bluuebunny/crossref_metadata_2025 huggingface dataset:
Cataloging of Road Traffic Signs (Building Deep learning model and Android Application)
Authors: Reddy G. Akhil
Published: June 2022

Abstract- The following research centers on the disciplines of applied science such as computer vision, machine learning. As a result of an increase in the usage and popularity of automobiles in numerous cities, the incorporation of intelligent traffic sign recognition technology into these automobiles has become an absolute necessity. The concern arises from drivers' incompetence to notice traffic signs under different circumstances on time. If this problem could be resolved, it may result in a drastic decline in the overall death toll from severe incidents. Thus, the identification of traffic indicators turns out to be the primary focus. Adopting a system that can automatically recognize traffic signs and enlighten the driver is essential, especially when drivers are exhausted, ill or intractable. Hence, the transition of a hazard-involved habitat into a safe and sound habitat requires extensive technological assistance. For a very long time, AI computations have been utilized in a variety of applications. A more precise, information-driven process, such as this one, can be incredibly beneficial for public authorities and citizens seeking to adapt more rapidly. Lastly, this thesis depicts that our new approach is more accurate than the previous ones at predicting traffic signs. Keywords- Torchvision, Opencv, ResNet, Image augmentation, CNN, Performance Metrics
Fake News Detection Using Machine Learning
Authors: A Hemalatha
Published: June 2022

Abstract: The role of social media in our day to day life has increased rapidly in recent years. Information quality in social media is an increasingly important issue, but web-scale data hinders experts’ ability to assess and correct much of the inaccurate content, or “fake news”, present in these platforms. It is now used not only for social interaction, but also as an important platform for exchanging information and news. Twitter, Facebook a micro-blogging service, connects millions of users around the world and allows for the real-time propagation of information and news. The fake news on social media and various other media is wide spreading and is a matter of serious concern due to its ability to cause a lot of social and national damage with destruction impacts. A lot of research is already focused on detecting it. A human being is unable to detect all these fake news. Detecting fake news is an important step. This process will result in feature extraction and vectorization; we propose using Python scikit-learn library to perform tokenization and feature extraction of text data, because this library contains useful tools like Count Vectorizer and Tiff Vectorizer. Then, we will perform feature selection methods, to experiment and choose the best fit features to obtain the highest precision, according to confusion matrix results. A feature analysis then identifies features that are most predictive for crowdsourced and journalistic accuracy assessments, results of which are consistent with prior work. We aim to provide the user with the ability to classify the news as “fake” or “real”.
Resonate: Website on Text to Speech
Authors: Wankhade Gauri
Published: June 2022

Abstract: Synthesizing speech is quite complex as it is heavily reliant on language. Meaning, the language processing section in a TTS system inherently has the largest chunk of linguistic knowledge for a particular language. The technical as well as theoretical challenges faced while building such a high-quality system can be quite daunting and hard to navigate. To ensure that the system has relevant and updated linguistic information, one must make sure it has access to the most natural and unrestricted text to ensure quality and authenticity. We will also need extensive studies to achieve the same. At the heart of this software engine lies an OCR Engine (Optical Character Recognizer) which inherits crucial morphological operations required for image conditioning & transformation, accompanied with python libraries used for character classification. Further the processed textual data is transformed into speech signals using various Text-to-Speech synthesis techniques
Design and Implementation of Phase Shifter for Wireless Communication
Authors: Rajeswari P. , Sushmitha P. , Divya E. , Jensila A. Sherin
Published: June 2022

Abstract: Phase shifters are common microwave devices that are widely used to control the phase of a microwave signal in mobile satellite systems, microwave instrumentation and measurement systems, modulators, noise cancellation systems, frequency converters, electronic beam scanning phase arrays, microwave imaging, and many other industrial applications is used for. Phase shifters are passive devices used to perform variable phase changes in the wave propagating through it. Phase shifters require compact size, low cost and low insertion loss in the desired bandwidth. The size of the phase shifters is a crucial parameter, especially in the design of portable microwave devices, due to the space constraints. The significantly higher insertion loss of phase shifters used in a transmitter causes a significant reduction in transmitting power levels, while it causes a severe drop in signal to noise ratio when the phase shifter is a part of the receiver.. Phase shifters are essential components in phased array antennas for wireless and Radio Detection And Ranging (RADAR) applications. Loaded line phase shifter, reflective line phase shifter and switched line phase shifters are the most commonly used. The electrical performance of a phase shifter is specified in terms of insertion loss, phase error, operating bandwidth and power handling capacity.. Emerging wireless systems have transceivers that require compact and cost effective phase shifters. Physical size and weight of phase shifters are the major issues in mobile and the wireless applications. Therefore, miniaturization of phase shifters has become an important objective of radio frequency (RF) designers to provide portability and affordability in wireless/mobile systems. The present research work mainly focuses on planar phase shifter design with linear phase shift. In this a Defected Ground Structures (DGS) is proposed where as ,Monolithic Microwave Integrated Circuits (MMIC), Micro Electro Mechanical Systems (MEMS) and fractals have emerged as the possible techniques for miniaturization of RF systems and antennas. However the existence of defected cells on the ground plane may limit the use of DGS based phase shifters. MMIC technology increases the cost and complexity of manufacturing whereas MEMS based phase shifter is prone to limited life and yield. In this thesis, fractal techniques are adapted to design and develop miniaturized phase shifters for wireless applications.
Robust Classification of Cardiac Arrhythmia Using Machine Learning
Authors: T G Yashaswini , G K Dr. Ravi Kumar , D Ms. Sindhu
Published: June 2022

Abstract: Machine Learning (ML) is developing progressively in the healthcare industry. The classifying of electrocardiogram (ECG) results depending on Cardiac Arrhythmia is one such instance, where ECG record's the heart's rhythm & electric activity. Two ML techniques, Random Forest (RF) and Convolution Neural Network (CNN) are employed in the presented work to yield rapid & effective categorization of heartbeats. The heartbeats are divided into five classes applying the PTB Diagnostic ECG Database plus the MIT-BIH Arrhythmia Collection. Both datasets are massive, with data being unbalanced for all five classes. The balancing of data is done using both oversampling & under sampling approaches to bring the data equal for each class. Based on performance indicators like f1-score, precision, recall, & accuracy, a comparison will be done among RF and CNN methods. Keywords: ECG, Cardiac Arrhythmia, RF, CNN
Optimized ANN using GA for Solar Power Prediction
Authors: Jain Prajesh , Roy Rejo , Varghese Albert John
Published: June 2022

Abstract: Renewable energy sources are not widely adopted due to their variability. Solar Power prediction is one such technique that can predict the solar power to be generated in the near future. Artificial Intelligence-based techniques are also used widely for power prediction. Short-term prediction is of much interest nowadays as it can help in scheduling activities. In this paper, a solar power prediction is done using Genetic Algorithm with ANN to help better understand the various concepts involved in power prediction. Artificial Neural Networks has shown much progress in the field of prediction. Power prediction proves to be beneficial for users who want to reduce their dependence on grid power. Keywords: Genetic Algorithm, Solar Power, Backpropagation, Solar Power Prediction, ANN
Detection of Ambulance Using Computer Vision
Authors: W Aishwarya
Published: June 2022

Abstract: The number of vehicles has increased in recent days. Managing this huge number of vehicles is a tedious process. Traffic Signals are used to control the flow of the vehicles in an orderly manner. Sometimes an ambulance may need to wait for long time in a traffic signal and if it waits for too long, it would put the patient’s life at risk. Traffic police can manually identify an ambulance and try to clear the traffic jam, but it is not possible with today’s enormous vehicles. Detection of Ambulance using Computer Vision is an application of computer vision and image processing which is capable of extracting images of vehicles and detecting ambulance. It is implemented using Python, OpenCV, TensorFlow and CNN. It captures the live feed of traffic using a camera and extract the vehicles. Then it is classified as an ambulance or non-ambulance vehicle. By automating this process, it is possible to clear a way for an ambulance that is waiting in a traffic signal.
Classification of MNIST Image Dataset Using Improved Convolutional Neural Network
Authors: Chattyopadhyay Neela
Published: June 2022

Abstract— Convolutional Neural Network (CNN) holds the current research interest in the ever-evolving image classification field. Accurate classifying the image data with minimum of time is highly desired. But the traditional CNN architecture often fails to generate the appropriate outcome for large dataset. So, a modified approach of CNN is proposed here which is the combination of data augmentation and batch normalization embedded with CNN. Now a days identifying or classifying digits accurately with variety of modes is really a task of challenge. The advantages of the proposed approach are noted when it is applied to the popular MNIST dataset used for digit classification. The proposed approach has been compared with some existing techniques and results infer that the validation, training loss and testing accuracy of the proposed approach are more superior as compared to the state-of-art approaches.
Fabric Color and Design Identification for Vision Impaired
Authors: Gayathri S. , Venkatesh G. , Akash S. , Manjula P.
Published: June 2022

Abstract - The weave pattern (texture) of woven fabric is considered to be an important element in the design and production of high-quality fabric. Traditionally, the recognition of woven fabric has many challenges due to its visual cues made by hand. In addition, methods based on pre-machine learning algorithms depend directly on manual features, which are timeconsuming and erroneous processes. Therefore, the default system is required to be divided into layers of woven fabric to improve productivity. In this paper, we propose an in-depth study model based on data extraction and a transfer method for the separation and recognition of woven fabrics. The model uses a residual network (ResNet), where the fabric texture features are automatically extracted and segmented in a way that ends. We tested the results of our model using test metrics such as accuracy, approximate accuracy, and F1 score. Keywords – Artificial intelligence, color, design, fabric and image processing
Performance of Glass Fiber, Basalt Fiber: Subjected to Fire
Authors: Mhaske Prasad. B. , Rathi Dr. V. R.
Published: June 2022

Abstract— Over the decades, there was a widespread increase in the use of fiber in concrete for improving its properties such as tensile strength and ductility. The fiber reinforced concrete is also used in retrofitting existing concrete structures. Dispersed fiber reinforcement of concrete improves specific properties and one of them is fire resistance. In numerous research was proven that glass fiber and basalt fiber can inhibit or partly prevent concrete from explosive spalling. New kind of fiber may be be used as dispersed reinforcement are chopped basalt fiber (BF) and glass fiber with ability to improve not only physical and mechanical properties of concrete but also to resist fire . Basalt is rock with suitable properties for resistance to high temperatures, as low coefficient of thermal expansion and stability up to 600 °C to 700 °C. Glass fiber has benefits of getting higher tensile strength and fire resistant properties, thus reducing the loss of damage during fire accident of concrete structures. Concrete mixes with various doses of cement and chopped basalt fiber and glass fiber had been investigated in this study. Properties of fresh and hardened concrete had been examined and evaluated temperatures.Due to large damages of concrete structure it was not possible to measure changes of porous system evaluated by spacing factor after thermal load. Compressive strength was examined before and after thermal load. Special thermal regimes with maximum temperature 200 °C, 300 °C,400˚C and 500 °C were applied. Results showed that chopped basalt fiber and glass fiber have positive impact not only on mechanical properties of concrete but also on its fire resistance. Two specific doses of chopped basalt fiber and glass fiber were tested but further research is in progress. Many studies are under way in this modern world in construction fields and seen that use of fiber reinforced concrete can lead to more effective and efficient construction material. Keywords— Chopped basalt fiber (BF), Glass fiber, Thermal load, fire resistance, spacing factor.
Smart ATM Pin Recovery System Using Fingerprint Identification
Authors: Seekoti Sruthi
Published: June 2022

Abstract— In ATM machines the user is identified by inserting an ATM card and authentication is provided by the customer entering a PIN. The PIN provided by the customer is compared with the recorded reference PIN within the bank Server. If the customer forgets the PIN after 3 trials ATM cards are blocked, to reactivate he needs to attend the bank and dothe formalities which could be a time consuming job. So fingerprint biometric is introduced to cut back this sort of error. This project aims at exploring the system to secure ATM pins and passwords with the fingerprint data specified only the legitimate user can access the pins and passwords by providing the valid fingerprint.
Car Number Plate Detection from Livestream
Authors: Gujjula Karthik Reddy
Published: June 2022

Abstract- As of late there has been an expansion in the quantity of vehicles and a few methods of transports accessible in the street organizations. Also, consequently need to screen the traffic have become a gigantic issue. Different strategies have been executed on the traffic the executives and its reconnaissance. For this issue the number plate recognition is useful as it is perhaps the main methodologies for managing the traffic utilizing a few advanced procedures. Programmed Number Plate Recognition (ANPR) framework is perhaps the best answer for this issue. In our country regularly number plates with different text styles are being used which add to intricacy of understanding tag as framework should be made for all regions. In this gave work an overview on mechanized. amount plate acknowledgment method is introduced. In this undertaking we do an investigation of the current ANPR frameworks.
A Smart Wearable Guiding Device for The Visually Impaired People
Authors: Vivek K P Venkat
Published: June 2022

Abstract— The "Smart Wearable Guiding Device for the Visually Impaired People" is designed to help blind individuals overcome their lack of vision by using other senses like sound and touch. It alerts the blind user of a major hurdle via audio and vibrating signals. According to the World Health Organization, 39 million individuals globally are considered to be blind. They have a lot of difficulties in their everyday routines. As a result, the project's goal is to provide a low-cost, highefficiency method of assisting the visually handicapped in navigating with a little more ease, quickness, and assurance. This Arduino based gadget will assist the blind in navigating without the use of a stick, which might be inconvenient for them. They may just wear it as a wristband or fabric, and it will work quite precisely with little to no practice. A ringer is also included in the system, which emits a warning sound and generates vibration signals. The system uses sound and vibration signals to warn the user about impending dangers. The frequency of both sound and vibration signals increases as the range between elastic glove and obstacles decreases. The design incorporates a buzzer that emits an audible alarm and a motor that produces vibration signals, as well as the ability to transmit notifications to the appropriate person in the event of a crisis. As a result, the study objective is to provide a low-cost, high-efficiency method of assisting blind people to travel with more ease, pace, and assurance. This design provides a low-cost, robust, portable solution for routes with a self-evidently quick reaction time.
Artificial Intelligence in 3D Bio Printing
Authors: K Pramod , AP Anjima
Published: June 2022

Abstract: 3D printing in full three-dimensional printing also known as additive manufacturing is the process of making three-dimensional solid objects from a digital file. The creation of a 3D printed object is achieved using additive processes. In an additive process, an object is created by laying down successive layers of material until the object is created. Each of these layers can be seen as a thinly sliced cross-section of the object.3D printing is the opposite of subtractive manufacturing which is cutting out / hollowing out a piece of metal or plastic with for instance a milling machine.3D printing enables you to produce complex shapes using less material than traditional manufacturing methods. As a result, 3D printing creates less material wastage. “3D Bio printing” or “bio printing” is a form of additive manufacturing that uses cells and biomaterials instead of traditional metals and plastics to create 3D constructs that are functional 3D tissues. But unlike 3D printing, bio printers print with cells and biomaterials, creating organ like structures that let living cells multiply. These biomaterials are called bio-inks, and they mimic the composition of our tissues. Bio printing can be applied to a variety of areas including but not limited to regenerative medicine, drug discovery and development, and 3D cell culture
Sky Cultivation Using Remote and Solar Power Source
Authors: Shivani Y.
Published: June 2022

Abstract— How to grow more food in less space with less water is the main concept involved in this project work. The former who doesn’t have more land can adopt this system by which more land can be created to produce more food than existing land. Rolling type of sky container garden concept is presented here which can be exposed to the sun with water and fertilizer feeding accessibility.A mini module of giant wheel structure is constructed with 8 compartments for cultivating the crops, the idea of choosing this kind of mechanism is to grow more crops in less ground place/area. This rotary type of multi soil containers attached to the main structure of wheel mechanism operates on a simple wheel mechanism that can minimize the ground area or volume required for cultivating the food items like vegetables, grains, etc. The wheel mechanism is attached to the shaft of high torque DC motor at its centre point at certain height, now this motor is controlled through a remote control unit designed with RF modules and mini embedded systems. The control circuit built with 89C2051 chip & relays is designed to rotate the wheel either in clock wise or in anti-clock wise such that hanging containers attached to this mechanism can be positioned to the ground level accessible point for watering and other maintenance activities. Hanging containers filled with soil are constructed with acrylic sheets. Since it is a prototype module, the basic concept of 8 hanging type of small soil containers are used and are attached to the moving wheel for demo purpose. But for real time applications giant wheels can be constructed with less expenditure. The structure of mechanism occupies very less ground place such that the vacant place also can be used for cultivation. Solar energy is used to drive the wheel, for this purpose, 10W panel is used and its output is used to charge the battery such that in absence of Sun also the mechanism can be activated.
Organization of Modular Training in Education
Authors: Kizi Ismatova Yulduz Numan
Published: June 2022

Annotation: Modular learning is a method of organizing the learning process based on the modular presentation of educational information. The essence of modular teaching is that the content of teaching is divided into autonomous organizational and methodological modules, the content and scope of which can vary depending on the didactic goals, profile and level of students. The combination of modules should provide the necessary degree of flexibility and freedom in teaching (and independent learning) a particular category of students and in selecting and assembling specific learning material needed to achieve specific didactic and professional goals. Keywords: credit module system, educational skills, credits, educational content, knowledge, skills and competencies.
Implementing Effective Techniques of Communicative Approach in English Language Teaching
Authors: Ibodullayevna Murodova Mutabar
Published: June 2022

Abstract: In the contemporary age of high professional requirements such as excellent communicative skills, the pressure on the learners to develop their communicative skills of English is rather imperative. The need for successful learning of communicative skills of English language suggests communicative ability to be the goal of language teaching. In other words, to teach English language using communicative approach becomes essential. The article presents the issues of implementing the most effective techniques of communicative method to the teaching process of language learners.
Evaluation of the antifungal powers of five plant species of the genus Terminalia on strains responsible for candidiasis
Authors: BOLOU Gbouhoury Eric-Kévin , YAO Konan , AGRE Don Josette , NGUESSAN Désirée Ruth Constance , ZIRIHI Guédé Noel , DJAMAN Allico Joseph
Published: June 2022

Background: Candidiasis is a fungal disease caused by Candida albicans, a yeast that preferentially affects mucous membranes. These diseases are more and more recurrent because of the generalized decline in immunity and the appearance of resistance to classical antifungal drugs. Therefore, fighting against therapeutic failures becomes necessary. The objective of this study is to contribute to the fight against candidiasis through the research of new antifungal molecules. To do so, the hydroalcoholic extracts of Terminalia catappa, Terminalia glaucescens, Terminalia ivorensis, Terminalia mantaly and Terminalia superba, five plant species used in traditional medicine against dermatoses, were tested on the in vitro growth of resistant strains of Candida albicans. In addition, the polyphenol composition of these plants was carried out in order to evaluate their protective powers.

Methods: The antifungal tests were performed by the solid-state dilution method. While the determination of polyphenols was performed by the photometric method.

Results: The results showed an inhibition of the growth of germs by four plants except Terminalia catappa. The minimum inhibitory concentrations (MIC) obtained are as follows: MIC (T. ivorensis) =0.25 mg/mL; MIC (T. glaucescens) =0.50 mg/mL; MIC (T. superba) = 4 mg/ML; MIC (T. mantaly) = 2 mg/mL.

Conclusion: This study indicates that T. ivorensis is the most active and has the highest content of phenolic compounds. This plant could be a source of effective molecules in the treatment of candidiasis.

Keywords: Candida albicans, candidiasis, Terminalia, antifungal, polyphenol,
Evaluation of Awareness and Knowledge of Pharmacovigilance amongst Final Year Students of Rivers State College of Health Science and Technology, Nigeria
Authors: Bagbi B. M. , George D. M. , Alagala M. B.
Published: June 2022

Adverse drug reactions (ADRs) till date are still considered as one of the main problems of drug therapy. Pharmacovigilance is the monitoring of drug safety by means of spontaneous adverse-effect reporting systems, case control and cohort studies.

This study evaluated the levels of awareness and knowledge of pharmacovigilance (i.e., ADR reporting) amongst final year students of Rivers State College of Health Science and Technology, Port Harcourt, Nigeria. It was a cross sectional awareness and knowledge survey amongst 200 students from the eight Schools of the institution. Specially adapted and structured questionnaires were administered to the students to obtain information on their levels of awareness and knowledge on reporting of ADRs. Simple descriptive statistics was used to analyze the data that were obtained. The result showed that over 72% of the students from each of the Schools had good knowledge of ADR, about 62% were aware of ADR reporting system, while less than 50% had knowledge of the process of reporting ADRs.

Final year students of College of Health Science and Technology, Port Harcourt have good knowledge of ADR. However, their awareness of the reporting system and particularly the process of reporting (pharmacovigilance) is poor and needs improvement.

Keywords: Awareness, adverse drug reaction, pharmacovigilance
Quantum Dots: A New Hope for the Pharmaceutical Field
Authors: Bhurbhure Om , Ghormade Vaishnavi , Katekar Vinayak , Sangule Dipali , Dhage Shivprasad , Boralkar Vrushabh , Padole Tejaswini
Published: June 2022

Quantum dots (QDs) are nanoparticles that have been developed for a number of biological and biomedical applications, such as drug delivery and simultaneous imaging of several cells. As a result of their unique physicochemical features, QDs have shown remarkable potential in receptor-based targeting. Functionalized QDs (f-QDs) are nano-sized smart systems that can deliver a wide spectrum of bioactive. Surface modified fluorescent carbon QDs has received interest as a targeting ligand for achieving cellular targeting with increased specificity. Several surface-designed and conjugated fluorescent carbon QDs are currently being investigated for cancer treatment, and the results are awaited with bated breath. This review emphasizes different synthesis methods, their characterizations, and different applications of QDs in cancer therapies.

Keywords: Quantum dots, Synthesis, Medical applications.
The Relationship between Nutritional Status and Degree of Pneumonia in Toddlers at Universitas Kristen Indonesia General Hospital
Authors: Adriani Ance , Simarmata Vidi Posdo
Published: June 2022

Pneumonia is an acute respiratory infection that majorly causes the death of children in the world, especially in developing countries. Malnourished is a risk factor for pneumonia in children under five years. This study aims to determine the association between nutritional status and pneumonia severity in children under five years in the Universitas Kristen Indonesia General Hospital. The design of this study was an analytical cross-sectional. The data was collected from December 2016 – to January 2017 in central to the medical record of UKI General Hospital. The subject was all infants hospitalized with pneumonia from 2013 to 2015. The indicator used for nutritional status was based on weight for height according to WHO 2007 chart. Pneumonia was found most in 13 – 24 months (36,6%). Thirteen of 82 children with normal nutritional status and 24/82 children with undernutrition had severe pneumonia (p = 0,025). Undernutrition status was significantly associated with the severity of pneumonia.

Keywords: nutritional status, the severity of pneumonia, children under five years
A Two-Sequence, Four-Period, Crossover, Full-Replicate Study to Demonstrate Bioequivalence of Carbamazepine Extended-Release Tablets in Healthy Subjects under Fasting and Fed Conditions
Authors: Salunke Shashank , Birla Ashish , Chaudhari Sandip , Makwana Manasvi , Waghmare Kailash , Shah Paresh , Shelke Sanjay
Published: June 2022

Carbamazepine is a first-line antiepileptic drug (AED) used for the treatment of partial and tonic-clonic seizures. We conducted an open label, balanced, randomized, two-treatment, two-sequence, four-period, single oral dose, full-replicate crossover study to assess and compare the  bioequivalence of  test  product  Carbamazepine extended release tablets USP 400 mg with reference  product Tegretol®-XR 400 mg (Carbamazepine extended release tablets), respectively in  healthy subjects under fasting and fed conditions. Blood samples were collected pre-dose and at regular intervals post-dose up to 240.00 hours. The plasma concentration was analyzed by a validated LC-MS/MS method and the reference-scaled and the unscaled procedure was used to determine bioequivalence for the pharmacokinetics parameters, Cmax, AUC0–t, AUC0-inf, Tmax, T½, Kel and AUC extrapolated was calculated. The results showed that the geometric mean ratios of Cmax, AUC0–t and AUC0-inf were 113.04%, 108.33% and 108.15% respectively, in the fasting conditions and 113.99%, 110.13% and 111.41%, respectively, in the fed conditions and the 90% confidence intervals were all within the range of 80.00% to 125.00%. It can be concluded from the result that the test product Carbamazepine extended release tablets based on osmotic release system (OROS) are bioequivalent to the reference product Tegretol®-XR tablets.

Keywords:  Bioequivalence, Carbamazepine, Sodium Channel Modulators and Epilepsy
Formulation and Evaluation of Floating In-Situ Gel of Nicardipine Hydrochloride
Authors: Patel Tarun , Desai Sharav , Jain Hitesh , Meshram Dhananjay , Rahevar Komal
Published: June 2022

The present research work aimed to formulate and evaluate a gastro retentive in situ gelling system of Nicardipine Hydrochloride using Sodium Alginate as gelling polymer, HPMC K100M as release retard polymer, calcium carbonate as a cross-linking agent, and tri-sodium citrate as fluidity enhancer agent to treat hypertension. The mechanism for the floatation was based on ionic cross-linking. Several evaluation tests were carried out for pre and final formulation evaluation. Based on the outcomes white-colored, viscous solution of uniform consistency was obtained. Batch B1 was very well prepared for the ability to control long-term drug release. The drug content was found to be > 97 %, the viscosities were in the acceptable range suitable for swallowing, and pH was found to be in the range of 7.33 – 7.68 which was compatible with oral digestion. Design expert 13 Software was used to derive results of interaction and responses based on the concentration of polymer and statistical analysis. The optimized formulation i.e., Batch B1 (0.6 % w/v and 0.5 % w/v HPMC K100M) showed a slow drug release of 96.44 % up to 12 hours. The best fit model for the drug release followed the Higuchi model which explained that the drug release occurred by the Fiskian mechanism i.e., a combination of both diffusion and erosion. The in-situ gel prepared can ultimately provide prolonged release, enhance the bioavailability of the drug and increase patient compliance.

Keywords: - In situ gel, Ionic cross linking, Sodium alginate, HPMC K100M, Nicardipine Hydrochloride.
Hematological and Biochemical Investigations of Green Synthesized Reduced Graphene Oxide Carbon Nanoparticles on Acetaminophen Induced Male Albino Rats.
Authors: Soumen Paul  , MousumiMitra  , Nilufar Yasmin  , Chandradipa  Ghosh  , Dilip Kumar Nandi
Published: June 2022

The  aim  of  this  study  is  to  evaluate  the  protective  activity  of  green-synthesized   Reduced  graphene  oxide  carbon nanoparticles   (RGO-CNP)   from   Asparagus   racemosus   (shatamuli)   by   hematological   and   biochemical   assessments   on acetaminophen  induced uremic rats. 36 animals were divided into six groups including a control group, acetaminophen  induced uremic  group  and nanoparticle  treatment  groups.  Nanoparticle  treated  four groups  were intraperitonealyco-administered  RGO- CNP at doses of 0.5, 1.0, 2.0 and 4.0 mg/kg bw and acetaminophen  at 500 mg/kg ofbw for 14 days respectively.  Hematological analysis revealed that there was significant decrease (p<0.05) in Red Blood Cells (RBCs), Hemoglobin (Hb), with acetaminophen induced Group II.  Co-administration  of green synthesized  RGO and acetaminophen  on nanoparticle  treating groups showed the effective  protectivity  and  significant  (p<0.05)  recovery  in  the  hematological  alterations.  Other  hematological  parameters including- WBC, Platelet, Hematocrit, MCH and MCHC remained within the reference range and no significant alterations were observed.  There  was a significant  increase  in plasma  ALT, AST, serum urea and creatinine  levels  (p< 0.05)  in uremic  group (Group II) compare to control (Group I).The alterations were further resettled to the higher dose of RGO treated groups (Group V and VI). The other tested biochemical  parameters  ALP, total bilirubin, direct bilirubin, Serum triglyceride  and cholesterol  levels were not significantly  altered when compared  with control Group I. In conclusion,  it is established  that RGO possess protective response  against  acetaminophen  induced  toxicity  as  dose  responsive  manners,  which  is  supported  by  haematological  and biochemical  observations.  This  promising  effect  suggests  the  potential  applicability  of RGO  as therapeutics  in drug  delivery systems to reduce the toxicity.
Comparison of Working and Non-Working Women in Terms of Marital Satisfaction and Quality of Life
Authors: Vivek Kumar Jha  , Rajbir Singh
Published: June 2022

The research aimed to equate working and non-working women with respect to their recognition and quality of life. Method: A selection of 160 women (80 working and 80 non-working) were selected for the research, using unique inclusion criteria. The data were compiled using the Miller Scale for Social Affection, the Updated Dyadic Scale for Adaptations, the Extensive Scale for Marriage Happiness and the WHO Standard for Life. Descriptive figures, multivariate variance analysis, Pearson's coefficients of association and a multiple regression study evaluate results is used for study. Results: The results showed substantial disparities in group, with working people showing enhanced interpersonal partnerships, adaptation, marital stability and strengthened expectations in the quality of life and the usage of spouse violence, sexual attacks and physical injuries for dispute resolution. Results of the study of regression found that 42.2% and 16.9% of the variances in lives of working people and non-worker people were influenced by emotional cut-off, a self-differentiation factor. In non-workers, 33% of the variation in the standard of life was  reflected by physical attack  as a dispute resolution strategy.  There were substantial disparities between  working  and  non-working  women.  An  important  discovery,  while  working  women  appeared  to  show  improved affection, was that most women in both categories show low adjustment with their husbands. Conclusion: It may be argued that employees have a higher standard of life than non-workers who are exploited most frequently by partners.
REAL-TIME AUTOMATED CONTOUR BASED MOTION TRACKING USING A SINGLE-CAMERA FOR UPPER LIMB ANGULAR MOTION MEASUREMENT
Authors: Akhavizadegan Alireza , Idna Idris Mohd Yamani , Bin Razak Zaidi , Binti Mazlan Mazlina , Binti Hamzah Norhamizan , Abdul Wahab Ainuddin Wahid , Hussain Mehdi
Published: June 2022

Upper limb angular motion measurement is particularly a subject of interest in the field of rehabilitation. It is commonly measured manually by physiotherapist via goniometer to monitor stroke patient’s progress. However, manual measurement has many inherent drawbacks such as the need to have both patient and physiotherapist to be at the same place. In this paper, an automated real-time single-camera upper limb angular motion measuring system is proposed for home-based rehabilitation to aid physiotherapist to monitor patient’s progress. The measurement of concern are angle measurement of elbow extension, elbow flexion, wrist flexion and wrist extension. To do this, we propose a method that utilized predefined coordinate points extracted from the contours of the object named as contour based motion tracking. The proposed method overcome problems of prior target tracking techniques such as Kalman filter, Optical flow and Cam-shift. The proposed method includes skin region segmentation and arm modelling for motion tracking. Prior skin segmentation techniques suffer from fixed threshold value set by the user. Therefore, we introduce dynamic threshold based on the lower and upper threshold boundary of isolated skin regions from the background. To ensure the reliability of our skin segmentation method, we compare them with four different related algorithms. The result shows that our skin segmentation method outperformed the prior method with 93% detection accuracy. Following the segmentation, we model the arm motion tracking by formulating mathematical equation of various points and motion velocities to track the arm. We then model the wrist and elbow position to estimate arm angular motion. The method is put together and tested with real human subject and other test settings. The result shows that our proposed method able to produce an accurate and reliable reading of +-1.25 average range of error from actual physiotherapist reading.
CONTENT-BASED FEATURE FUSION REPRESENTATION FOR MARINE INVERTEBRATES
Authors: Mustaffa Mas Rina , Mohd Norowi Noris , Yee Sim May
Published: June 2022

Marine species representation and retrieval is crucial for its studies and conservation. The images of these animals are usually captured underwater with complex background, at different angle, position, and size, which makes it very hard to provide a good representation with the current methods. Most of the current methods only support content-based representation for marine life images with clear background (taken in laboratory or in environments which have been set up), containing just one animal in an image, or the animal is positioned nicely at the centre of the image. Responding to these important needs, a multi-feature method for Content-based Image Retrieval (CBIR) that employs colour, shape, and texture information of marine life images is proposed. The colour feature vectors are obtained by extracting first and second order of Colour Moments. Shape information is constructed through the implementation of Discrete Wavelet transform up to four sub-bands and the extraction of Canny edge feature. Texture features are obtained with the Zernike Moments (ZM) of order four and the extraction of few Grey Level Co-occurrence Matrix properties. We conducted two experiments to determine the best order of ZM as well as to measure the retrieval performance of the proposed descriptor. Retrieval results based on marine invertebrate and Fish4Knowledge datasets clearly shown that the proposed method has effectively obtained the best precision value at 11 standard recall levels (72.42%) and MAP value (67.7%). The proposed method is further measured based on the statistical two-tailed paired t-test and has revealed a significant improvement in retrieval effectiveness.
MINTERM AND IMPLICANT SELECTION CRITERIA FOR DIRECT COVER ALGORITHMS AND OFF-BASED MINTERM ORDERING
Authors: AKAR Hakan , BAŞÇİFTÇİ Fatih
Published: June 2022

This paper presents a new method for minimization of logic functions. We summarized minterm and implicant selection rules for direct cover algorithms and introduced OFF based ordering method. As other minterm and implicant selection algorithms use ON minterms and runs in minimization phase, they may not find real isolated minterms for insignificant functions. The proposed method uses OFF minterms for ordering minterms. Thus insignificant functions including Don’t Care minterms, could be handled easily with this approach. Results revealed that although proposed algorithm use running time in reordering process, it saves much time in simplification process. In addition, output functions are more simplified with OFF based ordering method.
AN EXTENSION OF THE OUTLIER MAP FOR VISUALIZING THE CLASSIFICATION RESULTS OF THE MULTI-CLASS SUPPORT VECTOR MACHINE
Authors: Mohammadi Mandana , Sarmad Majid , Arghami Naser Reza
Published: June 2022

The main objective of this study is a graphical display of the results of the high (as well as the low) dimensional multi-class support vector machine classification. Additionally, we will visually be able to detect the outliers and misclassified observations by using this graphical tool. The “outlier map” as a successful graphical outlier detection tool of robust statistics is extended in this paper. In fact, this is a bilateral extension concerning the misclassified and outlying observations recognition. The most important feature of this extension is creating two types of discriminative boundaries to segregate the data and detect the outlying observations. For this purpose, we employed the simple but efficient concept of the “confidence interval”, which is computed for the mean of decision function of support vector machine and then, “thresholding” technique. After that, the efficiency of the outlier map in terms of the preciseness of the correct outlier identification has been tested by the classification accuracy. Moreover, we deployed the margin width “before” and “after” outlier detection as the other criterion to assess the preciseness of the correct outlier identification. We conducted an empirical study based on the proposed method on the simulated and several well-known real datasets. It shows the effectiveness of our proposed method by increasing the “margin width” and gaining a higher classification accuracy.
TWO-STEP MODEL FOR EMOTION DETECTION ON TWITTER USERS: A COVID-19 CASE STUDY IN MALAYSIA
Authors: Abdul Razak Chempaka Seri , Ab Hamid Siti Hafizah , Meon Hasni , A/P Subramaniam Hema , Anuar Nor Badrul
Published: June 2022

Human emotion is often a reflection of one’s behaviour that leads to awareness of one’s mental health. Emotion detection on Twitter users specifically gains attention as it generates information that is useful in the field of psychology and linguistics. However, most existing works related to the subject analysed the emotion of a tweet based on the number of keywords or phrases in it, thus resulting in false annotations and eventually false judgement of the user’s emotion. This paper proposes a two-step model with high and reliable accuracy to detect the emotion of Twitter users based on the semantic meaning of the tweets they posted. The first step classified the emotion of each tweet using four different deep learning techniques. The second step detected the emotion of the user based on the proposed statistical post-level features and a boosting technique. Then, Kappa’s agreement score method was implemented to validate both models. The first step achieved 0.9482 in accuracy while the second step achieved 0.9683 in accuracy. To further validate such highly accurate result, a case study was conducted, and a web-based system was developed to analyse the emotion of college students during the COVID-19 pandemic. Additionally, our analysis corresponded to most of the current reports on the pandemic which further proved the reliability of the developed model.
Value relevance of comprehensive income: Tax avoidance and derivative instruments
Authors: Firmansyah Amrie , Fadlil Arditiya , Wijaya Suparna , Irawan Ferry , Wibowo Puji , Mabrur Azas
Published: June 2022

The existence of comprehensive income as the adoption of IFRS, which has been carried out in Indonesia since 2012, has resulted in this figure information as one of the important information used by investors. Company policies originating from operating and non-operating activities can affect financial information quality. This study deals with the effect of tax avoidance and derivative instruments on the value relevance of comprehensive income. Research data is derived from the financial data of non-financial companies listed on the Indonesia Stock Exchange (IDX) from 2012 to 2019, sourced from www.idx.co.id and finance.yahoo.com. This study’s total number of samples is 202 observations through purposive sampling with several criteria. Data in this research is included cross-section data so that the hypothesis testing employed in this research is ordinary least square regression analysis. This study finds that tax avoidance and derivative instruments are not associated with the value relevance of comprehensive income. This study suggests that investors’ investment decisions are not influenced by information on tax avoidance and ownership of derivative instruments. However, tax avoidance is positively associated with value relevance using the book value of equity basis, while derivative instruments ownership is negatively associated with value relevance with the comparable basis.
Anemia ferropénica refractaria como presentación temprana de gastritis autoinmune en un adolescente
Authors: Beltrán Ramírez María Camila , Vera-Chamorro Jose Fernando , Espinosa Saltaren Lina María , Hani Amador Albis Cecilia
Published: June 2022

La gastritis autoinmune es una enfermedad subdiagnosticada en la población pediátrica. Lo anterior se debe a la ausencia de signos y síntomas específicos y manifestaciones clínicas tardías. Recientemente se ha identificado la anemia ferropénica como una manifestación hematológica precoz, lo que permite un enfoque diagnóstico temprano. Se presenta el caso de un adolescente colombiano, sin antecedentes de autoinmunidad, con ferropenia refractaria, en el que se realizaron estudios de extensión y se documentaron biopsias y serología compatible con gastritis autoinmune, con requerimiento de hierro parenteral en su evolución. Esta patología es subdiagnosticada en nuestro medio, ya que el diagnóstico temprano requiere un alto índice de sospecha, lo que permite la prevención de las complicaciones asociadas.
Linfoma de canal anal, reporte de caso y revisión de la literatura
Authors: Romo Sanchez Julian Andrés , Covelli Salazar Laura Ximena , López Bello Laura Alejandra , Figueroa Avendaño Carlos Edgar , Baquero Zamarra David Ricardo , Recamán Pinzón Andrea Camila , Garzón Olarte Horacio Humberto
Published: June 2022

Introducción: los tumores primarios del canal anal diferentes a carcinomas son entidades poco frecuentes; dentro de estos, los linfomas del canal anal son extremadamente raros y generan un reto tanto diagnóstico como terapéutico para el coloproctólogo.

Presentación de caso: se presenta a continuación un caso clínico de un paciente con virus de inmunodeficiencia humana (VIH) positivo con proctalgia y sensación de masa a nivel perianal, se documentó por resonancia magnética un engrosamiento concéntrico de las paredes del recto inferior, con realización de colonoscopia y biopsias con histopatología compatible con linfoma plasmablástico, por lo que se realizó una colostomía derivativa y, posteriormente, se indicó por el servicio de hematología una quimioterapia con esquema EPOCH.

Discusión: el linfoma de ano representa el 0,2 % de los tumores anorrectales, la mayoría de estos corresponde a linfomas no Hodgkin, y es aún más rara la enfermedad de Hodgkin a nivel anorrectal. La población con mayor riesgo de presentar esta entidad es los pacientes con VIH positivo, como el paciente descrito en el caso, aunque existen otros factores asociados descritos en la literatura.