“ Pandu ” Vyadhi is described in Ayurveda, having many clinical features similar to different types of anemia as mentioned in Modern text."Pandu" means a white colour mixed with yellowish Tinge as mentioned in Amarakosha. According to Charaka Samhita- In this disease the skin ofpatient isdiscoloured as Pandu or like haridra or greenish tinge. According to Sushruta Samhita in all types of Pandu body of the patient is more Pandu (shwetarakta or shweta pita).So it is named as Pandu. In Ayurveda Charaka has mentioned it as Rasavaha Srotodushti. Susruta has mentioned it as RaktavahaSrotodushti. A prominent diagnostic feature of Pandu roga is the pallor on the skin which occurs due to the quantitative and qualitative deficiency of raktudhatu(1).Besides the various etiological factors Aaharajahetu and ViharajaHetu plays an important role. In this modern era, people are unaware of their day-to-day life style. There is a drastic change in their livings. And this has made their life more complicated and which are leading for occurrence for many disease. Factors affecting manifestation of disease are change in the life style, high population, socio economic cause, stress, uncontrolled diet, addictions and lot more. According to Ayurveda, the best treatment for all the disease is nidanparivarjan means to avoid all the causative factors. So in order to make people disease free and to make people aware, review study of dincharya as nidanparivarjan of panduvyadhi has been presented in this paper. Key words : Pandu, Lifestyle,Dincharya, Nidanparivarjan, PathyaApthya.

Effective and efficient organizational performance is the aim which any organization wants to achieve. Enterprise Resource Planning (ERP) Systems is one of the key factors that contributes to the operational success of an organization, especially onewith larger operations. This paper presents an evaluation of the ERP systems functionalities and the perceived benefits on organizational performance. The paper has alsoinvestigated how American University of Nigeria implementedtheir ERP system and how it helps them improve their day to day business processes. Furthermore, the paper looks into the challenges,success factors, failures, and propose recommendations on how to improve ERP implementations. The method used in collecting data isinterview and questionnaires. The paper contributes to discussion on ERP implementation in organizations.

On the web social networks (OSNs) have encountered enormous Growth for later a long time What's more get a accepted portal for hundreds of a large number for web clients. These OSNs the table magnetic methods to advanced social connections and majority of the data sharing, as well as raise An amount of security and protection issues. Same time OSNs permit clients should limit right will impart data, they presently don't give any system should authorize protection worries In information connected with numerous clients. On the web social Networks (OSNs), which pull in many million individuals to utilize each day, likewise incredibly augment OSN users’ social circles Eventually Tom's perusing companion proposals. OSN users’ existing social relationship could make portrayed Likewise 1-hop trust relationship, and further secure a multi-hop trust chain throughout those suggestion transform. Similarly as those same Similarly as what kin as a rule knowledge in the Everyday life, the social relationship in cyberspaces would possibly structured by OSN users’ imparted attributes, e. G., colleagues, crew members, or classmates, which demonstrates those attribute-based suggestion methodology might prompt more fine grained social connections the middle of strangers. Unfortunately, security worries brought up in the suggestion procedure obstruct those developments for OSN users’ companion circis siliquastrum. A few OSN clients can't should reveal their personalities and their friends’ data of the open space. This one task may be spurred Toward the distinguishment of the need for a better grain Also that's only the tip of the iceberg customize security to information production for social networks. It proposes a protection security plan that not just keeps those revelations for personality of clients as well as the revelation from claiming chosen features to users' profiles. A singular client cam wood select feature of his/her profiles that if not a chance to be uncovered to others. Long range interpersonal communication may be modelled Concerning illustration graphs to which clients need aid hubs Also offers need aid labels. Labels are indicated possibly as touchy or as non-sensitive. It treats hub labels both similarly as foundation information a foe might possess, Also Likewise touchy data that need should make secured. It likewise displays protection security calculations that consider chart information with a chance to be distributed Previously, An manifestation such-and-such a foe who possesses data around An node's neighbourhood can't securely induce its personality and its touchy labels. It demonstrates that our result is effective, proficient What's more versatile same time putting forth stronger protection certifications over the individuals over Past exploration.

In 20st century the people wants the world on their hands. Internet of Things (IoT) is an ideal emerging technology to influence the internet and communication technologies, traditionally in the object-oriented paradigm everything in the world is considered as an object, but in the Internet of Things everything in the world is considered as a smart object, and allows them to communicate each other through the internet technologies. The Internet of Things can be described as connecting everyday objects like smart-phones, Internet TVs, sensors and actuators to the Internet where the devices are intelligently connected enabling new forms of communication between things and people. The home appliances are controlled by the Arduino which receives commands from the Internet, which operates according to the commands received from the mobile application via the internet. In our proposed system, the home server is built upon an Internet technology which receives commands from the client and the command is processed via Arduino, which allows a user to control and monitor sensors related to the home by using any Android capable smart phone or via the internet.

An analysis is carried out to study the heat transfer in unsteady two-dimensional boundary layer flow of a magnetohydrodynamics (MHD) second grade fluid over a porous oscillating stretching surface embedded in porous medium. The flow is induced due to infinite elastic sheet which is stretched periodically. With the help of dimensionless variables, the governing flow equations are reduced to a system of non-linear partial differential equations. This system has been solved numerically using the finite difference scheme, in which a coordinate transformation is used to transform the semi-infinite physical space to a bounded computational domain. The influence of the involved parameters on the flow, the temperature distribution, the skin-friction coefficient and the local Nusselt number is shown and discussed in detail. The study reveals that an oscillatory sheet embedded in a fluid-saturated porous medium generates oscillatory motion in the fluid. The amplitude and phase of oscillations depends on the rheology of the fluid as well as on the other parameters coming through imposed boundary conditions, inclusion of body force term and permeability of the porous medium. It is found that amplitude of flow velocity increases with increasing viscoelastic and mass suction/injection parameters. However, it decreases with increasing the strength of the applied magnetic field. Moreover, the temperature of fluid is a decreasing function of viscoelastic parameter, mass suction/injection parameter and Prandtl number.

Wireless Sensor Networks (WSNs) have gained significant attention in various real-time applications, such as smart cities, healthcare, precision agriculture, and disaster monitoring. However, the major limitation of WSNs is their constrained energy resources, as sensor nodes operate on limited battery power. This paper proposes an optimized routing protocol that dynamically selects the shortest and most energy-efficient path for data transmission. Our approach integrates an adaptive clustering mechanism, machine learning-based energy prediction, and a reinforcement learning (RL) model to enhance network lifetime and minimize energy wastage. The proposed algorithm is evaluated using extensive simulations on the NS-3 simulator and benchmarked against existing protocols such as LEACH, PEGASIS, and TEEN. Experimental results demonstrate that our algorithm extends network lifetime by 40%, reduces energy consumption per transmission by 30%, and improves the packet delivery ratio (PDR) by 15%. Keywords Wireless Sensor Networks (WSN), Energy Optimization, Adaptive Routing, Machine Learning, Reinforcement Learning, Network Lifetime, Data Transmission I. INTRODUCTION Wireless Sensor Networks (WSNs) consist of numerous spatially distributed sensor nodes that collect and transmit environmental data. These networks are widely applied in environmental monitoring, healthcare, smart grids, industrial automation, and military surveillance. Despite their benefits, WSNs face significant challenges due to limited energy resources, inefficient data routing, and communication overhead. Energy consumption in WSNs primarily occurs during data transmission, reception, and computation. Traditional routing protocols, such as LEACH (Low-Energy Adaptive Clustering Hierarchy) and PEGASIS (Power-Efficient Gathering in Sensor Information Systems), suffer from uneven energy distribution and high node failure rates. Therefore, optimizing routing protocols to extend network lifetime while maintaining efficient data transmission is essential. In this paper, we introduce a novel Energy-Efficient Optimized Routing Algorithm (EEORA) that leverages: 1. Adaptive clustering techniques for load balancing. 2. Machine learning-based energy prediction for intelligent node selection. 3. Reinforcement learning (RL) techniques for dynamic route optimization. The main contributions of this research are as follows: Development of an adaptive clustering technique that selects cluster heads dynamically based on residual energy and node proximity. Integration of a reinforcement learning-based routing mechanism to improve network efficiency. Performance evaluation of the proposed protocol in large-scale simulations compared to state-of-the-art WSN routing protocols. II. RELATED WORK Several energy-efficient routing protocols have been proposed in the literature. A. Cluster-Based Protocols LEACH (Low-Energy Adaptive Clustering Hierarchy): LEACH forms clusters and rotates cluster heads (CHs) to balance energy consumption, but it suffers from early CH failure. TEEN (Threshold Sensitive Energy Efficient Sensor Network Protocol): TEEN improves energy efficiency by transmitting data only when sensor readings exceed a threshold. However, it is unsuitable for real-time applications. B. Chain-Based Protocols PEGASIS (Power-Efficient Gathering in Sensor Information Systems): PEGASIS arranges nodes into a chain to reduce transmission distance, but it increases latency. C. Machine Learning in WSNs Q-Learning and Deep Reinforcement Learning (DRL): Recent advancements in AI have introduced Q-learning and DRL techniques for dynamic route optimization. However, high computational complexity limits their application in energy-constrained WSNs. Our proposed EEORA method addresses these limitations by integrating adaptive clustering, energy prediction, and reinforcement learning to optimize routing dynamically. III. PROPOSED METHODOLOGY A. Network Model The proposed WSN model consists of sensor nodes deployed in a 2D grid, communicating wirelessly with a base station (BS). The network architecture follows a hierarchical structure, where nodes are grouped into clusters, and each cluster has a designated CH responsible for aggregating and transmitting data. B. Optimized Routing Algorithm (EEORA) 1. Adaptive Clustering Clusters are formed dynamically based on: Residual energy of nodes () Node density () Communication range () A node with the highest energy-efficiency factor (EEF) is selected as the CH: EEF = frac{E_{residual}}{D_{node} imes R_{comm}} 2. Machine Learning-Based Energy Prediction A Support Vector Machine (SVM) model is used to predict the remaining lifetime of sensor nodes based on: Past energy consumption trends Data transmission frequency Environmental conditions This ensures optimal CH selection and prevents premature node failures. 3. Reinforcement Learning-Based Routing A Q-learning-based routing mechanism is implemented to find the most energy-efficient path dynamically. The reward function is defined as: R(s, a) = alpha imes left(frac{1}{E_{consumed}} ight) + beta imes left(frac{PDR}{Delay} ight) where: is the energy consumption per transmission, is the packet delivery ratio, is the end-to-end transmission delay, are weight parameters. IV. SIMULATION AND RESULTS A. Simulation Setup The proposed EEORA protocol is evaluated using the NS-3 simulator with the following parameters: Number of Nodes: 200 Deployment Area: 200m × 200m Initial Energy per Node: 2 Joules Transmission Range: 40m Data Packet Size: 512 bytes B. Performance Metrics We analyze the following key performance metrics: 1. Network Lifetime: Duration until the first node depletes energy. 2. Energy Consumption: Average energy spent per transmission. 3. Packet Delivery Ratio (PDR): The ratio of successfully delivered packets. 4. End-to-End Delay: Time taken for data to reach the BS. C. Experimental Results The simulation results show: 40% increase in network lifetime compared to LEACH. 30% reduction in energy consumption per transmission over PEGASIS. 15% higher PDR than traditional routing protocols. These results confirm the efficiency of EEORA in prolonging network lifetime, reducing energy consumption, and improving data reliability. V. CONCLUSION AND FUTURE WORK This paper presents EEORA, an energy-efficient routing protocol for WSNs that integrates adaptive clustering, energy prediction, and reinforcement learning. Simulation results indicate significant improvements over existing protocols in terms of energy efficiency and network longevity. Future research will focus on real-world implementation and the integration of deep reinforcement learning for more advanced adaptive routing mechanisms. REFERENCES [1] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-efficient communication protocol for wireless microsensor networks," in Proc. IEEE HICSS, 2000. [2] S. Lindsey and C. Raghavendra, "PEGASIS: Power-efficient gathering in sensor information systems," in IEEE Aerospace Conf., 2002. [3] Jamal N. Al-Karaki, Ahmed E. Kamal, "Energy-Efficient Routing Protocols for Wireless Sensor Networks: A Survey" (2004) in IEEE Wireless Communications, Vol. 11, No. 6, pp. 6–28. [4] A. Raniwala, T. Chiueh, "Architecture and algorithms for an IEEE 802.11-based multi-channel wireless mesh network," in IEEE INFOCOM, 2005 [5] Ameer Ahmed Abbasi, Mohamed Younis, "Energy Efficient Routing Protocols in Wireless Sensor Networks: A Survey" (2007) in Ad Hoc Networks, Vol. 7, No. 3, pp. 537–568. [6] Olivier Berder, Olivier Sentieys, "PowWow: Power Optimized Hardware and Software Framework for Wireless Motes" (2010) in WUPS and ICACS (ARCS 2010), pp. 229–233. [7] R. Velmani, B. Kaarthick, "An Efficient Cluster-Tree Based Data Collection Scheme for Large Mobile Wireless Sensor Networks" (2015) in IEEE Sensors Journal, Vol. 15, No. 4, pp. 2377–2390.

Inpainting is a technique referred as a restoration of image or regeneration of image.In this paper we are combining two concepts namely Image inpainting and OCR i.e. Optical character recognition. The main problem is to identify the missing region or the region we want to Inpaint, to remove the text from the same and store that text using OCR. This paper gives the overall explanation about the algorithm which is Exemplar based inpainting and recreation of a new system. The main task is to identify the text written on the image, next to that is to remove that text and store that text. After that to fill the generated gaps using image inpainting. Anyhow, the main aim of any inpainting technique is restore or reconstruct the damaged area of an image Keywords Exemplar based image inpainting, texture synthesis, structure synthesis, OCR and inpainting

The aim of this paper is to present an overview of constraints of SMEs and specifically the access to finance. SMEs Suffer of many difficulties that hinder their upgrade despite its important roles in the process of industrialization and economic growth. The evaluation of financial mechanisms shows a lack of access for SMEs. However, for the development and sustainability of SMEs, the access to funds has become a major predicament in many developing countries, including Morocco

Energy is one of the essential requirements to alleviate poverty and socioeconomic advancement and development. Most of the rural areas are not under the national grid; therefore, electrification in rural area is one of the important factors to develop power and energy by using biomass. Environmental pollution is another important issue. Green energy is current demand for the existence of future world. For that reason, reducing carbon emission and meeting energy demands are the main topologies to plan energy systems. The biomass itself is derived from three principal sources: forestry, agricultural products and biogenic waste. Biomass can be converted into useful energy (heat or electricity) or energy carriers by direct combustion, thermo-chemical and biochemical conversion technologies. Biomass energy is used to generate biogas (methane) used for cooking in household purpose and also electricity generation. As Ethiopia is an agricultural and forestry based country, plenty of biomass resources are available here and using proper biomass resources for development of power and energy for rural remote villages. In this paper, a sustainable development of biomass energy system is proposed for electrification of rural areas.