bluuebunny/crossref_metadata_2025 huggingface dataset:
High Speed Built in Self-Test via Pattern Generation
Authors: S Riju , G. V Soni Meera
Published: September 2023

This paper presents the built-in self-test (BIST) design of a C-testable high-speed carry-free divider which can be fully tested by 72 test patterns irrespective of the divider size. Using a graph labelling scheme, the test patterns, expected outputs, and control signals can be represented by sets of labels and generated by a simple circuitry. As a result, test patterns can be easily generated inside chips, responses to test patterns need not to be stored, and use of expensive test equipment is not necessary. Results show that the hardware cost for generating such labels is virtually constant irrespective of the circuit size. Dividing Circuits, Integrated Circuit Testing, Integrated Circuit Design, Design For Testability, Digital Arithmetic, Built In Self-Test, Graph Theory, Built In Self-Test Design, High Speed Carry Free Dividers, C Testable Circuits, Graph Labelling, Test Patterns, Control Signals, 64 Bit, Built In Self-Test, Circuit Testing, Automatic Testing, Test Pattern Generators, Hardware, Signal Generators, Test Equipment, Costs, Controllability, Observability, In Spartan3E FPGA device family, computation of 8-bit circular convolution using Modified Karatsuba Algorithm.
Development and Analysis of Mechanical Properties of Natural FRP Composites for Marine Applications
Authors: A. K Ratheesh , L Udhayalakshmi
Published: September 2023

Polymer matrix composites with filler reinforcements have undergone considerable advancements recently. In a variety of industries, including aerospace, automotive, construction and marine, these composites have showed considerable promise. The mechanical qualities of the composite material, such as strength, stiffness, and toughness, can be enhanced while keeping a low weight by the inclusion of natural fiber and filler reinforcements. Filler and fiber reinforcements has shown a great promise in improving the performance and versatility of composite materials, and further research and development in this area are expected to continue. Despite the many benefits of polymer matrix composites with filler and fiber reinforcements, there are still problems that need to be solved. For example, it is difficult to achieve uniform reinforcement dispersion, to manage the interfacial bonding between the particles and the polymer matrix, and to scale up production without increasing costs. Numerous crucial fundamental features of a composite material are heavily influenced by the homogeneous distribution of filler particles throughout the material. The enhancement is significantly affected by the uniformity of the dispersion of these particles, inclusions, filaments, or fibers within the matrix material. In this proposed work mainly deals with the development and analysis of the Natural FRP polymer composites with added natural filler which are abundantly available in and around our vegetation such as coconut, bamboo, cactus etc. The Natural composites can be fabricated and tested for its mechanical, metallurgical and Thermal characteristics and compare with the properties of existing material and explore the opportunities of introducing the natural fibers and fillers in the existing Marine composite materials such as Ferro cement, Glass reinforced plastic, Aramid fiber Composites etc.
Building Design Techniques to Withstand Landslides
Authors: R. M Pooja Raj
Published: September 2023

Landslides are among the many natural disasters causing massive destructions and loss of lives across the globe. India has a high degree of vulnerability towards the occurrence of Landslides. Landslides and avalanches are among the major hydro-geological hazards that affect large parts of India. Around 15% of the country’s region is prone to landslides. The Himalayas of Northwest and Northeast India and the Western Ghats are two regions of high vulnerability. Some major recent incidents are Kerala (2018), Himachal Pradesh (2018), Uttarakhand (2018), Tamenglong-Manipur (2018), and Kalikhola, Manipur (June 2017). Landslides are a natural phenomenon, but it involves many human activities which lead to the mass movement of landmass. In recent times we find the causes of landslides increasing day by day and the primary cause is deforestation. To survive, one needs to keep a check on these human activities. Landslides can result in enormous casualties and huge economic losses in mountainous regions. In order to mitigate landslide hazard effectively, new methodologies are required to develop and a better understanding of landslide hazard are required. To reduce future risks, it is important that a lot of attention is paid to the structural design of the buildings. This paper is aimed to propose some techniques and materials to resist landslides that allow the local communities to continue living on landslide prone slopes without causing damage to buildings.
Study on Analysis of Risk in Construction Management
Authors: P. S Megha
Published: September 2023

There is an several kind of risk occurrence due to increasing of construction projects which leads to excessive effects in time and cost basis. It is based on identification, evaluation and management of risk in construction project. Finally, we provide the suggestion to avoid risk and how to rectify the following risk occurrence. That’s why we collected the data in Gantt chart from construction officials and also to receive the information about construction project by questionnaire. From that we analyses the risk by using software like primavera. The data collection is based on two suspects as government and private organization. Apart from that, we referred number of journals which gave some ideas to manage the risk and provide the solution to avoid risk during construction work and also provide kind of solutions for construction risk sector. Risk assessment is a tool to identify those risks in a project and manage it accordingly with proper treatment. Risk assessment is defined in this study as a technique that aims to identify and estimate risks to personnel and property impacted upon by a project. The aim of this project report is to make aware of risk that occur during construction work and give some reasonable solution in construction project with procedures. A brief discussion on application of risk management, hence, somewhat better outcome, avoid risk and value of constructor and client were studied.
Secure Data Storage and Sharing Techniques: A Review
Authors: R Akila Rahini , S. T Sukanya
Published: September 2023

A large number of researchers, academia, government sectors, and business enterprises are adopting the cloud environment due to the least upfront capital investment, maximum scalability, and several other features of it. Despite the multiple features supported by the cloud environment, it also suffers several challenges. Data protection is the primary concern in the area of information security and cloud computing. Numerous solutions have been developed to address this challenge. However, there is a lack of comprehensive analysis among the existing solutions and a necessity emerges to explore, classify, and analyze the significant existing work for investigating the applicability of these solutions to meet the requirements. This paper presents a comparative and systematic study, and in-depth analysis of leading techniques for secure sharing and protecting the data in the cloud environment. The discussion about each dedicated technique includes: functioning for protecting the data, potential and revolutionary solutions in the domain, the core and adequate information including workflow, achievements, scope, gaps, future directions, etc. about each solution. Furthermore, a comprehensive and comparative analysis of the discussed techniques is presented. Afterward, the applicability of the techniques is discussed as per the requirements and the research gaps along with future directions are reported in the field. The authors believe that this article’s contribution will operate as a catalyst for the potential researchers to carry out the research work in the area. In this paper investigating various methods used in the existing work for the secure data storage.
Charity System Based Using Blockchain
Authors: J Anju , R Gini
Published: September 2023

The charity organizations in China lack transparency and the supervision to them is difficult to achieve, which has a negative impact on the willingness of the people to donate. Blockchain as an underlying technology of Bitcoin system provides a new solution for the charity system in terms of technology. This paper proposed a charity system based on blockchain technology and expounds the design pattern, architecture and operational process of the platform. Some core functions of the charity platform have been realized and verified on Ethereum in this article. We hope to increase the transparency of charities to enhance the public’s trust in charities and promote the development of philanthropy by blockchain-based charity system.
Gradient Boosting and Naive Bayes Crop Yield Prediction and Fertilizer Recommendation
Authors: R Surya , S. T Sukanya
Published: September 2023

Farmers use Big Data to get information on changing Weather, Rainfall, Fertilizer Usage, Rainfall, and other factors that impact the crop yield. The yield of a crop is mainly determined by the climatic conditions like Temperature, Rainfall, Soil Conditions, and Fertilizers. All of this information assists farmers in making accurate and dependable decisions that maximize their productivity from cultivating the land. Recently, the Machine Learning Algorithms are used by the researchers to predict the yield of a crop before its actual cultivation. Firstly, Pre-process the data in a Python environment and then apply the Map Reduce Framework, which further analyses and processes the large volume of data. Secondly, K-means Clustering is employed on results gained from Map Reduce and provides a mean result on the data in terms of accuracy. Using Gradient Boosting Algorithm to predict the yield of crops based on the parameters like State, District, Area, Seasons, Rainfall, Temperature, and Area. To enhance the yield, this work study also suggests a fertilizer based on the soil conditions like NPK Values, Soil Type, Soil PH, Humidity, and Moisture. Fertilizer Recommendation is primarily done by using the Naive Bayes [NB] Algorithm.
Logistics Management in Construction Industry
Authors: L Vaniraj Mitra , T. R. Sethuraman , G Sujithra
Published: September 2023

Planning, transporting, and controlling the process of acquiring and managing resources is known as logistics in construction management. It is impossible to ignore the importance of logistics in construction management. With the right logistics, a challenging construction project can become a well-organized activity with reduced costs and improved procedures. Construction logistics main goal is to facilitate the hiring of laborers, the transportation of materials, and other resources needed during the construction process. This project focuses on researching factors influencing logistical management in the construction sector and putting appropriate solutions in place. For this purpose, initially nineteen Literatures are studied based on construction logistics management. From the literatures it was studied that statistical analysis is better way to analyze Logistics management in construction industry and important factors that are affecting in construction logistics is identified from the literatures. Questionnaire regarding the factors affecting construction logistics is also prepared. Then, data was gathered from various construction companies. The data are then ranked using the relative importance index method. The Microsoft Excel software is used to analyse this data and identify the key variables that have an impact on logistics management in the construction sector. The Microsoft Excel software is used to analyse this data, and Anova one-way test is used to identify the important factors that influence logistics management in the construction industry.
E-Commerce Application for Farm Fresh Trading
Authors: V. G Kaviya , R Gini
Published: September 2023

For several years, farmers in India have had little liberty in choosing markets and purchasers for their produce. All states in the country, except three, degree that marketing and selling of farm produce must be directed through state-owned mandis, retail markets where mediators (middlemen) crush farmers to increase margins. According to research, mediators have become dominating buyers of the agricultural market, resulting them to take control over the plight of the farmers and gulping all the profits. The farmers work day and night expecting a good yield. They use a lot of financial resources lending money and buying fertilizers, seeds etc. So, they have the right to enjoy every rupee gained on their corp. In this context, we propose a system which brings farmers close to the retailers cutting the middlemen. Our system consists of a mobile or web application which will serve as a platform for farmer the growers and retailers or customers to sell and buy their farm products. This system aims at giving a profitable price to farmers to their farm products cutting the middlemen. This allows the retailers or the customers to buy products from the farmers at a lower than the normal price. Farmer uploads their product with details and buyers view these details and book that product with in a time. The bidding system is suitable for bulk buyers who would like to bargain for a certain product. They will be able to bid on a product as well as view other bids. This will help them get products at a better price. The consumer can give a rating and review only after having purchased a particular product. K-Nearest Neighbours (KNN) is proposed to recommendation system based on common product ratings, and make predictions using the average rating of top-k nearest neighbours. These are visible on each item’s page along with the average of the item’s average rating. K-Means is used to overcome sparsity problems and to form user clusters to reduce the amount of data that needs to be processed.
Vehicle Overload Detection System Using Pic Microcontroller
Authors: S. L. Sini , P Thenmozhy , J. B Abisha Jey
Published: September 2023

Most of the road accidents in the present era are due to overloading the vehicles. Highways are where most accidents occur due to vehicle overloading. Most of the overloaded vehicles are truck/lorries and other vehicles are buses, car and bikes. Overloaded vehicles also damage to the road. Overloaded buses can cause passengers a variety of injuries in a crash, such as broken bones, herniated disc, organ damage etc. Nowadays there are very few systems to detect vehicle overloading in real time. The main purposeof this project realizes real-time detection of vehicle load.
Seismic Analysis of a Structure Considering Effect of Soil Structure Interaction
Authors: J Jenifa , H. Hanio merinkline
Published: September 2023

Structural design is the main part of nowadays in life of civil and structural Engineer. As in today’s scenario there are a lot of parameters which is used in designing parameter which affects the life and quality and the working life and ability of the structure. In today’s life software’s are used to design structure. The software’s which are used in daily life nowadays are Stand pro and Etabs. So, in this project we are going to planning, designing and Analyze a Residential G+12 Building using Etabs. M25 grade of concrete and Fe 415 steel material use for the design of structure. IS Code 456-2000 & IS 800-2007 LSM are used for concrete and steel section design. We are looking for the seismic analysis due to earthquake load.
A Study on Working Capital Management Kerala Automobiles Limited Aaralumoodu, Neyyattinkara
Authors: S Aparna , A. Robert Raja Singh , C. R Manju
Published: September 2023

In this project title “A Study on working capital management at Kerala Automobiles Limited”. The study aims to analyses the liquidity profitability and solvency position of the firm using the financial tools. The study’s made based on financial statement for the past five years of KAL using financial tools such as ratio analysis, comparative balance sheet analysis, and working capital analysis. By combining these tools it enabled to determine the results in effective’s manner. The study is made to evaluate the working capital get operational result as well as to known the future progress of business concern. This study not only focus on the working capital management of the firm but also serves as a stepping stone to make remedial measures ensuring future business prospectus of KAL. To analyses the overall business activities, financial statement of the company for the past five years from 2017-2022 was taken into consideration. The firm having effective infrastructure facilities and skilled personal and its effective utilization could result into better attainment of business goals and thereby in attaining the good will of the company.
A study on Organizational Culture and its Impact on Employees Behaviour with special reference to TTK Prestige Ltd, Coimbatore
Authors: S. N. Dharshini , A. Robert Raja Singh , S. R Haritha
Published: September 2023

Organizational culture is the accepted norms and values that are associated with a particular company. These norms are seen as distinctive to a particular organization. Organizational culture can be tackled in three realms such as behaviour & artifacts, values & assumptions and beliefs. The term behaviour denotes the visible elements of culture prevailing with a certain organizational dress code, the way employees use technology in their task etc. The objective of the study is to assess the existing culture of the organization and to find its impact on employee’s behaviour, to study the relationship between organizational culture and employee behaviour, to understand how the employer encourages participation in decision making and to find out the most influencing factors affecting organizational culture. The research design used in this study is descriptive research design. Data from 50 people were collected as population study. Data was collected by survey method through structured questionnaire with close-ended questions. The primary data was obtained through questionnaire directly from the employees. The secondary data was collected through internal source and external source, company records, documents, journals & websites. The collected data has been edited, classified and tabulated. The statistical tool used in this study is Percentage analysis, Chi-square test, and Correlation and Weighted Average method.
Lung Infection Segmentation of COVID-19 in CT Images With Deep Convolutional Neural Network
Authors: G Jijo , S. T Sukanya
Published: September 2023

In this paper, try to establish a new deep convolutional neural network tailored for segmenting the chest CT images with COVID-19 infections as well as the entire lung from chest CT images, referred to as COVID-SegNet. The proposed method can be hugely beneficial for the early screening of patients with COVID-19. Inspired by the observation in annotation processing, the boundaries of COVID-19 infection regions are highlighted by adjusting the window breadth and window locations, extend Squeeze and excitation (SE) unit, named Feature Variation (FV) block, for handling the confusing boundaries. The main idea of the FV block is to implicitly enhance the contrast and adjust the intensity in the feature level automatically and adaptively for different images. Based on the captured features of previous layers, the FV block employs channel attention to obtain the global parameter to generate new features. In addition to the channel attention, the FV block uses spatial attention to guide the feature extraction from inputs in the encoder. Aggregating these features can effectively enhance the capability of feature representation for the segmentation of COVID-19. Furthermore, we propose a Progressive Atrous Spatial Pyramid Pooling (PASPP) to handle the challenging shape variations of COVID-19 infection areas. PASPP consists of a base convolution module followed by a cascade of atrous convolutional layers, which uses multistage parallel fusion branches to obtain the final features. Each atrous convolutional layer in PASPP only uses atrous filters with a reasonable dilation rate to cover different receptive fields. And by the progressively aggregated information from atrous convolutional layers, the information from multiple scales is effectively fused, which further promotes the performance of COVID-19 pneumonia segmentation. The proposed method achieves state-of-the-art performance. Dice similarity coefficients are 0.987 and 0.726 for lung and COVID-19 segmentation, respectively. Here, conducted experiments on the data collected in China and Germany and show that the proposed deep CNN can produce impressive performance effectively. The proposed network enhances the segmentation ability of the COVID-19 infection, makes the connection with other techniques and contributes to the development of remedying COVID-19 infection.
Adoption of IoT technology in Maritime Sector
Authors: B Mary Nathisiya
Published: September 2023

By its very nature, the transport and logistics industry demands an extensive and effective data interchange for successful management and decision-making. A specific approach is needed for the marine industry because of the complex and diverse environment. The naval industry’s quick adoption of IoT technology will make it easier to administer basic services like vessel monitoring, emissions control, preventative maintenance, safety, and welfare. The IoT solutions described in this article are tailored to the industry’s current demands. The suggestions are in line with the projects, which intends to provide an interactive study course on maritime and surveyor IoT systems to fill the market need caused by the rapid growth of the Smart Maritime & Surveying business.
A High-Speed, Area-Efficient Transfer Method Using a Reverse Carry Propagate Adder
Authors: V. S Muralikrishna , M. Joselin Kavitha
Published: September 2023

The most important component of any electronic device has historically been the arithmetic and logic unit. An efficient algorithmic function, such as addition and multiplication, which is required for an arithmetic as well as logic unit to be significant in the current improvement. For performing modular arithmetic in several cryptography and pseudorandom bit generator (PRBG) algorithms, the three-operand binary adder is the fundamental functional unit. In this paper, this study purposes a reverse carry propagate adder A carry input signal is more important than the carry output signal because, in the RCPA structure, the carry signal flows counter-clockwise from the most significant bit to the least significant bit. In the presence of delay changes, this carry propagation technique results in greater stability. Three implementations of the reverse carry propagate full-adder cell with different delay, power, energy, and accuracy levels are introduced by this study.As a result, it continues as one of the greatest options for creating huge arithmetic circuits with little increase in area and minimal power and energy usage.
AxPPA: Approximate Parallel Prefix Subtractor
Authors: M Jithu , R. A Abisheka
Published: September 2023

Parallel prefix Subtractor is the most flexible and widely used for binary addition/subtraction. Parallel Prefix Subtractor is best suited for VLSI implementation. No any special parallel prefix Subtractor structures have been proposed over the past years intended to optimize area. This paper presents a new approach to new design the basic operators used in parallel prefix architectures which subtract the unit by using modified technique of 2’s complement. Verification will also be done using LFSR technique so we don’t need to apply any manually input to perform the subtraction process. We can analysis and create the difference in terms of area between parallel prefix Subtractor and BIST architecture of parallel prefix Subtractor. The number of multiplexers contained in each Slice of an FPGA is considered here for the redesign of the basic operators used in parallel prefix tree. The experimental results indicate that the new approach of basic operators make some of the parallel Prefix Subtractor architectures faster and area efficient.
Prediction of Cancer Disease Using Machine Learning Approach: A Review
Authors: D Abishek , R Sujitha
Published: September 2023

Cancer has identified a diverse condition of several various subtypes. The timely screening and course of treatment of a cancer form is now a requirement in early cancer research because it supports the medical treatment of patients. Many research teams studied the application of ML and Deep Learning methods in the field of biomedicine and bioinformatics in the classification of people with cancer across high or low-risk categories. These techniques have therefore been used as a model for the development and treatment of cancer. A sit is important that ML instruments are capable of detecting key features from complex datasets. Many of these methods are widely used for the development of predictive models for predicating a cure for cancer, some of the methods are artificial neural networks (ANNs), support vector machine (SVMs) and decision trees (DTs). While we can understand cancer progression with the use of ML methods, an adequate validity level is needed to take these methods into consideration in clinical practice every day .In this study the ML & DL approaches used in cancer progression modeling are reviewed. The predictions addressed are mostly linked to specific ML, input, and data samples supervision. 2021ElsevierLtd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Virtual Conference one Advanced Nano materials and Applications. This is an open access article under the CCBY-NC-ND license.
Students Performance Prediction and Classification Using Ridge Regression Algorithm
Authors: S. S Pooja
Published: September 2023

Education system is very old and due to a large population of students, there are some serious issues in analyzing and predicting students’ performance. Every institution has its own set of standards for evaluating student success. In existing system there is no proper procedure for monitoring and analyzing a student’s performance and progress. Here the focus is given to additional external factors like students status, parent occupation etc.. That will be more effective in visualizing and analyzing student’s performance. This project proposed Ridge regression Algorithm is used.
A Fabric Defect Detection Method Based on Deep Learning
Authors: J Dhaneesh , R Sujitha
Published: September 2023

Fabric defect detection is a challenging task in the fabric industry because of the complex shapes and large variety of fabric defects. Many methods have been proposed to solve this problem, but their detection speed and accuracy were very low. As a classic deep learning method and end-to-end target detection algorithm, YOLOV4 has evolved rapidly and has been applied in many industries, showing good performance. This paper proposes an improved YOLOv4 algorithm with higher accuracy for fabric defect detection, in which a new SPP structure that uses Soft Pool instead of Max Pool is adopted. The improved YOLOv4 algorithm with three Soft Pools can process the feature map effectively, which has a significant advantage in reducing the negative side effects of the SPP structure and improving the detection accuracy. The improved SPP structure is used by the three outputs of Backbone, and in order to ensure that the output can be inputted into the subsequent PANet successfully, the network structure is improved that a series of convolution layers after the SPP structure is added for reducing the channel numbers of feature map to an appropriate value. In addition, contrast-limited adaptive histogram equalization is adopted in advance to improve the image quality, which results in strong anti-interference abilities and can slightly increase the mAP. Experimental results show that, compared with the original YOLOV4, the improved YOLOV4 increases the mAP effectively by 6%, while the FPS only decreases by 2. The improved YOLOv4 can identify the location of defects accurately and quickly, and can also be applied in other defect detection industries.
Analysis of Soft Storey Buildings with Different Types of Steel Bracing Under Seismic Load
Authors: A Govind
Published: September 2023

A soft storey is one that has a discontinuity in the stiffness of the building where one storey is significantly more flexible than the other storey. In order to tackle the problem of parking space, open ground storey is more preferred. The soft storey effect is the main criteria to be considered while constructing a building with open ground storey configuration. These buildings possess a higher tendency for collapse during earthquake due to soft storey effect. The discontinuity in stiffness will result in large bending moment and shear force action in open ground storey building. The study aims to find out the effects of soft storey configuration in the building with different types of steel bracings under seismic loads. The types of steel bracing include concentric bracing, eccentric bracing and cross bracing. The effect of bracings systems used in soft storey building under seismic load are studied using ETABS software. The different parameters like lateral displacement, bending moment, storey drift, storey shear, storey stiffness needs to be analysed and compared. Response spectrum analysis and nonlinear dynamic time history analysis is carried out to understand the behaviour of building under earthquake loads. From the results it was concluded that, the inclusion of cross steel bracing proved to be the most effective structural configuration closely followed by the concentric inverted V steel bracing configuration in order to mitigate the soft storey effect in all zones. The stability of a building can be improved by using these lateral load resisting systems.
Artificial Intelligence based Classification of Diseases for Rice Leaf Using CNN model
Authors: M Misba , A Vivek , R Ratheesh , C Aslin
Published: September 2023

Rice cultivation is a crucial industry in India, but it is plagued by various diseases that can damage crops at different stages. These diseases are challenging for farmers to identify accurately due to their limited knowledge and expertise. As a result, the farmers often struggle to take appropriate measures to prevent or manage these diseases, which can result in significant losses in crop yield and quality. Therefore, there is a need for advanced technologies and tools to help farmers accurately identify and manage these diseases, ensuring a sustainable and profitable rice cultivation industry in India. Recent advances in Deep Learning have demonstrated that Convolutional Neural Network models can be highly effective in automatic image recognition tasks. These models have shown great potential in addressing the challenges faced by farmers in identifying diseases in crops such as rice. However, in order to train such models, a large and diverse dataset is required, which may not always be readily available. To address this issue, researchers have created their own dataset of rice leaf disease images, which may be smaller in size but sufficient for the task at hand. To develop their CNN model, they have used a technique called Transfer Learning, which used as a starting point to fine-tune already trained models for a new task. The proposed CNN architecture is based on the VGG-16, a widely used pre-trained model used in computer vision tasks. The researchers trained and tested their model with a dataset obtained from rice fields and the Internet. The results show that the proposed model achieves 92.46% accuracy, demonstrating its potential in accurately detecting rice leaf diseases.
The Significance of artificial intelligence in the early diagnosis of multiple myeloma
Authors: S. S Anisha , A Shajin Nargunam
Published: September 2023

A malignancy known as multiple myeloma develops in a type of white blood cell known as a plasma cell. The plasma cells are responsible for the production of antibodies. In multiple myeloma, healthy blood cells are displaced by malignant plasma cells that build up in the bone marrow. Using machine learning techniques, artificial intelligence has radically changed the world of oncology research. Machine learning is a branch of artificial intelligence that makes use of algorithms to analyse data, draw conclusions from it, and then utilise those conclusions to make decisions in the present. In this study, we explore the potential applications of artificial intelligence in the diagnosis of multiple myeloma and present the most important machine learning and deep learning experiments conducted in the field. One of the most severe haematological cancers worldwide is multiple myeloma.
Detection Classification of Diabetic Retinopathy Using Deep Learning Neural Network
Authors: R Divya , R Sujitha
Published: September 2023

Diabetic Retinopathy (DR) is an eye condition that mainly affects individuals who have diabetes and is one of the important causes of blindness in adults. As the infection progresses, it may lead to permanent loss of vision. Diagnosing diabetic retinopathy manually with the help of an ophthalmologist has been a tedious and a very laborious procedure. This paper not only focuses on diabetic retinopathy detection but also on the analysis of different DR stages, which is performed with the help of Deep Learning (DL) and transfer learning algorithms. Diabetic Retinopathy (DR) is one of the leading causes of blindness for people who have diabetes in the world. Early detection of this disease can essentially decrease its effects on the patient. Dense Net are used on a huge dataset with around 3662 train images to automatically detect which stage DR has progressed. Five DR stages, which are 0 (No DR), 1 (Mild DR), 2 (Moderate), 3 (Severe) and 4 (Proliferative DR) are processed in the proposed work. It presented an AI based smart tele ophthalmology application for diagnosis of diabetic retinopathy. The app has the ability to facilitate the analyses of eye fundus images via deep learning from the Kaggle database using Tensor Flow mathematical library. The app would be useful in promoting health and timely treatment of diabetic retinopathy by clinicians.
Recenzo de la libro: Caligaris, Irene. 2021. Unu lingvo por ĉiuj, unu lingvo de neniu lando: Surkampa esploro pri la esperantaj identecoj. Pisa: Edistudio.
Authors: Giordano Alessio
Published: September 2023

Kial, en la 21-a jarcento, oni daŭre lernas esperanton? Kiajn identecojn kunpartoprenas la esperantistoj? La verko de Irene Caligaris prilumas kel kajn el la duboj, kiuj delonge akompanas la sciencajn esplorojn pri la esperanta medio, ĉu kultur-historiajn, ĉu socilingvistikajn.
Recenzo de la libro: Fiedler, Sabine, kaj Cyril Robert Brosch. 2022. Esperanto: Lingua Franca and Language Community (Studies in World Language Problems 10). Amsterdam kaj Philadelphia: John Benjamins.
Authors: Stria Ida
Published: September 2023

Se mi devus resumi la recenzatan libron en unu frazo, mi dirus, ke ĝi estas ĉio, kion lingvisto devas scii pri la nature funkcianta planlingvo Esperanto. Ĝi fakte prezentas al la leganto detalan enrigardon en la funkciadon de la lingvo surbaze de tute nova, ampleksa materialo. La aŭtoroj estas agnoskitaj lingvistoj, kiuj jam de jaroj esploras pri Esperanto. La recenzata libro estas la rezulto de plurjara laboro kadre de granda eŭropa projekto MIME (Mobility and Inclusion in Multilingual Europe), en kiu la lepsika universitato respondecis pri la studado de la angla kiel interlingvo por Eŭropo. Esperanto venis do nature en la projekton kiel alternativa ilo de komunikado.
Recenzo de la libro: Heller, M., McElhinny, B. (2017). Language, capitalism, colonialism: Toward a critical history. Toronto: University of Toronto Press.
Authors: Fettes Mark
Published: September 2023

Sur paĝo 126 de ĉi tiu libro aperas mia brakhorloĝo. Nu, fakte ne mia, sed simila produkto de la svisa firmao Movado, fotita de la svisa esperantistino Mirejo Grosjean. La foto enkondukas kelkpaĝan pritrakton de Esperanto kaj aliaj planlingvoj, per kiu la aŭtoroj - du kanadaj socilingvistoj kaj/aŭ lingvo-antropologoj - malfermas sian sondadon (en la kvara ĉapitro el ok entute) de la lingvaj dimensioj de 'alternativaj modernecoj', nome 'internaciismo, komunismo kaj faŝismo'.
A study on how to Accelerate Cultivating of Innovative and Entrepreneurial Talents in Higher Vocational Colleges after the Epidemic
Authors: LIU GUO QIANG , Lai PC
Published: September 2023

Innovation and entrepreneurship are becoming more and more prominent after the epidemic. The cultivation of students’ innovative and entrepreneurial ability has become an urgent task for education and training departments. This paper mainly introduces how to improve innovation and entrepreneurship education and focus on the strategies for cultivating innovative and entrepreneurial talents in higher vocational colleges, such as the infiltration of education concepts and talent training models, the integration of innovative and entrepreneurial education and professional education courses, the unification of innovative and entrepreneurial education theories and practices, the teaching and training group building, etc．
Influence of Design on Real Estate Inventories by Members of Kenya Property Developers’ Association in Nairobi County
Authors: Karimi Fridah , Kirera N , Odoyo Fredrick S
Published: September 2023

The purpose of this study was to determine the influence of design on Unsold New Houses held by members of the Kenya Property Developers Association (KPDA). The study adopted a positivist philosophy and descriptive correlational research design. The study population consisted of 4,085 unsold new houses, where a sample size of 364 units was drawn using a multistage random sampling technique. Property managers in this study were the units of observation; hence data was collected through a self-administered questionnaire. Descriptive statistics focused on relative frequency distribution, means, and standard deviation. Inferential statistics included ordinal logistic regression to test hypotheses and one-way ANOVA to assess the differences between group means. The generalized ordinal logistic regression study results revealed that the design of the unsold new house explains 36% of the duration it remained unsold (r2 = 0.36). The findings further indicated that having other bedrooms ensuite (β = -1.548, p < 0.05), having a domestic servant's quarter (β = -1.888, p < 0.05), and having a swimming pool within the property development (β = -2.510, p < 0.05) were significant predictors of the duration of unsold new houses. The study concluded that the design of the unsold new house significantly influences the duration the house remained unsold. The study recommends that property developers should incorporate a swimming pool and domestic servant quarters in their development as well as having other bedrooms ensuite for houses with more than one bedroom.
Evolution of Teaching Radiology on Medical Students
Authors: Akram Wissam
Published: September 2023

Ionizing radiation is widely used in the field of medicine both for diagnosis and treatment. So, Understanding the principles of radiation safety and how to apply them in clinical practice is critical for medical and paramedical staff The study was conducted to assess the knowledge of nursing staff about ionizing radiation and protection from ionizing radiation during the diagnostic and therapeutic examination. In this study, a quantitative descriptive approach and a comprehensive review of previous studies were followed in order to emphasize the importance of teaching medical physics and ionizing radiation science because of its extremely important impact on the nursing staff working in medical institutions and radiological examination centers of both types, diagnostic and therapeutic. Through this study, we noticed that the paramedical staff's knowledge of physics and technology was not sufficient, and from our point of view, it does not meet the needs of healthcare institutions that require a deep understanding of tools and equipment that depend on the principles and laws of physics. We also expect that the nursing staff's lack of knowledge of the physical foundations and laws that are used may have a negative impact on the patients' condition in clinical practice. Thus, there is a need to improve nursing students' knowledge of physics by changing the way biophysics is taught in the nursing curriculum.
Kushite Princess Amun Rhodes I, "Holy Wife of Amun", Ruler of Upper Egypt
Authors: بادي أمل
Published: September 2023

Political conditions in Egypt during the period of the New Egyptian Kingdom (1575-1084 B.C) helped to control to the priesthood of Amoun on religious and political issues, especially in southern Egypt. It elevated the position of the Divine Adoratrix, the wife of Amoun, particularly in the Kushite period in the fifteenth dynasty when Kushite Princesses controlled governing issues in South Egypt on behalf of their brothers, the kings. The Kushite princess Amoun Ridis was the first Divine Adoratrix to take on this important position.
Prevalence and Identification of Cestode Species Recovered from Infected Organs of Lizardfish (Saurida undosquamis)
Authors: Elmajdoub Layla , Emshiheet Kholoud , Abushiba Fatma , Elzwawy Sara , Abusahal Mabrooka
Published: September 2023

192 specimens of the Saurida undosquamis were collected from the local market of Misurata city in Libya. the prevalence rate of cestode helminths in examined fish Saurida undosquamis, was high. Based on the morphological and morphometric characterization represented two species of cestodes were isolated. Of the total examined fish (169, 88%) were infected with (Tetraphyllidean sp. and Trypanorhyncha sp. larvae). The density of cestode helminths was around 6810, and they were collected from the stomach, anterior and posterior parts of the intestine in all seasons, the liver and muscles showed no cestode infection, and a non-significant difference (P> 0.05) were found between cestode density infection of infected organs, this study found a high infection rate with Tetraphyllidean sp. and Trypanorhyncha sp. larvae in the Saurida undosquamis.
Cadmium Telluride (CdTe) Compound and Silicon (Si) Semiconductor Materials Detectors for X-Ray
Authors: Gabasa Hagag , Said Assma , Abdulla Karima , Aghtisa Samah
Published: September 2023

There are different approaches and also materials to construct a detector for x-rays. the available semiconductor materials, Silicon (Si) is mainly used for charged particle detectors and soft X-ray detectors. Cadmium Telluride (CdTe) compound semiconductors for x-ray detectors have experienced a rather rapid development in the last few years, due to their appealing performance. In this paper we review the physical properties of semiconductor detectors for x-ray. In particular, we focus on compound semiconductor detectors. In addition, Si detector has better energy resolution achievement. However, it does not have good detection efficiency for higher energy above (40Kev). While CdTe detector supplies higher detection efficiency for x -rays about 100% for up to 100 keV in energy. The response functions of Si detector to reduce small x-ray, which has limited sensitivity for energy about 30keV. The XR-100T is high performance for x-ray and gamma ray detector by using 241Am (59.5keV), so the cooler are mounted the input FET a feedback components to the Amptek to charge sensitive preamplifier. Both the Si and CdTe detectors are connected to the PX2 combined amplifier and power supply, that was provide the voltage needed to operate XR-100T CdTe. The PX2 T CdTe amplifier has a Rise Time Discrimination circuit, measure the FWHM energy resolution of 55Fe (5.89) the peak in each spectrum hence a graph of energy resolution. Moreover, the Rise Time Discrimination So the escape peak of 55Fe was determined with Si detector was 11.66 keV, also k- sell x-ray energy was calculated to 5.77keV and the Rise Time Discrimination effect was studied on the spectrum when is it switched on and off. Its influence was found in decreasing the noise of the spectrum.
Analisis Kesejahteraan Penerima Zakat Produktif di Desa Sulung Berdasarkan Model CIBEST
Authors: Gusmina Miza , Eva Eva
Published: September 2023

Penelitian bertujuan untuk menganalisis kesejahteraan penerima zakat produktif yang ada di Desa Sulung dengan Model CIBEST. Metode yang akan digunakan di dalam penelitian ini ialah metode deskriptif dan pendekatan kuantitatif. Jenis dan sumber data yang digunakan data primer yang didapat langsung dari sumber aslinya. Peneliti memberikan kuesioner kepada para mustahik yang mendapatkan bantuan dana zakat dari Lembaga Amil Zakat BAZNAS Kabupaten Sambas. Teknik pengambilan sampel dalam penelitian ini manggunakan metode Total Sampling yaitu sampel yang diambil sama dengan total populasi. Seluruh responden akan dianalisis berdasarkan klasifikasi CIBEST Indeks, serta dikelompokkan berdasarkan tingkat spiritual dan materialnya. Hasil perhitungan dengan menggunakan model CIBEST ini mengungkapkan bahwa pendayagunaan zakat produktif oleh BAZNAS sudah berjalan secara efektif. Hasil analisis yang menyatakan keefektifan dari pendayagunaan zakat produktif pada BAZNAS yaitu seluruh penerima zakat produktif berada pada kuadran I.
Afinal, onde estão vocês?
Authors: Petrus Bia
Published: September 2023

O artigo propõe uma reflexão sobre intervenções realizadas no jardim da Faculdade de Belas Artes da cidade do Porto, a partir da articulação entre os conceitos de utopia e de distopia, entendendo o espaço das ações ora como um produto da realidade utópica, ora como espaço cheio de contradições que minam a vivência cotidiana daqueles que ali transitam. Ao observar os efeitos dessas intervenções, entendidas como microações estético-políticas, pergunta-se: como o artístico e seus processos afetam contextos reais, transformando objetividades e subjetividades, numa ordem sensível e interferindo nas relações entre sujeitos e entre sujeito e espaço social? Se as questões emergentes, que nos colocam diariamente diante dos problemas que enfrentamos como humanidade e parte do sistema vivo sobre a superfície da Terra, parecem não estar presentes em alguns lugares do nosso cotidiano, como podemos torná-las visíveis?
Pemodelan Topik Menggunakan n-Gram dan Non-negative Matrix Factorization
Authors: Afidh Razief Perucha Fauzie , Syahrial
Published: September 2023

Pemodelan topik merupakan teknik pembelajaran mesin yang digunakan untuk melihat topik dalam sekumpulan dokumen teks. Pada penelitian ini pemodelan topik yang digunakan adalah Non-Negative Matrix Factorization (NMF) dengan n-gram. Preprocessing seperti penghilangan tanda baca, angka dan stopword diimplementasikan pada penelitian ini. Proses ini dilakukan dengan terlebih dahulu mengubah kata yang terdapat dalam artikel menjadi kata berhuruf kecil. Penelitian ini juga mengeksplorasi keefektifan penerapan unigram, bigram, dan trigram pada pemodelan topik. Pada penelitian ini juga menggunakan coherence value untuk menentukan jumlah topik terbaik yang dapat dibentuk. Data yang digunakan pada penelitian ini berjumlah 53.920 artikel berita yang bersumber dari portal berita RMOL.id dan BeritaSatu.com untuk periode Juli sampai Desember 2022. Visualisasi t-SNE digunakan untuk melihat distribusi pembentukan topik. Berdasarkan hasil penelitian yang dilakukan diperoleh bahwa jumlah topik yang dapat dibentuk dari RMOL.id untuk unigram adalah 15 topik dengan nilai coherence value 0.812748,  bigram adalah 10 topik dengan nilai coherence value 0.835738 dan trigram adalah 7 topik dengan nilai coherence value 0.830572. Sedangkan pada BeritaSatu.com diperoleh 10 topik untuk unigram dengan nilai coherence value 0.799718, bigram 15 topik dengan nilai coherence value 0.788762 dan trigram 15 topik dengan nilai coherence value 0.801935.