bluuebunny/crossref_metadata_2025 huggingface dataset:
Peruntukan Beban Pembuktian di Bawah Enakmen Keterangan Mahkamah Syariah: Satu Penilaian
Authors: bin Saifuddin Suhaizad
Published: April 2021

Enakmen Keterangan Mahkamah Syariah (EKMS) merupakan statut penting bagi menyokong penguatkuasaan undang-undang substantif. Beban pembuktian merupakan salah satu aspek signifikan yang terkandung di dalam enakmen penting ini dan sering dibahaskan penilaiannya. Penulisan ini bertujuan untuk menganalisis peruntukan undang-undang berkaitan beban pembuktian yang terkandung dalam EKMS. Penulisan ini juga berhasrat untuk mengemukakan cadangan penyelesaian ke atas permasalahan yang dikenal pasti. Kerangka penulisan undang-undang tulen berasaskan pendekatan secara doktrinal dan kualitatif merupakan reka bentuk yang diaplikasi. Data penulisanan dikumpul melalui metode temu bual separa struktur dan dokumentasi. Data yang diperoleh dianalisis menerusi metode analisis kandungan secara kritis. Penulisan ini mendapati wujud ketidakjelasan dan kekaburan peruntukan undang-undang berkaitan beban pembuktian dalam peruntukan sedia ada. Masalah tersebut telah mengakibatkan ketidakfahaman dan tafsiran yang berbeza di kalangan pengamal undang-undang syariah berkaitan dengan beban pembuktian. Justeru, penulisanan ini mencadangkan penambahbaikan ke atas peruntukan undang-undang tersebut agar pemakaian beban pembuktian dalam perbicaraan jenayah syariah di negara ini menjadi lebih jelas dan lebih mudah difahami.
Deposition of tantalum carbide on Ti6Al4V alloy by electric discharge treatment
Authors: Burkov А. А. , Kulik M. A.
Published: April 2021

Titanium alloys attract wide attention of researchers due to the unique combination of low density, high strength, corrosion resistance, biocompatibility, etc. Therefore, the study of new methods for processing titanium and the creation of protective coatings seems relevant. Metal-ceramic coatings were obtained by electrospark treatment of a titanium alloy Ti6Al4V in a mixture of titanium granules with tantalum carbide powder. Three mixtures of granules were prepared with a TaC content of 2.4; 4.6 and 6.7 vol.%. Coatings were deposited by rectangular pulses with an energy of 0.33 J and a frequency of 1 kHz for 8 minutes in an argon stream. The increase of the volume fraction of tantalum carbide powder in the mixture of granules from 2.4 to 6.7 vol.% does not lead to a significant increase in cathode gain. The average coating thickness ranged from 29 to 36 microns. Using scanning microscopy and energy dispersive analysis methods, it was found that the coating structure is represented by a metal Ti – Ta – C matrix with large ceramic grains. According to x-ray phase analysis, it was found that tantalum carbide TaC prevails in the coating composition. It content increases with increasing powder concentration in the mixture of granules. In addition to it, there are phases of titanium carbide and tantalum subcarbibide TaC0.6, which are the products of TaC decarburization during its interaction with the titanium melt. With an increase of the tantalum carbide concentration in the mixture of granules, the hardness of TaC/Ti coatings increased from 6.1 to 8.9 GPa, which is 2–3 times higher than that of the Ti6Al4V alloy. Coefficient of friction of coatings was in the range of 0.5–0.9. Dry sliding wear tests showed that TaC/Ti coatings had a wear rate ranging from 0.1·10–5 mm3/Nm to 1.7·10–5 mm3/Nm. Thus, the use of these coatings makes it possible to increase the wear resistance of the Ti6Al4V alloy up to 128 times.
Tendency and seasonality of suicide in Chihuahua, México. A retrospective analysis from 2008 to 2018
Authors: Fernández-López Montserrat , Hernández-Montes Rosa Ivonne , Álvarez Reza Sofía , Flores-Olivares Luis Alberto
Published: April 2021

Introduction. Suicide has shown an international and national trend to increase, mainly in young people, together with seasonal behavior associated with high temperatures. Although Chihuahua saw the highest number of suicides and suicide attempts in 2016, there are no studies documenting their seasonal and trend behavior. Objective. This study sought to analyze the trend and seasonality of completed suicides in the state of Chihuahua from 2008 to 2018. Method. The number of deaths from intentionally self-inflicted injuries was obtained from INEGI. The absolute suicide rate was estimated, and a time series model applied to identify its trend and seasonality. In addition, environmental temperature was used as a predictor variable for the number of suicides through a Poisson model. Results. A trend was found in the completed suicide rate from 2008 to 2018 in men and women, both separately and together (stationary R2 .73, .66 and .69, respectively), together with seasonality in both sexes (p < .002), with the highest figures being recorded in June and July. An increase of 1,028 suicides was found for every 1°C rise in temperature. In the 10-24 and 25-34 age groups, a linear increase in the suicide rate was observed during the period studied (R² > .7, p = .001). Discussion and conclusion. Between 2008 and 2018, the suicide rate increased in the state of Chihuahua, mainly among those aged between 10 and 34. Moreover, suicide rates tend to increase during the months of June and July because of temperature.
INFORMAL INDUSTRIES IN INDIA: PRESENT SCENARIO, GAP AND OPPORTUNITIES BY
Authors: Sankar Jyoti Nath, Dr. Biju Mani Das Krishna Kumar Thakur,
Published: April 2021

India is one of the biggest markets in the world; here mainly two types of industry are in scenario either formal or informal. Whereas informal sector is widespread across the geography and it contributes to the economy of country. Most of the employment comes from this sector; still it is the most neglected sector in India. It is also the most exploited industry in India.

This study aims at gaining an in depth overview of the informal sector in Indian context.
IMPROVED PARTICLE SWAM OPTIMIZATION FOR CROWD SIMULATION USING HYBRID AGENT REINFORCEMENT LEARNING ALGORITHM
Authors: Senthil Kumar Thangavel K. Pavithra, G. Radhamani,
Published: April 2021

In an emergency route planning technique, simulating the dynamic crowd has route capacity constraints and global target of evacuating all crowd evacuees. To stimulate the crowd, the new arena is developed to know the real-time situation to face the crowd evacuation on exit point. The crowd evacuation is done with the process of Hybrid Agent Reinforcement Learning (HARL) algorithm consisting of Improved Multi-Agent Reinforcement Learning (IMARL) and State-Action-Reward-State-Action (SARSA). In the proposed work, the appropriate route selection mechanism focused on finding optimum evacuation route(s) is done in the first phase. Dynamic crowd can also be evacuated to find its way with the support of the HARL process in the second phase. The proposed HARL method can also be implemented with multi-objective improved particle swarm optimization (IPSO) technique for crowd simulation. The experimented results demonstrate the effectiveness of stability in the HARL process, which provides an improved performance for crowd simulation
RIGID TRACKING FOR SCALE AND ROTATION VARYING TARGETS FROM MOVING CAMERA
Authors: Yamuna G. Karthika Pragadeeswari C.,
Published: April 2021

Targets when move rapidly needed to be tracked in many significant fields such as in combat applications. Objects undergoes many scale changes and also undergoes rotation variance. The target when viewed from static position, the size becomes smaller as the target moves farther and farther. Tracking the targets needs more attention and this can be done by Improved optical flow to which feature extraction through Histogram of Oriented Gradients and Random Sample Consensus (RANSAC) algorithm for scale and rotation invariance is added. The performance of the method is measured by its computation time, accuracy and high true positive values and other related parameters simulated in MAT LAB.
ANALYTICAL INVESTIGATIONS OF MECHANICAL PROPERTIES OF SEMI SOLID PROCESSED ALUMINIUM 7075 ALLOY
Authors: Dr. S. Rajesham, Dr. M. Manzoor Hussain S.Venkata Narasimha Rao,
Published: April 2021

At present for industries it is a challenge to produce products of good quality and should have high durability. In this engineering world there is great a great need of various engineering materials to satisfy these engineering needs. The material usage mainly depends on the material strength and properties. Aluminum-7075 alloy is primarily used for transport applications, such as aerospace, maritime and automotive industries, thanks to its good mechanical properties and a low density. For the semi-solid formation of aluminium alloys, a homogenous equiased grain structure is required. The stress mediated melting mechanism is one of the approaches used to achieve such a microstructure.

The present work describes the synthesis of Al 7075 semi solid metal matrix composite reinforced with graphene and the characterization of their mechanical properties.  Graphene is added to aluminium-7075 and samples are prepared both with stirring and without stirring at varying temperatures. The samples are prepared at 6800c, 7100c, 7400c, 7700c, 8000c, 8300c, 8600c, 8900c, 9200c.

At these temperature the material is mostly semi-solid Aluminium 7075 and graphene is added to this semi-solid molten melt and stirred with stirrer. The specimens are prepared according to ASTM standards. The tests like hardness, tensile, impact and compression tests are performed and the values are compared. The tensile power, hardness, compression reduces as its temperature increases. The specimens are analysed using ANSYS software. The specimens with stirring has good mechanical properties than without stirring.  Graphene has good mechanical characteristics such as strength and hardness.
EXPERIMENTAL INVESTIGATION ON A SOLAR AIR HEATER WITH AND WITHOUT OBSTACLE
Authors: Et. al. A. R. Vijay Babu,
Published: April 2021

In this paper convection form of heat transfer is used to convert cold air to hot air. Forced convection is preferred for this experimental analysis; obstacles are also used to analyze the temperature level of air with the help of Air Heating Solar Device (AHSD). Semi Annular fins are used as obstacles for this experimental verification. The outlet temperature and pressure drop of SAH were determined by changing the fin densities with the help of software tool FLUENT. The analysis result shows that the outlet temperature is more and pressure drop was less in the case of SAH with obstacles when compared to the SAH without obstacles.
Predictive Analysis using Convolution Network on Sentiment Analysis of Text Classification using Machine Learning
Authors: Et. al. Vanitha kakollu,
Published: April 2021

Today we have large amounts of textual data to be processed and the procedure involved in classifying text is called natural language processing. The basic goal is to identify whether the text is positive or negative. This process is also called as opinion mining. In this paper, we consider three different data sets and perform sentiment analysis to find the test accuracy. We have three different cases- 1. If the text contains more positive data than negative data then the overall result leans towards positive. 2. If the text contains more negative data than positive data then the overall result leans towards negative. 3. In the final case the number or positive and negative data is nearly equal then we have a neutral output. For sentiment analysis we have several steps like term extraction, feature selection, sentiment classification etc. In this paper the key point of focus is on sentiment analysis by comparing the machine learning approach and lexicon-based approach and their respective accuracy loss graphs.
CABS SERVICE QUALITY INFLUENCE ON CUSTOMER SATISFACTION – A STUDY CONDUCTED ON MAJOR CAB AGGREGATORS IN BENGALURU, INDIA
Authors: Et. al. Kedar Gokhale,
Published: April 2021

The aim of the present study is to determine relationship between the quality of service and customer satisfaction for cab services in Bengaluru city in India. For this, six variables were identified, namely comfort, safety, affordability, extent of service, driver’s behaviour and reliability. Pearson’s correlation test showed that all the variables were positively correlated with customer satisfaction. Six hypotheses were tested to study the effects of these variables on customer satisfaction. Multiple regression showed that the variables exerted a significant effect on customer satisfaction. As much as 97% variance in the customer satisfaction could be explained with the help of six variables that were tested
ANALYSIS OF MULTICAST ROUTING PROTOCOLS FOR HEALTH CARE MONITORING SYSTEM
Authors: Et. al. Joshua Reginald Pullagura,
Published: April 2021

The most important technology we must concentrate on in the different application fields of WSN is health applications and the transmission reliability of health data in multi-hop communication. Short-term health signal failure may be fatal or life-threatening. The topology of an ad hoc network changes regularly due to the node movement and communication in those scenarios depend on the path selected for transfer of information. Since all the nodes are battery-powered, energy-efficient routing should be provided to extend the network's life. In MANET's critical issues include energy usage, QoS (Quality of Services), vulnerability to attacks, and connection stability. Link stability is a topic that needs to be addressed in order to improve communication. Since radio links are generally varied due to node mobility, Link Stability is important to extend the life time. This work gives comparison of three existing multicasting routing protocols that can be used in health monitoring systems. MAODV, LSP-MAODV and PN-SEMRP are compared using NS2 simulation. PN-SEMRP shows better results when compared to the other mechanisms
SUPPLY CHAIN MANAGEMENT AND ITS PRACTICAL IMPACT
Authors: Et. al. Shreyansh Jain,
Published: April 2021

This paper studied about the role of different independent factors on supply chain responsiveness. Here, we considered factors such as joint decision making, information quality and performance risk as three independent variables and supply chain responsiveness as a dependent variable. We tried to survey different supply chain professionals working in different sectors to have an unbiased image in our study.

After applying Pearson corelation in our study, we understood the significance of our independent variables on supply chain responsiveness. The positive significance shows the importance of these factors while working on our dependent variable. All three relationships are showcasing either positive or strong corelation. Finally, we could infer that there are a lot more factors that we can take in to consideration for calculating the impact on supply chain responsiveness in future studies. This will definitely strengthen the case and will help in practical explanation.
POTENTIAL ANALYSIS OF ADDITIVE LAYER MANUFACTURING TECHNOLOGIES USED FOR PROCESSING POLYMER COMPONENTS
Authors: Et. al. Rohit Pandey,
Published: April 2021

In previous years, the usage of additive layer processing grew considerably. Different companies, including motor cars, aerospace, equipment, communications and medical devices utilize additional layer production. However, at present, processed additive layer products comprise less than one percent of all items manufactured. If the prices of additive layer processing systems decline, the manner in which customers communicate with suppliers will be modified. Additional development layer innovations provide the market and culture with different possibilities. It will make the personalized development of strong lightweight goods simpler, and prototypes that with past manufacturing techniques were not feasible. However, the application of this device may be hampered and delayed by numerous obstacles. Many situations require higher costs than conventional approaches for making a component utilizing additive layer production techniques. This study reviews the cost literature for the development of additive layer and attempts to recognize situations in which additive production may be cost-effective and also to identify new methods of minimizing costs in the usage of this technology
Performance Comparison of Fresh and Spray & Wait Protocol through ONE Simulator
Authors: Et. al. Puneet Garg,
Published: April 2021

Opportunistic Networks (OppNets) are becoming the prime interest for researchers day-by-day due to the large scope of further research into it. An opportunistic network is used to transmit data in an environment of intermittent connectivity. OppNet offers a variety of routing protocols based on different strategies. Each protocol has some pros and cons. Among the available ones, Fresh Routing Protocol and Spray-and-wait Routing Protocol are the most efficient routing protocols in terms of performance during data transmission. This paper aims to compare these two different routing protocols through simulation on the ground of standard performance metrics. It is believed that this simulation comparison will help upcoming researchers in the selection of appropriate routing protocol as per their requirement
Info_PCA: A Hybrid Technique to Improve Accuracy by Dimensionality Reduction
Authors: Et. al. Surabhi Lingwal,
Published: April 2021

Principal Component Analysis and Shannon Entropy are some of the most widely used methods for feature extraction and selection. PCA reduces the data to a new subspace with low dimensions by calculating the eigenvectors from eigenvalues out of a covariance matrix and thereby reduces the features to a smaller number capturing the significant information. Shannon entropy is based on probability distribution to calculate the significant information content. Information gain shows the importance of a given attribute in the set of feature vectors. The paper has introduced a hybrid technique Info_PCA which captures the properties of Information gain and PCA that overall reduces the dimensionality and thereby increases the accuracy of the machine learning technique. It also demonstrates the individual implementation of Information gain for feature selection and PCA for dimensionality reduction on two different datasets collected from the UCI machine learning repository. One of the major aims is to determine the important attributes in a given set of training feature vectors to differentiate the classes. The paper has shown a comparative analysis on the classification accuracy obtained by the application of Information Gain, PCA and Info_PCA applied individually on the two different datasets for feature extraction followed by ANN classifier where the results of hybrid technique Info_PCA achieves maximum accuracy and minimum loss in comparison to other feature extraction techniques.
A Survey: Benefits of Mango Leaves and Techniques Used For Evaluvation of Diseases Affecting Mango Leaves
Authors: Et. al. M.Prabu,
Published: April 2021

Agriculture plays a vital role in day to day life for the living organisms in all over the world. There are many plants are identified as medicinal plants in India. This survey aims to give a clear picture of the benefits of mango leaves, how it can be considered to be herbal medicine or home remedy for various diseases. But in spite of its numerous benefits these leaves are subjected to various types of diseases that are caused due to fungal infections. Along with the fungal infection there are climatic factors that affect the growth of these leaves resulting in less production, growth and quality. The factors such as light, temperature, nutrients, rainfall directly or indirectly influence the growth of the tree. Hence the mango leaves has been survived with detailed explanation of techniques in order to detect the diseases based on the factors and techniques that addresses all the existing issues and help in predicting the diseases well in advance.
ENHANCED SECURITY FRAMEWORK FOR THE SMART HOME AUTOMATION SYSTEM
Authors: Et. al. Priyajot,
Published: April 2021

Elderly care as well as enhance the quality of life for seniors, the users must be supplied with a lot of personal information about their homes and personal lives. This promising technology is being blocked by results in security and privacy. With the intent to empower end users, we did semi-struct interviews with 42 potential new and novice Smart Home customers. The issues they were concerned with focused on were connected around attacks on Smart Home data and devices, as well as the effect on users in general, to the importance of keeping their functionality balanced with the expectations of the people in their surroundings. In addition, we use measures from an interdisciplinary point of view to deal with the four topics The paper concludes with a few ideas for dealing with users' concerns, along with ideas for supporting application developers in crafting effective user-oriented digital assistants.
Design and Analysis of Metamaterial based-check board AMC Backed EBG Antenna for Body Placement Applications
Authors: Et. al. Kunapareddy Koteswara Rao,
Published: April 2021

In this paper a compact EBG antenna with Artificial Magnetic Conductor (AMC) is proposed for on body applications. The proposed antenna is designed with single SRR (split ring resonator) and double SRR to differentiate the performance of the proposed antenna. The proposed EBG antenna bending analysis is performed at different angles on human body to attain good radiation characteristics. The footprint of proposed antenna is of 0.2λ0*0.24λ0mm2 and AMC with dimension of 0.48λ0*0.48λ0 mm2.The proposed antenna is obtained good return loss and radiation characteristics when EBG antenna is placed on the human leg with an angle of 300 at corresponding operating frequencies 2.4GHz, 5.8GHz, 9GHz and 9.5GHz respectively. The obtained operating frequencies cover wireless applications such as GPS, ISM, and Radar and satellite communications. The proposed EBG antenna is obtained with high gain 7.05dBi at 9.5GHz operating frequency. The surface current distributions are obtained for the proposed antenna is of 137A/m. Good isometric radiation patterns are observed for the proposed antenna. The SAR analysis is performed when the EBG antenna is placed on the human leg at an angle of 30degree is of 1.23W/kg.
A Compact Dual Notch Frequency Reconfigurable Antenna for WIMAX,DSRC, RADAR and Ku band Communication Applications
Authors: Et. al. Vutukuri Sarvani Duti Rekha,
Published: April 2021

A frequency reconfigurable ultra-wide band antenna with dual notch bands is proposed in this paper. PIN diodes are located on ultra-wide band monopole antenna and are investigated for frequency reconfigurable characteristic of the proposed antenna. Multi-bands and narrow bands have been achieved by different combinations. Proposed antenna is fabricated on FR-4 substrate of dimensions 37 x 40 x 0.8mm3. For the successful combinations, antenna performance parameters like S11 characteristics, surface current distribution, peak gain, radiation efficiency and 2D radiation patterns are analyzed and illustrated in the paper. Peak gain of 4.83dB is obtained in operating band for D1, D2= 0, 1 combination. Radiation efficiency is not less than 70% in the entire operating bands. Results are analyzed experimentally for validating proposed antenna. Simulation based results and measured results are in good agreement.
Corona Virus Detection and Classification with radiograph images using RNN
Authors: Et. al. Dr Moulana Mohammed,
Published: April 2021

We’re working on detecting the symptoms of Corona virus, also known as Covid-19, in this project.COVID-19 is a highly infectious disease that has been declared a Pub- lic Health Emergency and a Pandemic by the World Health Organization.The virus has infected over 25 million people worldwide,which has killed over 840,000 people and threat- ened the lives of millions more. COVID-19 is characterised by a dry cough, sore throat, and a high temperature. It is critical to find quick and accurate results for Covid-19 at this time in order to stop it in its early stages and avoid it from being a problem. Deep learning concepts are being used to analyse and classify symptoms from radiograph im- ages.Chest radiographs are one of the early screening tests to assess the onset of disease since the infection seriously affects the lungs.In this proposal, we used a recurrent neu- ral network model combined with a multi-level thresholding technique to detect Corona virus. One of the machine learn- ing techniques for prediction is the RNN model. A Recur- rent Neural Network is used to decide if the given images belong to Covid-19 during the classification process. This implementation is based on a publicly available dataset of radiograph images.
Design and Development of Enhanced Exam Hall Seating Arrangement Automation System
Authors: A. Sasireka, K. Vijay A. H. Nandhu Kishore,
Published: April 2021

During exam period, it is very hectic task to find out the venue of the examination hall and which seat is allocated to a particular student. Students used to face many problems for finding the exam hall and their seats. Therefore, an exam hall seating arrangement system is needed to computerize the traditional way of preparing the examination hall allotment and generate the hall seating arrangement plan automatically for smooth conduction of exams. The proposed system will guide the students to find out their respective examination hall during their exams. This would also show the respective seat of a student in a particular row of their examination. The other objective of developing this system is to help the students to direct them to their respective examination hall without delays for going on searching for hall plan and their seat allotment. It contains the student, department, subject, staff details, examination hall and their seat allotment. This system will also send the hall number and seat allotted to a particular student through that student’s registered email id. The classifier algorithm is used for efficient generation of seating arrangement and Advanced Encryption System (AES) algorithm is used for password verification of registered users for ensuring high-level security.
DEEP RECURRENT NEURAL NETWORK BASED AUDIO SPEECH RECOGNITION SYSTEM
Authors: Et. al. Savitha G,
Published: April 2021

Speech recognition system has become an integral part of how the computer technologies can be used to influence and improve the human work and activities. These are being used extensively, from personal assistants to self-driving car Human Computer Interfaces (HCIs) and other industries as well. While the most common approach to speech recognition system building is using the Hidden Markov Models (HMMs). The HMM models assume a specific structure of the data and unable to capture temporal dependencies. This paper however presents a unique approach for isolated word recognition based on deep learning models using Recurrent Neural Networks (RNNs) particularly, which can perform end to end speech recognition without any assumption of structure in data using Bidirectional LSTM (BiLSTM). The network proposed in the paper can learn both features in the data and capture temporal dependencies.
SMART ELECTRICITY CONSERVATION SYSTEM USING EFFICIENTNET
Authors: Et. al. Ushasukhanya S,
Published: April 2021

Conservation of electric resource has been one of the important challenges over the decades. Worldwide, many nations are struggling to conserve and to bridge the gap between the demand and production of the resource. Though many measures like several Government acts, replacing existing products with energy conserving products and many solar based systems are being invented and used in practise, the demand and the need to preserve the resource still persists. Hence, this paper focuses on a novel technique to conserve the electric resource using a deep learning technique. The system uses Convolutional Neural Networks to identify and localize humans in the CCTV footages using EfficientNet, a deep transfer learning model. The classifier processes and yields its output to an embedded Arduino microcontroller, after detecting the presence/absence of human. The microcontroller enables/disables the electric power supply in the area of human’s presence/absence, based on the classifier’s output respectively. The system achieves an accuracy percentage of 84.2% in detecting humans in the footages with the subsequent enabling/disabling of electric power resource to conserve electricity.
AWARENESS ON PENSION PLANS-A STUDY OF INVESTORS’ IN BENGALURU CITY
Authors: B.V. Pushpa
Published: April 2021

Individuals make inconsistent, irrational financial decisions mainly due to disproportionate time preferences. Bias and procrastination prevail. Along with a default option, there is a need for a customized plan with individuals' socio-cultural and economic status.  Low participation rates are mainly due to a lack of awareness of pension literacy and behavioral aspects. Individuals have failed to create a corpus to protect themselves for retirement as there is a lack of awareness to suitability of a plan to one’s situation, failure to measure income adequacy at retirement, not able to identify the link between contributions made and pension drawdown, etc. Age and gender differences prevail strongly. Defined contribution plans are likely to dominate in global pension model in the years to come. Individuals are ready to own their risk but have little control and knowledge to cover themselves. Frequent timely and prompt advice or counseling from investment advisors will enable participants to understand the need, identify suitable options and schemes, and provide themselves with sustainable long-term savings. This should convert willingness to participate to real participation.

Keywords: Financial literacy, Pension knowledge, Defined contribution pension plans (DCP), irrational decision making, demographics.
PERFORMANCE COMPARISON OF UNSUPERVISED SEGMENTATION ALGORITHMS ON RICE, GROUNDNUT, AND APPLE PLANT LEAF IMAGES
Authors: Et. al. Rajendra Prasad Bellapu,
Published: April 2021

This paper focuses on plant leaf image segmentation by considering the aspects of various unsupervised segmentation techniques for automatic plant leaf disease detection. The segmented plant leaves are crucial in the process of automatic disease detection, quantification, and classification of plant diseases. Accurate and efficient assessment of plant diseases is required to avoid economic, social, and ecological losses. This may not be easy to achieve in practice due to multiple factors. It is challenging to segment out the affected area from the images of complex background. Thus, a robust semantic segmentation for automatic recognition and analysis of plant leaf disease detection is extremely demanded in the area of precision agriculture. This breakthrough is expected to lead towards the demand for an accurate and reliable technique for plant leaf segmentation. We propose a hybrid variant that incorporates Graph Cut (GC) and Multi-Level Otsu (MOTSU) in this paper. We compare the segmentation performance implemented on rice, groundnut, and apple plant leaf images for various unsupervised segmentation algorithms. Boundary Displacement error (BDe), Global Consistency error (GCe), Variation of Information (VoI), and Probability Rand index (PRi), are the index metrics used to evaluate the performance of the proposed model.  By comparing the outcomes of the simulation, it demonstrates that our proposed technique, Graph Cut based Multi-level Otsu (GCMO), provides better segmentation results as compared to other existing unsupervised algorithms.
EMBRYOTOXICITY AND TERATOGENIC EFFECTS OF PARMOTREMA TINCTORUM (NYL) HALE ON ZEBRAFISH (DANIO RERIO) AND CYTOTOXIC ACTIVITY OF LICHEN EXTRACT ON HEK293T CELL LINE
Authors: Et. al. M. Shenbagam,
Published: April 2021

Parmotrema tinctorum (Nyl) Hale an edible lichen, used as a spice and flavouring agent for meat and vegetable preparations by ethnic groups in India and Nepal. In Zebrafish embryos and larva, the therapeutic applications of P.tinctorum widely reported. However the teratogenic effects not  reported. This study was aimed to examine the toxicity of P.tinctorum on the promising model for toxicity research, the Zebrafish, because their genetic structure is more similar to human beings. Additionally, we have demonstrated a toxic effect of P.tinctorum extract on the human normal cell line (HEK293T) by MTT assay. The methanol extract of P.tinctorum was extracted by Soxhlet and for embryotoxicity and teratogenicity activities, we use different concentrations (50µg/ml – 200µg/ml) of lichen extracts on twelve selected fertilized Zebrafish embryos. The extract did not exhibit any effect on Zebrafish Survival rate, hatching rate, heartbeat and teratogenicity which was similar to control groups. To conclude that, methanol extract of P.tinctorum is found to have a nontoxic property to zebrafish embryo and human normal cell line (HEK293T) and suggests that this might be safe for consumption
9T SRAM CELL WITH MT-SVL TECHNIQUE FOR LEAKAGE POWER REDUCTION
Authors: Et. al. Kothamasu Jyothi,
Published: April 2021

With the technology scaling there is a decrease in transistor size and increase in number of the transistors per a chip. It causes tremendous increase in complexity and the power dissipation of circuits. This paper mainly focuses on reduction of leakage power dissipation in SRAM 9T cells by employing multi threshold self controllable voltage level circuits  (LSVL & USVL). The Simulation results show that with the employment of MT-SVL technique, leakage power is being reduced compared to the improved SVL technique. The overall simulation is done with CMOS 180nm technology, using the tool of Cadence Virtuoso.
An Experimental Study Skills To Enhance Reading Skill
Authors: Dr. S. Gunasekaran Dr.L.Bapitha
Published: April 2021

Reading, Knowledge, Motivation Reading is not only one of the most important skills in language teaching, but also one of the main objectives of learning English in general. Many factors such as students’ background knowledge, motivation, interest, organization of the texts and study skills may affect reading skill. The purpose of this study was to investigate whether teaching study skills would increase students’ reading comprehension ability or not. To achieve this goal an experiment was carried out at Anna University College of Engineering, Ramanathapuram, Tamilnadu, India during the second semester of 2016-2017. The results of the study supported the argument that skills in reading depend on the precise coordination of a number of special reading skills and there is a significant relationship between the knowledge of study skills and reading comprehension.
Robotic Process Automation (RPA): Process prioritization using Cognitive Complexity matrix
Authors: Dr. Prashant Bharge Arunoday Jaju,
Published: April 2021

The process automation using robotic processes automation (RPA) has been witnessing an increasing trend of interest in recent days. However, when it comes to selection of processes for automation, among various factors process complexity is not given enough weightage. Also there are fewer researches regarding process selection and the factors impacting this decision. This research gives a methodology for selecting processes based on the complexity so that the organization can implement RPA with the optimum benefits. With this approach we can prioritize the processes in order to gain the maximum profit from the automation. This approach will also segregate the processes in which RPA automation will not result into significant amount of benefit
Factors impacting Purchase Behaviour of Automobiles Post Covid-19
Authors: Shetty Sachin
Published: April 2021

Vehicle Purchase has been rapidly increasing and since last decade the automobile sector has been growing in double digits in India. There are several factors considered by an individual during the purchase of automobile. With the changing trend and with the pandemic situation safety has also been a key factor that adds into it. This paper tries to examine the factors impacting the purchase behaviour. Initially the literature review aims at finding out the significant variables that act as components in purchase of a vehicle. Subsequently, the paper uses statistical technique of Exploratory factor analysis ( EFA ) to club the different variables into single factor. It was found that 21 variables fall into 6 factors namely Brand trust, Socio-demographic factor, Economic factor, Product and tech factor, Psychographic & safety factor and Govt infra & policies factor
Challenges Faced By the Indian Transportation Sector in Implementing New Age Technologies
Authors: Tripathy Sandip
Published: April 2021

This research paper in its entirety tries to articulate the various types of challenges faced by the Indian Transportation Sector in implementing new age technologies for better control and visibility throughout the entire Supply Chain. It mostly focuses on the road and rail mode of transportation, though briefly it also touch-bases upon the water and air modes. Indian railways and roads position themselves as the third and second largest network respectively worldwide. In addition to a set of questionnaires circulated among individuals working in the logistics domain to capture their point of view, a thorough literature review of the previous works in this field was done to identify the causes – both external and internal to an organization, which affects implementation of digital solutions to present transportation problems. In this paper, we discuss along with others, two of the greatest challenges posed to the digital transformation – firstly, adamant attitude of traditional players operating in this space, who have for long, functioned through traditional processes and legacy systems and secondly, the complexity of the road and rail network running through the length and breadth of the country. Though the average time taken by enterprises to digitize their transportation business has reduced tremendously due to need of remote operations in these unprecedented times during COVID-19, but still there exist some of the challenges which need to be addressed. Some of the major drivers of identifying these challenges are the need to - reduce lead times by setting up a platform/control tower which can automate the management of transportation with minimized touch points between organizations and their customers, need to reduce risk of manipulated data by minimizing human intervention and need to increase customer satisfaction by incorporating functionalities like real-time tracking, automated exception handling and other. The challenges which were identified in this study can be further analysed to improve on it and conceptualize a framework for transforming Indian logistics (majorly the transportation space). This paper is written from the point of view of current scenario of Indian transportation industry.
ANALYZING THE OPERATIONAL AND LOGISTICS REQUIREMENTS BY EVALUATING THE MARKET POTENTIAL FOR E-LOGISTIC SUPPORT PROVIDER
Authors: Ramkrishna Manatkar Nikhil Satpute,
Published: April 2021

continuously 2020. The Indian government has made a declaration that it is working at the approach to build up the new logistics plan in India. The point is to build up the most prudent approach to transport products by 2035.

As we know logistics is a highly diverse gambit consisting many factors and variables, we decided to focus on Trucking segment of logistics in Mumbai region. Mumbai is a city in Maharashtra, India. To know more about the market and its potential we needed to know more about the transporters and manufacturing industries in Mumbai. As transporters in Mumbai can get us about the idea of logistical truck movements inside and outside Mumbai, and the manufacturing industries can suggest us about which type of trucks are required by them according to the raw materials they need or the final products they distribute. Apart from the logistic movement in and out of Mumbai, we also tried to capture the openness of transporter to sign up for e-logistic service provider and try to expand their business by adding a technological aspect to it.

Research contains detailed and verified information of 57 transporters and on all possible combination of types of trucks provided by transporter and their operational routes. Also, we have recognized total of 125 Manufacturing companies from various industries, having one or more plant in or around Mumbai. Also, we classified the 125 companies into 15 Industries These companies have some raw material movements into Mumbai and some finish goods movement from Mumbai to various parts of India.

By analyzing the collected data, we found out which type of truck have how much demand on which route. Also, we could figure out the willingness of transporter to work in collaboration with e-logistics company
AUGMENTED REALITY AND VIRTUAL REALITY IN RETAIL - A BIBLIOMETRIC ANALYSIS
Authors: Bardhan Anasuya
Published: April 2021

Purpose – “Augmented and Virtual Reality” is a trend in retail that is lately catching a lot of attraction. These interactive technologies enhance the retail process by offering a better shopping experience and affects consumer's preference towards the retailers. Retailers need to align their business model to counteract the changing traffic patterns. This study will help in inferring trends, themes researched, identifying the prolific authors, researchers, and present the big picture.

Methodology - To understand the current research state, Biblioshiny and VOS viewer has been employed to conduct a quantitative study on research papers done in the field of AR/VR in retail during the period 1993-2020 from the “Web of Science core database”. 

 

Findings - (1) Increase in publication of papers in the past 27 years, divided into 2 parts: a low exploration period and developmental period. (2) The research covers 38 countries. With respect to the research volume, the top five countries being – (i) “China”, (ii) “the United States”, (iii) “the United Kingdom”, (iv) “Germany”, and (v) “South Korea”. There has been a lot of collaboration between these countries, with maximum collaboration between the USA and China. (3) Virtual Reality, Retailing, Interactivity are amongst the trending keywords in this field in recent years. (4) The main research themes in area of AR/VR in retail mainly focuses on the research directions like – the adoption of the technology, impact on consumer behavior, and performance and user's information control.

 

An overview of present state of academic studies was generated by employing a knowledge-based map which recognises researcher collaboration networks. This study is riveting as it has rarely been examined in this in a new manner.
Application of Block Chain & Artificial Intelligence in E-commerce supply chain to reduce product counterfeiting & increase transparency
Authors: KIRAN KARANDE LAKSHIT JAIN,
Published: April 2021

Product counterfeiting is a major issue in today’s world. These days product counterfeiting leads to around 1.05 lac crore rupees in India per year. As per a report by business standard, if even 50% of product counterfeiting is stopped with authentication, monitored properly and governed, it can save 50,000 crore rupees per year in India itself, then think about whole world. This research paper is based on the use of block chain along with artificial intelligence to curb the problem of product counterfeiting and maintain the transparency. This research paper also demonstrates the use of blockchain using R studio as a platform. R is a programming language mostly for data analytics purposes. So, the implementation of blockchain in R can give a wide exposure to the data to be analyzed and suitable insights and forecasts can also be made. The research findings give a holistic picture of all the variables that affect the supply chain of E-commerce industry. This study helps the supplier side in curbing their loses and also the consumer side in receiving the genuine product that build trust among both the stakeholders
The impact of COVID-19 on Consumer Behaviour on spending pattern with respect to Mobile Phones and the impact of Anti-Chinese Sentiment towards buying of foreign brands
Authors: Tibrewala Punit
Published: April 2021

COVID-19 pandemic has brought the world to a standstill. People are locked in their houses having a very low option to move out during the lockdown period. The objective of the study is to focus on the impact of COVID-19 on consumer behaviour towards the use of mobile phones and their view towards Made in India products. The consumption pattern of individuals might be altered due to COVID-19 as there is no knowledge of when everything will be resumed back to normal. A survey sheet was floated to collect individual data via responses using social media platforms, blogs and calls. These responses would provide data for further analysis to determine the outcome of the study. Hypothesis testing method is used for the data analysis and to interpret the results
A STUDY ON THE USE OF ICT IN PRE SERVICE TEACHER EDUCATION IN DELHI
Authors: Teotia Dr. Anil Kumar
Published: April 2021

In using technology in the classrooms, the efficiency of the teachers is directly proportional to the outcomes it follows. In the present study, the researcher tried to study the impact of ICT on the achievement level (in Mathematics Education) of elementary teacher trainees in Delhi and their opinions about using ICT in the classroom. The elementary teacher trainees of Delhi were the sample population for the current study. The opinions from various teacher educators, parents and teacher trainees were collected. The qualitative and quantitative data collected from different stakeholders were analysed and synthesised. It was found that the learning of all trainees was improved through the use of ICT in the classroom. However, the high achievers were more benefited than the low achievers.

Moreover, trainees think that the use of technology in their classrooms has a positive impact on their academic scores, and they find learning easy with the use of technology. Trainees did not accept the positive role of technology in the learning of co-curricular subjects. Further, trainees with better technological infrastructure availablein institutes performed better on achievement tests. Despite having better technological infrastructure, trainees do not like the idea of total dependency on ICT with the 'no teacher in class’ method. They preferred and voted for the active role of educators in the classrooms.However, parents (mainly mother) consider that ICT has a positive impact on trainees’ learning. The interviews with teacher educators concluded that the trainees' basic writing, reading, calculating etc., were improved significantly by using ICT. However, they refused to accept any pedagogical advantage of using computers/overhead projectors in the teacher training programme.
ROLE OF “HUMAN LIBRARY INTERVENTION” IN CREATING AWARENESS OF DIVERSITY & INCLUSION
Authors: Et. al. Dr. Kasturi R Naik
Published: April 2021

The advent of globalization, workforce mobility, and international projects are generating demands for culturally proficient individuals and post pandemic there is scope of creating awareness of diversity & inclusion across globe using technology. Education, training, and development of these employees begin in the webroom now (Van Dyne, Ang, Livermore, 2010).

Diversity and inclusion efforts tussle since they often attempt to find a one-size-fits-all solution to eradicating bias. The Human Library is making an influence, because their approach is personalized to each individual’s own biases and prejudices. They’re tackling diversity and inclusion one person at a time and now with advent of technology they can do it on a large scale and see the benefits.

The main drive of this paper is to examine whether the education system plays an important role in developing an individual with an open outlook without any discrimination, stereotypes, and prejudice and the important use of the human library as a tool to develop this open outlook. The research objectives of this paper include focusing on the theoretical and practical concepts of emotional intelligence, stereotypes, discrimination, prejudice and establishing a relationship between these concepts and the human library utilizing thorough literature review and consolidation.