Browse Items (11808 total)
Sort by:
-
Analyzing Job Satisfaction, Job Performance, and Attrition in International Business Machines Corporation through Python
Since workers significantly impact the firm's operation, businesses invest heavily in them. They must deliver better and more excellent performance to compete with the increasing competition. Employee performance is becoming more and more important for business success and staying ahead of the competition, so companies are putting more money into things like training, growth centers, and careers. The target audience was the employees working in International Business Machines Corporation. The data was analyzed through the process of Exploratory Data Analysis using Python. There is a 0.002297 link between Job Satisfaction and Performance Rating, and a 0.002572 correlation between Work Life Balance and Performance Rating. The relationship between work-life balance and job involvement is -0.01462, indicating a negative impact on work-life balance for people who are heavily interested in their occupations. The study would help Human Resources Managers formulate their policies and understand the employees better in the current environment. Here, Job Satisfaction and Performance Rating served as mediators, and the findings show that their influence on Attrition is minimal at this firm. 2024 IEEE. -
Analyzing Market Factors for Stock Price Prediction using Deep Learning Techniques
This paper presents a comprehensive study on stock price predictions by integrating market factors and sentiment analysis of news headlines. The research is divided into two modules, each employing distinct methodologies to enhance the accuracy of stock price forecasts. In the first module, market factors are investigated using three advanced algorithms: Long Short-Term Memory (LSTM), Gradient Boosting Decision Trees (GBDT), and Facebook Prophet (FBPROPHET). These algorithms are evaluated based on metric scores such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). The analysis focuses on predicting high and low values of market prices for the period from January to June 2021. The comparative assessment of these algorithms provides insights into their effectiveness in capturing market trends and making precise predictions. In the second module, the paper explores the impact of news headlines on stock prices by extracting sentiment using three distinct algorithms: lexical-based analysis, Naive Bayes, and FinBERT. The sentiment analysis aims to gauge the market sentiment reflected in news articles and assess its influence on stock price movements. Prediction accuracy is calculated for each algorithm, highlighting their strengths in capturing sentiment patterns. 2024 IEEE. -
Analyzing online food delivery industries using pythagorean fuzzy relation and composition
Food and beverages constitute a significant portion of the family expenditure, which motivates the food delivery companies in striving hard to meet the customer needs through their dynamic food delivery apps. The online food ordering system is one of the most profitable marketing strategies for restaurant businesses. The face of the restaurant industry has shifted from the traditional dine-in culture to takeaways, online ordering, and home deliveries. Digital technology and social media have a significant role in ensuring the efficiency and popularity of a food delivery app. The four essential factors for a food delivery company to satisfy the needs of the consumers in day to day life are choice of restaurants, speed of delivery, payment option and quality of service. The objective of this study is to discern and analyse these four essential factors adopted by the leading four food delivery companies and evaluate the perceptions of the consumers. The best online food delivering company is identified using Pythagorean Fuzzy Relation (PFR)and composition. The analysis concludes that Zomato food application is the best in consumers perception.The outcome of the survey is made more efficient by adopting a mathematical approach. Copyright IJHTS. -
Analyzing Risk-Return Trade-Offs Using ARCH and GARCH Models of the BRICS Countries
This study investigates financial markets in BRICS nations (Brazil, Russia, India, China, and South Africa) from 2003 to 2023. It examines mean returns, volatility, skewness, and kurtosis, assessing normality and data stationarity. ARCH-GARCH models uncover conditional heteroskedasticity and volatility clustering. It also explores mean reversion and momentum effects in the Nifty and MOEX indices. Findings show negative, near-zero mean returns, except for SSEC, which is modestly positive. Serial correlation suggests past values impact current returns. Volatility varies, with MOEX and SSEC having higher levels. ARCH-GARCH models indicate volatility clustering and non-normal return distributions. Mean reversion and momentum effects are identified in Nifty and MOEX, benefiting investors, financial institutions, and policymakers. This research informs investment strategies, risk management, and financial forecasts in BRICS economies, contributing to the understanding of the global financial landscape and potential contagion effects. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Analyzing students academic performance using multilayer perceptron model
Identification of the students behavior in the class room environment is very important. It helps the lecturer to identify the needs of the students. It also aids in identifying the strength and weakness of the individual and guide them to improve on their performance. Observing and supervising the students regularly can improve their performance. The data has been collected from 120 students who took the common the course taught by two different lectures. The students were observed based on the internal assignments and quizzes and the model exam given by the respective lecturers. In this paper the students are categorized into different groups based on their performance using Multilayer Perceptron (MLP) and also different factors which are influencing the performance of the students are identified. BEIESP. -
Analyzing the Consumer Buying Behavior by Adapting Artificial Intelligence (AI)
In any business consumers or customers are important part of the market, so it is necessary to attract more customers for increasing the profits. The current research in this area has demonstrated that artificial intelligence (AI) has a substantial impact on the end customer, contrary to the widespread notion that it has more of an impact on industry than other manufacturers. There are many studies on the various applications of AI in analyzing and visualizing the consumer behavior. Thus, it is been observed the behavior of consumer is not same for same businesses, it varies from consumer to consumer. In other respects, AI is changing how consumers act right now. In coming year's use of AI will become common where the human dependable businesses also get automated with time. 2024 IEEE. -
Analyzing the Inter-relationships of Business Recovery Challenges in the Manufacturing Industry: Implications for Post-pandemic Supply Chain Resilience
The COVID-19 pandemic brought about a rapid change in the global business environment, leading to increased risks of supply and demand disruptions. As society and the industry continue to acclimate to the new normal, the contributions of the manufacturing industry are critical in the recovery process. However, the existing literature lacks a framework to analyze the manufacturing sectors challenges during the recovery to enhance supply chain resilience (SCR). To address this gap, this study develops a framework for business recovery, especially in the manufacturing sector. A broad literature examination and expert survey were conducted to identify the critical potential business recovery challenges. Further, the interplay of business recovery challenges was analyzed using mixed methodologies such as total interpretive structure model and the cross-impact matrix multiplication applied to classification (MICMAC) to foster a framework that can assist the manufacturing industry in improving SCR. The study found that challenges like lack of flexible policies for handling disruptions and lack of management support toward building resilience have the highest driving power impeding business recovery. Other challenges, such as lack of reconfiguring production lines, lack of product competencies to meet disturbances, and less adoption of robust technologies are also identified as major challenges. The implications of the study offer valuable insights into global manufacturing industries. It also has significant propositions for the Pacific region. The Pacific region faces unique challenges, including geographic isolation, resource dependency, diverse economies, climate vulnerabilities, and complex trade relationships. The suggested frameworks adaptability and applicability to these regional characteristics enable businesses and policymakers in the Pacific to better understand and address the specific dynamics of post-pandemic recovery, ultimately contributing to enhanced SCR tailored to the regions needs. The study enriches the existing SCR literature by analyzing inter-relationships between business recovery challenges in the manufacturing industrys post-pandemic context. The Author(s) under exclusive licence to Global Institute of Flexible Systems Management 2024. -
Analyzing the interactions among delay factors in construction projects: A multi criteria decision analysis
The construction industry is a crucial sector that drives economic growth and facilitates socio-economic development. However, construction projects often get delayed due to multiple controllable and uncontrollable circumstances. In this scenario, the construction industry is striving for potential solutions to resolve project delays. Thus, the present study objectives to analyze the delay factors that affect the timely accomplishment of construction projects in the context of emerging economies. The study adopts a mixed methodology comprising of Delphi, Total Interpretive Structural Modelling (TISM) and Matrice d' Impacts Croises Multiplication Applique a Classement (MICMAC) method to model the identified delay factors. A Delphi analysis was conducted to finalize the most crucial delay factors to the on-time completion of building projects. The causal relationships and expert interpretations for each identified delay factor were then determined using multi-criteria decision analysis, TISM and MICMAC analysis. The study results highlight that lack of knowledge of newer construction methodologies and lack of project monitoring tools and techniques are positioned at the bottom level of model, which suggests that this delay factor influences others. The study results will help managers resolve the issues of project delays by selecting the most suitable approach. The findings from the study suggest adopting advanced technologies for effective communication, use of analytical tools for resource allocation and waste-scrapping approaches for eliminating delays in construction projects. The Author(s) 2023. -
Analyzing the Market Dynamics of Electrical Appliances with a Special Emphasis on Sustainable Electric Energy
This study looks into the market dynamics of electrical appliances with a special emphasis on sustainable electric energy. The research aims to understand how factors such as technological advancements, consumer behavior, and regulatory policies influence the electrical appliances market. By examining the trends and challenges within this sector, the study highlights the growing importance of sustainability in product development and consumer choices. The main areas of focus include the adoption of energy-efficient technologies, the impact of rising household incomes on appliance usage, and the role of government policies and initiatives in promoting sustainable energy consumption. The findings of the study would provide insights into how the industry can align its practices with environmental goals while meeting the evolving needs of consumers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Analyzing the Performance of Canny Edge Detection on Interpolated Images
Surveillance cameras are extensively used nowadays in many commercial and domestic places to monitor theft, intrusion and other illegal activities. Typically, the cameras are placed at a high position to monitor a large area. Therefore, the captured images include background area in addition to the target objects. Under such situation, the image can be zoomed to focus on the target objects using various interpolation techniques. For further processing of the image, many techniques like edge detection, image sampling and image thresholding etc. are available. Considering edge detection to be a basic step for many application such as Object detection, Object recognition etc, in this work, we analyze the performance of the Canny Edge Detection algorithm on images interpolated using Nearest Neighbour, Bilinear and Bicubic interpolation methods. Canny Edge Detection is applied to the input image and the resultant image is saved for later comparison. The same image is upscaled using interpolation and the Canny Edge Detection algorithm is used on this upscaled image. This image is then resized to the original image size. Both the images are compared to check for their similarity using the Structural Similarity Index Method (SSIM). 2019 IEEE. -
Analyzing the Performance of Conformable and Non-Conformable Patch Antennas
This paper presents a performance analysis between a conventional triangular shaped patch antenna and a future reconfigurable patch antenna. There are different materials with different electronic properties for the simulation of triangular shaped patch antenna. All the materials for the triangular patch antenna are simulated using FEKO tool. Materials selected for triangular patch antenna are Copper, Single-wall Carbon Nano-tube (SCNT), Multiple-wall Carbon Nano-tube (MCNT) and Graphene. For the futuristic antennas, cotton fabric based reconfigurable patch antenna is also analyzed and compared with triangular shaped patch antenna. Graphene based triangular patch antenna has been analyzed best out of other materials. Reconfigurable cotton fabric-based patch antenna provides better bandwidth and results are validated through simulation and experimental setup. 2024 IEEE. -
Analyzing the Prospects of Blockchain in Healthcare Industry
Deployment of secured healthcare information is a major challenge in a web-based environment. eHealth services are subjected to same security threats as other services. The purpose of blockchain is to provide a structure and security to the organization data. Healthcare data deals with confidential information. The medical records can be well organized and empower their propagation in a secured manner through the usage of blockchain technology. The study throws light on providing security of health services through blockchain technology. The authors have analyzed the various aspects of role of blockchain in healthcare through an extensive literature review. The application of blockchain in COVID-19 has also been analyzed and discussed in the study. Further application of blockchain in Indian healthcare has been highlighted in the paper. The study provides suggestions for strengthening the healthcare system by blending machine learning, artificial intelligence, big data, and IoT with blockchain. 2022 Shilpa Srivastava et al. -
Analyzing the therapeutic significance of Strelitzia reginae Banks: Exploring its physico-chemical properties, elemental makeup, and antimicrobial activity
Plants constituting biologically active molecules with curative value have overtime showed advantage as subject of researches. Strelitzia reginae (Bird of Paradise) is a member of the Strelitziaceae family. Several South African tribes used plant parts to treat the venereal diseases and inflamed glands. The study aimed to investigate therapeutic potential of leaf and root extracts of S. reginae by assessing the physico-chemical properties, elemental analysis. Elemental analysis was carried out by Atomic Absorption Spectrometry (AAS) method, quantitative phytochemical analysis was carried out using, Gas Chromatography and Mass Spectrometry (GC-MS) analysis. The leaf and root of S. reginae were extracted using soxhlet technique of extraction and was further concentrated with a rotary evaporator. Standard protocols assessed the plants elemental compounds, physico-chemical properties, qualitative and quantitative phytochemicals, GC-MS analysis, antioxidant activity using DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay, phosphomolybdate assay, ferric reducing power assay (FRAP), metal chelating assay, and antimicrobial potential by well diffusion test. The results of AAS exhibited that the leaf and root contain more calcium and less of cadmium content. Preliminary phytoconstituents showed the presence of medicinally important alkaloids, anthraquinones, tannins, carbohydrates, flavonoids, saponins, phenols, proteins, and amino acids. The quantitative phytochemical analysis revealed that the leaf has higher total phenolic, flavonoid, chlorophyll, carbohydrates, protein, and proline contents than root. GC-MS analysis verifies the existence of bioactive components like squalene, hexatriacontane, phytol, hexacosane, heptacosane, and octacosane. DPPH, phosphomolybdate assay, FRAP and metal chelating antioxidant analysis revealed excellent activity in leaf and in root sample. As various South African tribes employed plant parts to treat sexual diseases and swollen glands, the antimicrobial property was investigated for the first time using a well-diffusion approach, and both plant parts revealed significant antibacterial and antifungal efficacy against recognized strains. The current study showed S. reginaes therapeutic potential and asked for more pharmacological and biological research to boost the importance of the worlds unevaluated herbal plants. 2024, Indian journals. All rights reserved. -
Analyzing the Virtual Reality Experiential Dimensions at the Game Centers of Tourist Destinations
Virtual Reality (VR) games have attracted the attention of customers lately since they have been offering the most immersive experience through amusement park rides such as VR roller coasters and VR games related to adventure, thrill, scare, etc. Bangalore being a gem of the tourist destination and an IT hub was chosen for the study as it has the greatest potential of offering various VR experiences to the customers. The top 6 of Bangalore's VR game centers were selected based on the popularity and review count from Trip Advisor and Google reviews websites. Analyzing user-generated content has become an intriguing part of business research to find valuable marketing insights for better decisionmaking. The empirical findings show that the majority of the customers are extremely satisfied with the VR experiences and illusion emerges to be the major influencing factors for experiential satisfaction and customers are ready to spend for VR when the VR experiential dimensions meet the expected standards. 2024, Journal of Toursm & Development. All rights reserved. -
Anchored ferrocene based heterogeneous electrocatalyst for the synthesis of benzimidazoles
A facile and sustainable electrochemical synthetic strategy for phenyl benzimidazoles has been developed using a ferrocene-based electrocatalyst anchored on Toray carbon paper (TCP) coated with conducting polymeric film. The developed electrode was used for the electrochemical dehydrogenative cyclization reaction of o-phenylene diamine and benzaldehyde using lithium perchlorate/acetonitrile as electrolyte. The surface characteristic properties of the developed electrode were characterized by FESEM, Optical profilometer and X-ray photoelectron spectroscopy. Electron transfer mechanism of the anchored ferrocene-based electrocatalyst was thoroughly studied. To determine the efficacy of the catalyst, the electron transfer coefficient (0.5) and apparent rate constant 41.4 s?1 were determined. The cyclic voltammetry studies reveal that the electrochemical oxidation peak for the synthesis of benzimidazole occurs at 0.48 V. The formation of the product was confirmed by Gas chromatography and Nuclear Magnetic Resonance spectroscopy. A comparison chart is presented for the green metrics and sustainability of the present strategy with other electrochemical approach. 2022 Elsevier Ltd -
Anchored ferrocene based heterogeneous electrocatalyst for the synthesis of benzimidazoles /
Electrochimica Acta, Vol.435, ISSN No: 0013-4686.
A facile and sustainable electrochemical synthetic strategy for phenyl <a href="https://www.sciencedirect.com/topics/chemistry/benzimidazole" title="Learn more about benzimidazoles from ScienceDirect's AI-generated Topic Pages" class="topic-link">benzimidazoles</a> has been developed using a ferrocene-based <a href="https://www.sciencedirect.com/topics/chemistry/electrocatalyst" title="Learn more about electrocatalyst from ScienceDirect's AI-generated Topic Pages" class="topic-link">electrocatalyst</a> anchored on Toray carbon paper (TCP) coated with conducting polymeric film. The developed electrode was used for the electrochemical dehydrogenative <a href="https://www.sciencedirect.com/topics/chemistry/cyclization-reaction" title="Learn more about cyclization reaction from ScienceDirect's AI-generated Topic Pages" class="topic-link">cyclization reaction</a> of </span><em>o</em><span>-phenylene <a href="https://www.sciencedirect.com/topics/chemistry/diamine" title="Learn more about diamine from ScienceDirect's AI-generated Topic Pages" class="topic-link">diamine</a> and <a href="https://www.sciencedirect.com/topics/chemistry/benzaldehyde" title="Learn more about benzaldehyde from ScienceDirect's AI-generated Topic Pages" class="topic-link">benzaldehyde</a> using lithium perchlorate/acetonitrile as electrolyte. The surface characteristic properties of the developed electrode were characterized by <a href="https://www.sciencedirect.com/topics/chemistry/field-emission-scanning-electron-microscopy" title="Learn more about FESEM from ScienceDirect's AI-generated Topic Pages" class="topic-link">FESEM</a>, Optical profilometer and X-ray photoelectron spectroscopy. </span> -
Android security issues and solutions
Android operating system uses the permission-based model which allows Android applications to access user information, system information, device information and external resources of Smartphone. The developer needs to declare the permissions for the Android application. The user needs to accept these permissions for successful installation of an Android application. These permissions are declarations. At the time of installation, if the permissions are allowed by the user, the app can access resources and information anytime. It need not re-request for permissions again. Android OS is susceptible to various security attacks due to its weakness in security. This paper tells about the misuse of app permissions using Shared User ID, how two-factor authentications fail due to inappropriate and improper usage of app permissions using spyware, data theft in Android applications, security breaches or attacks in Android and analysis of Android, iOS and Windows operating system regarding its security. 2017 IEEE. -
-
Animal-Assisted Therapy : Effect on Neuropsychological Functioning, Depression and Emotion Regulation
The mere presence of a dog in a therapeutic setup is known to bring about positive newlineoutcomes, so when incorporated into therapy, dogs can bring multifarious benefits that are not entirely tapped upon. There also exist cultural differences in the perception towards and acceptance of animals which limits the generalisability of western literature. This research aimed to study the effect of animal-assisted therapy, with therapy dogs, on depression, emotional newlineregulation and neuropsychological functioning of individuals. A pretest-posttest experimental research design was used wherein 42 participants were matched and randomly divided into experimental and control groups. Both the groups received therapeutic interventions once a week, for 45 minutes, over a period of 2 months, however, only the experimental group received animal-assisted therapy. Beck Depression Inventory-II, Difficulties in Emotion Regulation Scale newlineand NIMHANS Neuropsychology Battery were used to gauge the level of depression, emotion newlineregulation and neuropsychological functioning before and after the intervention. The findings reveal that both the experimental and control group saw a significant improvement in their level of depression and emotion regulation, however, only the experimental group showed a significant improvement in all the measured domains of neuropsychological functioning. No newlinesignificant changes were observed in the domains of neuropsychological functioning of the control group. The results help validate the animal-assisted therapy interventions provided to improve the individuals neuropsychological functioning, and emotion regulation and alleviate depression. Further implications are identified and discussed as per the results. -
Animal-assisted therapy for children and adolescents with neurodevelopmental disorders: A review
The increase in neurodevelopmental disorders presents the need for complementary and alternative treatment modalities to support well-being in the maximum possible way. This narrative review was conducted with the aim to explore how animal-assisted therapy as a complementary treatment approach is beneficial for children and adolescents with neurodevelopmental disorders. A search in various databases was conducted to identify articles published in the field of animal-assisted interventions. The review comprised of a total of 32 studies. The discussion of the results was presented in terms of different therapy animals incorporated into the therapeutic environment. The review indicated that animal-assisted therapy has the potential to improve symptoms and various psycho-social variables in individuals suffering from different developmental disabilities. 2024, IGI Global. All rights reserved.