences of the people and express the taste, passion, imagination and intellectual experiences of particular nation. Landy is a two syllable poem, the first syllable is short just nine syllable and second syllable is thirteen syllables and every fourth syllable has a syllable on it, and one of the characteristics of (Landy) is that they can be fully understood and explained in this long frame. Afghanistan is one of the least developed countries in the world, so its poets and writers try to choose a beautiful forum for their work as well as topics that suit the needs of the society. Pashto short stories which are not available in any other language of the world. As a result, the demands of the people have been fully addressed in the shorts, as they can be names in the literature of promise.
A Model for Sustainable Adoption of Solar Photovoltaic Technology in Tanzania
Authors: Raymond J. , Kihedu J. H. , Kimambo C. Z. M.
Published: August 2022

Solar photovoltaic (PV) technology has been used for several decades to meet the electric energy need of various communities in Tanzania, particularly in rural areas that face a supply gap, due to various reasons. This study builds on three previous     projects that were implemented at different locations of the United Republic of Tanzania. These projects are the Sustainable Solar Market Packages 1 (SSMP 1) Project, which was implemented in Sumbawanga District; the Sida/MEM Solar Project, which was implemented in several regions of Tanzania Mainland and the UNDP/MEM Solar PV Project, which was implemented in Mwanza region. The aim was to develop a sustainable model for enhancement of the solar PV technology adoption in Tanzania. The model was developed based on the identified barriers that hinder the adoption of solar PV technology and adopted the best strategies from successful projects. Further, the drivers and activities were developed based on selected best strategies from successful projects. The identified barriers to the adoption of solar PV technology were grouped into five categories based on their significances. These include; limited access to finance (32%), weak enforcement of relevant policy and regulations (31%), technical capacity (18%), lack of awareness (9%) and other social drivers (10%). The analysis of information and data that was obtained from the project reports shows that there are prevailing challenges on awareness on solar PV technology and non-enforcement of quality standards. However, major barriers are on the high price of solar PV systems and lack of access to finance. A model for adoption of solar PV technology in Tanzania was developed and tested by validating it with a successfully implemented solar PV project in Tanzania. In the validation, thirteen (13) out of twenty-one (21) activities of the UNDP/MEM Solar PV Project demonstrated the moderate compliance with the model prescription by 62%. The UNDP/MEM Solar PV project developed a financing mechanism but it was not sustainable due to low application of sustainable adoptions strategies. Also, most of the strategies lacked some important drivers and activities due to financial constraints and technical know-how. The mechanism was not opening opportunities for new users to adopt the solar PV technology or maintain the existing ones. Moreover, stakeholders have not put in place the conducive conditions for existing projects to be sustainable. Recommended future interventions include application of the developed adoption model for Solar PV by using data from other solar PV projects for sensitivity analysis of identified barriers and best strategies.
Analysis of Recent Trends in Single Image Dehazing Techniques
Authors: C Jenisha , Joice C Sheeba
Published: August 2022

The main objective of this paper is to present a detailed study on various recent innovations in haze removal techniques. The suspended particles in the atmosphere like mist, fog, and haze cause the captured picture to get degrades. Hence to get a clear image the dehazing technique is essential and the dehazing technique is also important since it is used for various applications like urban transportation, video analysis, visual surveillance, Image Processing, computer vision, outdoor photography, medical imaging for diagnostic purposes, object detection, object recognition, etc. In this paper, we have classified the existing dehazing techniques into Multiple and Single Image dehazing techniques and explained the significance of each method in detail. This paper also presents the outcomes of the DCP, CAP, MLP, DehazeNet, and PMS-Net dehazing methods by assessing the resultant dehazed image visually by qualitative analysis and by calculating the MSE, RMSE, PSNR, SSIM, BRISQUE, and FADE evaluation metrics by quantitative analysis. Thus, this paper helps the nurturing researchers who are doing their research work in this field, to acquire a wide knowledge about the various haze removal techniques.
Energy Optimization In Data Centers For Cloud Computing
Authors: R Bobra Anjali , Patel Bhavesh
Published: August 2022

Cloud is rising as an integrative research area due to its systematized handling over the varied computing resources as a service to the end users all over the web. It has emerged with adding into large scale Data centers which contain thousand number of heterogeneous servers across the globe. These Data centers require lot of energy for its functioning. Looking into the increased requirement of computing, the size of Data Centers is increasing day by day and in turn resulting in increased consumption of energy. This poses a real challenge in front of the industry to make the data Centers green and energy efficient to reduce both the cost of running and carbon foot print which is not environment sustainable. Several energy optimization approaches are suggested by various re-searcher in this area. Regarding this end, we identified distinct techniques which are capable of minimizing the energy intake of data centers like consolidation, cooling techniques, routing algorithms, virtualization, scheduling, load balancing and migration etc. We have also reviewed various simulation tools used by researchers for testing their energy efficient approaches. Lastly a research direction has been identified for play down the consumption of energy.
A Network Infrastructure for Security Enhancement
Authors: Verma Shikha
Published: August 2022

Security is big concern for an organization. All the work done in any organization should be secure and protected from unauthorized access. The physical arrangement of workstation forms topology. Organization’s most commonly used topologies are star and ring. Paper also presents architecture for an organization that is most protected from failure. To ensure security, organization should use port level security. Secured ports help to limits the workstation to be connected to the port. This helps in security as well as traffic management. The paper also presents the maintenance of syslog server to check unauthorized access so that network can be protect from outside world. As the organization’s LAN connected to outside world so the security of routers, firewall and wireless access point is also needed.
Diagnosis of Skin Cancer using Deep Learnig
Authors: Mishra Nitin , Chaturvedi Saumya
Published: August 2022

Skin diseases consist of a wide range of ailments that affect the skin, including microbial infections, viral, fungal, allergies, epidermis malignancies, and parasitic diseases. In South-Asian countries like India, people don’t care much about skin conditions. In our country, people prefer home remedies to cure skin conditions instead of visiting a dermatologist which can lead to serious skin conditions. Early diagnosis of skin disease is very important as it can reduce the severity of the condition. Melanoma is the deadliest type of skin cancer and the most prominent form of cancer. Melanoma could be diagnosed early, which would reduce overall illness and death. The odds of dying from the ailment are proportional to the extent of the malignancy, which is proportional to the length of time it has been growing. The keys to early detection are patient self-examination of the skin, full-body skin screenings by a dermatologist, and patient engagement. This work aims to categorize skin cancer into two types: malignant and benign. Two different approaches were used. Starting with a simple Convolutional Neural Network and then moving on to transfer learning. In our experiment, we were able to attain a classification accuracy of 82 percent.
Comparative Study of Rainfall Prediction Modeling Techniques : Case Study on Karapur, India
Authors: Iliger Sushma , Pinto Mario
Published: August 2022

India's economy is highly dependent on agriculture which is in turn dependent on rainfall. Every region receives varying amounts of rainfall and based on that the crops are grown to suit the geographical conditions. Due to the lack of proper predictive technology in making use of rainfall, the agricultural practices have put high pressure on the underground water tables leading to depletion of water resources in local areas. Considering these factors, we have tested the suitability of the different existing machine learning models for the data collected from the Karapur weather station of Goa state, India to predict rainfall locally. The different models being used are Multiple Linear regression(MLR), Decision tree Regressor, Random forest Regressor, XGBoost, and Artificial Neural Network algorithm(ANN). After analysis we obtained 85% accuracy and the algorithm performance compared in terms of mean absolute error and R2 Score. . The result of the study revealed that ANN outperformed the others by delivering an average R2 score close to 1.
A Review: Development of Smart Agriculture Using IOT, Agriculture Robots and Wireless Sensory Network
Authors: Sharma Disha , Vaishnav Dharmendra , Joshi Divyanshu , Krishan Sharma Gopal , Trivedi Dharmendra
Published: August 2022

Concerns about food security have skyrocketed in recent years. As agriculture is the backbone of India and about 70 percent of the people in our country depend on agriculture and agricultural production must increase rapidly to meet the food needs of people around the world. Agricultural challenges need to be addressed by adopting new approaches to improve soil capacity and the protection of natural resources. Therefore, the internet of things will bring unimaginable benefits to help people to live smarter and more comfortable lives. In this paper, the utilization of IOT in farming and agricultural sector has been investigated and analyzed with functional agricultural robots relying solely on the development of agricultural robots in operation, which includes reliable interaction (HRI) between robots and agricultural workers, as well as on existing infrastructure and also Wireless sensory networks (WSNs) can be used in agriculture to provide farmers with a large amount of information. A number of sensory technologies are used in precise agriculture, providing data that helps farmers to monitor and prepare crops that measure temperature, soil moisture, and location-based humidity.
Avian Influenza Prediction Using Machine Learning Approaches: A Review
Authors: Shori Maana , Saroha Kriti
Published: August 2022

The avian influenza virus can be a cause of economic devastation due to its impact on poultry and potentially on the economy, making it the cause of a potential pandemic. By predicting the disease, the consequences can be mitigated, so the work done in this area so far and the gaps in the study are reviewed in this paper. An approach is also proposed in this direction.
The Planning and Production of A Hindi Digital Dictionary for NLP Specific Purpose
Authors: Sharma Gatha , Sharma Anaadi
Published: August 2022

Digital humanities provide possibilities for the creation of new pathways for research in the field of Humanities and Social Sciences. A complete digital infrastructure has to be created to realize these possibilities. Since the 1960’s computational linguists are trying to develop tools for better communication between human languages and machines. A digital dictionary is one such tool. It forms the core of natural language processing (NLP) based tasks. Digital dictionaries contain an enormous amount of information and are very useful, but their design is structured according to the specific needs either of the language learners or the program for which they had been designed, so data access for other NLP tasks is either limited or denied completely. The creation of a completely new digital dictionary becomes inevitable in such a scenario.
The Analytics of Big Data & Hadoop Architecture: A Literature Review
Authors: Pokharana Anchal , Sharma Krishankant , Sharma Samiksha
Published: August 2022

We are living in an immensely created, specialized time, where the web is getting to be the major need of all people. Today, our social, individual, and in addition proficient life is rotating around the internet. Along these lines, bringing forth Big Data at a staggering force. Conventional administration apparatuses and systems are demonstrated, un-reasonable while managing Big Data. Big Data has actually been coined for and represents those useful & informational attributes of data whose volume, speed, and distinctiveness make them complex to be caught, worked with, or processed upon. So in order to manage this large data, the Hadoop platform comes into the picture. Hadoop is an open-source platform that ensures massive data management, and data regulation and also takes care of heavily enlarged data applications running in assembled systems. It is at the point of convergence of creating an organic network of colossal data which is on a very basic level and is used for advanced assessment exercises, including data mining and AI applications.
Crop Recommendation System and Plant Disease Classification using Machine Learning for Precision Agriculture
Authors: Choudhary Mahendra , Sartandel Rohit , Arun Anish , ladge Leena
Published: August 2022

The Agriculture sector is the backbone of our country. It provides a living for the vast majority of India’s inhabitants, but it only accounts for 15% of the country’s GDP. In comparison to other countries, our country’s crop yield is quite poor. This could be one of the reasons for India’s increased suicide rate among marginal farmers. Another cause for this is that farmers do not plan their crops properly. Another reason for this situation is that farmers frequently make incorrect crop selection decisions, such as planting in the wrong season or picking a crop that would not yield much for the particular soil. Incorrect crop selection will always result in a lower yield. It is difficult to survive if the family is entirely dependent on this revenue. In this paper, we offer a model that addresses these concerns. The suggested methodology allows for crop selection based on economic and environmental factors, intending to boost crop yields to satisfy the country’s growing food demand. The proposed model predicts the crop yield by studying factors such as rainfall, temperature, humidity, soil nutrients, ph value of the soil. The model assists farmers in maintaining soil nutrient levels. In addition to that, the app will enable farmers to identify diseases in their plants.
AI in Healthcare: Privacy, Trust and Ethical Challenges
Authors: Rawat Srishti , Singhal Shefali , Gupta Tanvi
Published: August 2022

Artificial intelligence is an ever-growing technology that has proved its usefulness in the field of healthcare. However, AI has also raised several challenges and ethical concerns in relation to privacy and trust. Embedding this system in AI has raised some serious concerns from the unethical use of user data to taking responsibility in case of a mishappening. In this paper, we will give an overview of some of the facilitation of AI in healthcare and a review of some major areas of concern regarding the correct and ethical usage of this technology. The goal of this research is to state some approaches to the challenges introduced by AI in the healthcare industry.
Comparative Analysis of Resonant Converters
Authors: Shiva Rama Krishna Prasad Lingabathini , Srinivas Mavurapu
Published: August 2022

This paper presents the comparison among the different resonant converters especially in the Analysis of Total Harmonic Distortion (THD). The THD of output current from the inverter circuit (or) resonant current of different resonant converters such as series LC, LLC and LCC is determined. The resonant converters are to be operated above the resonant frequency to obtain the Zero Voltage Switching (ZVS) to achieve the lesser switching losses. The simulation of various resonant converters is performed in the MATLAB/Simulink software.
Forensic Analysis of Blue Talk (Random Chat)
Authors: Manna Francis , Kumar Agrawal Animesh
Published: August 2022

Android forensics has evolved over the years; with new opportunities comes a variety of new challenges. Being open-source, the Android platform allows developers to contribute to the fast-growing Android market. However, users of Android smartphones may be unaware of the security and privacy consequences of installing applications on their mobile devices. Android applications (apps) use a permission strategy where permissions govern access to certain APIs. Unfortunately, no internal verification method is available to prevent applications from seeking too many or fewer permissions, leading to privacy issues. When applications request too many permissions, users are exposed to avoidable threats. Blue Talk (Random Chat), a social networking smartphone application, is one such popular app available on the Android play store that saves a lot of user data, which can be extracted and used as potential forensic evidence. This study describes how forensic investigators can use Blue Talk (Random Chat) on the Android platform to obtain useful information. The extraction and analysis of artifacts and the application’s permission and vulnerabilities on an Android device are the key focus areas in the research.
Review on Signalling in Indian Railways and Way for the Future
Authors: Kumar S. Sravan , Chaitanya K. Krishna
Published: August 2022

The need for having better signaling system which ensures safety, has gained more demand after the inclusion of electronic systems like track circuits, axle counters etc., into railways. Signaling problem is more severe in India because of its huge population and most of them are relying on railways. To serve the needs of passengers, Indian railways has introduced many electronic signalling systems, but survey shows that there is still scope for improvement of the safety standards which improves reliability of railway networks. This paper presents various signalling methods which includes ETCS,GSM-R,CBTC and their standardizations that were followed in India and new ideas for further improvement of signaling is presented.
“That Was Amazing!” A Two-Study Perspective on Language Classroom Experiences Through the Lens of Psychological “Flow”
Authors: Jacobs Christopher , Morgan William
Published: August 2022

The construct of psychological flow bridges several areas of second language learning interest, including motivation, investment, self-efficacy, and autonomy. Flow, characterized by intense focus on an enjoyable activity that is at once challenging and accessible, creates conditions that have been linked to learning. Research interest in flow has grown, but the L2 research remains scarce and exploratory. This paper, which uses a two-study format, proposes and tests a new category coding scheme designed to explain which activities generate language-class flow. In Study A, third- and fourth-semester learners of Spanish, French, Italian, and German (N = 82) described their most flow-generating language-class experiences on an online questionnaire. In Study B, first- through fourth-semester students of Spanish (N = 588) did the same. The responses were coded to one category in each of four contrasting category pairs. Parallel analyses were conducted for each study, and within each study counts and chi-square tests were performed separately on each category pair. The results of both studies showed statistically significant contrasts within all four category pairs, and revealed that student-centered, open-ended, authentic, and non-competitive activities were more likely to generate flow than their opposites (i.e., teacher-centered, closed-ended, inauthentic, and competitive activities). Pedagogical implications and directions for future research are discussed based on these results.