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Transliteration is the process of mapping the character of one language to the character of some other language based on its phonetics. India is very much diverse in languages where people speak different languages. Though they speak different languages, it might be difficult for them to read the script of those many languages. In a situation like this, transliteration process plays a major role. It helps in various Natural Language Processing applications such as Information retrieval, Machine translation, Speech recognition. These are NLP applications which make the computer understand the natural language as to how human being interprets. It helps in translating technical terms and proper names from one language to another language. Moreover, transliteration works have been carried out in languages such as Japanese, Chinese and English. But when considering Indian languages, especially Tamil language, very few recognizable works have been carried out. In this paper, transliteration process is carried out on Unicode Tamil characters. The phonetics-based forward list processing is implemented for transliterating from English language to Tamil language which yields promising results.

There are several industrial uses for LLC resonant converters. The outcome of the converter is greatly influenced by the design and analysis methodologies used. An LLC resonant converter has been designed based on first harmonic approximation (FHA) modelling, and an optimal design technique has been provided in this work. The goal of this research is to provide a thorough design technique for an LLC resonant converter, based on rigorous quantitative analysis of the circuit’s steady-state performance. This study uses FHA technique, which greatly facilitates the model of the system, resulting in a linear circuit that can be analyzed using a standard complex ac-circuit analysis. The FHA methodology is used to establish circuit characteristics and to estimate the outcomes. Although half-bridge power converters are frequently employed in isolated, converters with high-voltage inputs, and medium-power applications are frequently constructed with resonant switching to increase efficiency, a feature that adds complexity but also provides various performance benefits. Two major benefits of the LLC resonant architecture are the soft-switching capabilities of the Power MOSFETs and secondary rectifiers, as well as the ability to operate at zero load. Additionally, the LLC resonant converter is simulated and the results are confirmed using PSIM.

Modeling a reliable electrical equivalent circuit to simulate the output I-V characteristics of organic solar PV (OPV) cells still prevails as a challenging task. This is because, estimating unknown parameters from the transcendental current equation determining the nonlinear OPV characteristics is extremely difficult. More importantly, predicting the parameters for dynamic changes in irradiation profile demands reliable optimization-based models. Therefore, this article proposes the application of adaptive wind-driven optimization (WDO) algorithm for a three-diode electrical equivalent model to estimate the OPV circuit parameters. Application of WDO algorithm has produced precise PV parameters to reproduce the exact I-V characteristics. In particular, the ability to replicate the kink effect in OPV characteristics is a noticeable improvement. Compared to its counterparts, various factors that enable WDO to enhance its compatibility towards nonlinear OPV modeling are: i) unique velocity update strategy via Coriolis and Gravitational forces, ii) excellent tradeoff between exploration and exploitation of control variables, iii) adaptive capability to maintain solutions within the search space even if the limits are breached, and iv) easiness in parameter tuning. For the validation, extensive testing has been conducted to reproduce the widely used characteristics of nav100 OPV cell at various operating conditions. Quantitatively, WDO method showcases excellent accuracy with an individual absolute error value in the order of 10-6 and convergence within the first 50 iterations itself, demonstrating its supremacy to solve OPV parameter identification problem.

In the literature arena, it is claimed that lean manufacturing has been implemented successfully in organizations. However, lean manufacturing has been finding little application in classical manufacturing organizations. A careful study of the literature would indicate that non-value adding activities have been occurring in classical manufacturing organizations and preventing the successful implementation of lean manufacturing. In order to overcome this deficient situation, the research reported in this paper was carried out. By carrying out this research, non-value adding activities were mapped with lean manufacturing strategies. In the beginning, 50 non-value adding activities and 27 lean manufacturing strategies were gathered from the literature arena. Through critical thinking, the non-value adding activities were mapped with lean manufacturing strategies. The list containing this map presented in this paper will be useful to the engineers and managers for successfully implementing lean manufacturing in classical manufacturing organizations.

The classification of the brain tumor image is playing a vital role in the medical image domain, and it directly assists the clinicians to understand the severity and to take an appropriate solution. The magnetic resonance imaging tool is used to analyze the brain tissues and to examine the different portion of brain circumstance. We propose the convolutional neural network database learning along with neighboring network limitation (CDBLNL) technique for brain tumor image classification in medical image processing domain. The proposed system architecture is constructed with multilayer-based metadata learning, and they have integrated with CNN layer to deliver the accurate information. The metadata-based vector encoding is used, and the type of coding estimation for extra dimension is known as sparse. In order to maintain the supervised data in terms of geometric format, the atoms of neighboring limitation are built based on a well-structured k -neighbored network. The resultant of the proposed system is considerably strong and subjective for classification. The proposed system used two different datasets, such as BRATS and REMBRANDT, and the proposed brain MRI classification technique outcome is more efficient than the other existing techniques.

The transportation sector plays a prominent role in driving the economy of any given nation. However, with the recent tensions arising in and around the transportation sector, sustainable mobility concepts have evolved. However, it is quite unclear whether sustainable mobility is feasible and exhibits economic returns, environmental benefits, and societal advantages. Hence, taking into account the environmental, economic, and social impact, and technical possibilities, this study intends to analyse sustainable mobility in relation to economic returns, environmental benefits and societal advantages using bibliometric analysis. For this study, we considered two decades of research, from 2001 to 2021. An in-depth search was performed on articles generated in the last two decades to assess the state of the literature on sustainable mobility. The most reverent, frequently referenced papers and influential journals in the field of sustainable mobility were identified. The acquired findings highlight the most prominent publications, journals, and authors who have made significant contributions to sustainable mobility studies, as well as the sub-areas or themes linked to sustainable mobility. Overall, the analysis discovered current paradigms, significant research topics, and a relationship between the domains of sustainable mobility studies. Meanwhile, this study also demonstrates advancements in the primary themes and sub-areas during the previous 20 years and alterations in future research fields. In addition, this study identified the promotion of rapid-reliable-safe-convenient (RRSC) transportation services, reduction in urban car traffic, and support to low transportation demand as the critical steps that require immediate attention in order to build a sustainable mobility future. We also observed that hydrogen would be a promising fuel and potential technology for the future mobility sector in the post-COVID era.

The purchase of products or administrations through an electronic trade called web based shopping over internet using a web browser. Online Product surveys are significant for up and coming purchasers in helping them decide. To this end, distinctive sentiment mining systems have been proposed, where making a decision about a survey sentence’s direction (e.g., positive or negative) is one of their key difficulties. As of late, Machine learning has risen as powerful methods for taking care of assumption order issues. An AI model inherently learns a helpful portrayal consequently without human endeavors. In any case, we propose a regulated AI structure for item audit conclusion arrangement which utilizes pervasively accessible evaluations as powerless supervision signals. To assess the proposed system, we build a dataset containing 2, 00,000 pitifully named survey sentences and 15000 marked audit sentences from Amazon. Trial results show the more exactness contrasted with past one.

The DC-DC converters operate extensively in a variety of industrial applications such as electric vehicles, renewable energy systems, aerospace applications, consumer electronics (smartphones, laptops, etc.) and energy storage solutions. The reliability of the DC-DC converters is of a greater significance. The research endeavours made in enhancing the reliability of the DC-DC converters are still very limited and dispersed. Due to the rapid growth in semiconductor technology, the DC-DC converters have an endless number of topologies, with various operating principles and functionalities. Enhancement of the reliability of all types of DC-DC converters is still a challenging task. Power switches are the most fragile components in converter circuits, which inherently fall prey to the faults occurring in the system. Hence, there is always a requirement to take appropriate remedial measures to deal with all kinds of faults. Further, in order to detect the occurrence of fault a fast fault-diagnosis and fault-tolerant strategies in the DC-DC converters is mandatory and the same has to be embedded in the converter for safety purpose. In view of the importance of the same, the fault-diagnostic algorithms and fault-tolerant strategies developed in the literature, by various researchers are furnished in a single document after conducting an exhaustive review.

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability.

This paper reviews and discusses the state of the art of integrated switched-capacitor and integrated inductive power converters and provides a perspective on progress towards the realization of efficient and fully integrated DC–DC power conversion. A comparative assessment has been presented to review the salient features in the utilization of transistor technology between the switched-capacitor and switched inductor converter-based approaches. First, applications that drive the need for integrated switching power converters are introduced, and further implementation issues to be addressed also are discussed. Second, different control and modulation strategies applied to integrated switched-capacitor (voltage conversion ratio control, duty cycle control, switching frequency modulation, Ron modulation, and series low drop out) and inductive converters (pulse width modulation and pulse frequency modulation) are then discussed. Finally, a complete set of integrated power converters are related in terms of their conditions and operation metrics, thereby allowing a categorization to provide the suitability of converter technologies.

Wireless power transmission (WPT) is one of the breakthroughs in effortless electric vehicle (EV) charging technology. Different types of wireless charger topologies were proposed and implemented to meet various constraints like power transfer efficiency, wireless transfer distance, and misalignment tolerance. Yet the coupling separation and the transfer efficiency are still underdeveloped for contactless charging of medium- and low-power EVs like e-cycles and e-scooters. For achieving the high-distance WPT in the vehicles which are prone to misalignment issues, series-series (SS) compensated WPT is used. The conventional SS-compensated WPT uses a voltage-fed converter for the power conversion. But the combination of these topologies allows reverse current flow in the system, which will affect the transfer efficiency and life span of the source. To prevent this, a reverse blocking diode or a current-fed converter can be used. Though the reverse current problem can be solved, these approaches seem to reduce the power transfer efficiency further. This article tries to optimize the current-fed converter-based SS-WPT to achieve higher coupling separation, higher power transfer efficiency, and higher misalignment tolerance than the conventional designs. To achieve this, the input inductor of the current-fed converter and the primary coil of the SS-WPT are tuned without affecting the magnetic resonance condition. The transfer efficiency was found to be 94% at a coupling separation of 200 mm, which is 20% more than the conventional voltage source inverter-based, renewable energy-powered SS-WPT charging efficiency. After proving the concept in prototype design, the results are validated by testing the same in a real-time electric cycle.

Managing supply chain becomes very much difficult due to the interaction between various stakeholders. Hence, it is essential to make strategic decisions in time. From time to time, the status of in-progress performance of effective supply chain management is varying due to its nature of interrelated and interactive upstream and downstream flows. Thus, it is necessary to make a database from the point of suppliers to customers to integrate the process flow and also reduce the operational gap. The manufacturing processes involved, fluctuation in demand, costs related to transportation, costs related to inventory and costs related to decisions, are the significant operational aspects, but not limited to these alone. For carrying out this integration, it is necessary to update, consolidate and categorize the database for deriving feasible decisions. Data-based decision support plays a critical role in encompassing the routine production and triggers to meet the customer requirements. The decisions in time will be quite useful by considering the database and orienting towards the effective, smooth and successful supply chain management.

Electrification of vehicles becoming a widely discussed term among the enthusiastic researchers in the present century. They have contributed a plethora of techniques to this cause. As more research conducted in the field of electric vehicle charging, sustainable transportation gained more importance. Renewable energy powered electric vehicles are introduced by the same cause. Parking slots are then transformed into a large source of solar energy by the integration of solar panels. For the ease and flexibility of charging, wireless charging techniques are introduced. Vehicle-to-vehicle (V2V) wireless charging technique is introduced to meet the contingency conditions like battery drain during a long ride. Present V2V technology has disadvantages like poor transfer efficiency, coupling separation, and misalignment tolerance. This chapter presents an optimized V2V charging system with improved parameters. An overall efficiency of 60% is achieved in hardware at a coupling coefficient of 0.02 for the proposed system. For conventional WPT model, the overall efficiency 60% is for coupling coefficient of 0.09 only. Results are verified with PSIM simulations and hardware.

The restructuring of power systems and the ever-increasing demand for electricity have given rise to congestion in power networks. The use of distributed generators (DGs) may play a significant role in tackling such issues. DGs may be integrated with electrical power networks to regulate the drift of power in the transmission lines, thereby increasing the power transfer capabilities of lines and improving the overall performance of electrical networks. In this article, an effective method based on the Harris hawks optimization (HHO) algorithm is used to select the optimum capacity, number, and site of solar-based DGs to reduce real power losses and voltage deviation. The proposed HHO has been tested with a complex benchmark function then applied to the IEEE 33 and IEEE 69 bus radial distribution systems. The single and multiple solar-based DGs are optimized for the optimum size and site with a unity power factor. It is observed that the overall performance of the systems is enhanced when additional DGs are installed. Moreover, considering the stochastic and sporadic nature of solar irradiance, the practical size of DG has been suggested based on analysis that may be adopted while designing the actual photovoltaic (PV) plant for usage. The obtained simulation outcomes are compared with the latest state-of-the-art literature and suggest that the proposed HHO is capable of processing complex high dimensional benchmark functions and has capability to handle problems pertaining to electrical distribution in an effective manner.

Hardfacing involves depositing a required superior material over a substrate for improving its surface properties like wear and corrosion to function properly in the given working conditions. For example, normally, carbide forming elements that have excellent tribological properties are fused over the steel substrates for the improvement in performance or life. The cited research work described in this article has been undertaken to investigate the suitability of the substrate and the coating material to be used for high temperature applications such as turbine blade which has to work against the corrosive and erosive working environment. The failure of the turbine blades is predominantly due to combustion by-products exhausted from the combustion chamber attributed to high temperature and velocity. In this research work, medium carbon steel EN24 substrate was hardfaced with the coating material nickel-based alloy Inconel 625 selected for its toughness, high corrosion and creep resistance using MIG welding process. The experiments were conducted as a means to improve the surface properties of the turbine blades through hardfacing. The results of the experiments indicated that the properties of Inconel 625 can be comfortably used as turbine blades.

Customer demand requirements are changing rapidly in the current industrial scenario. Changing customer needs necessitates the adoption of appropriate modern tools, equipment, and other needed delivery methods. These efforts are to be integrated by considering the demand requirements of customers, the needed supply of raw material, availability of sub-assembly, manufacturing systems management, delivery of products based on the due date requirements of the customers, and after-sales services. These activities are to be integrated with dynamic operable strategies to face the challenges in the pierce competitive market environment. In order to amalgamate these activities dynamically, supply chain management integrated with risk management strategies are initiated. Risk mitigation through the identification of risk, assessment of risk, prioritization of risk, and control of risk are effective in many of the manufacturing organizations. But, the risk control measure just pinpoints the loss reduction at that point of time only and the development of feasible strategies for risk mitigation. Then, moving towards routine production activities will be usually resumed. The loss of producing elements in the supply chain flows was not analyzed in detail to prevent them in the future. In order to tackle these issues in a cursory manner in manufacturing organizations, the development, and implementation of strategies by adopting the integrated supply chain risk management principles are essential for the mitigation of loss prevention efforts. For moving towards the continual improvement of manufacturing organizations with appropriate outcomes, it is essential to integrate these types of risk prevention measures.

In recent decades, the usage of natural cellulosic fiber based polymeric composites in industrial and domestic applications has been increased because of its eco friendliness nature. It also has several benefits like high strength-to-weight, low cost, available in ample, sustainable etc. The advancements in the field of composite materials results in the development of hybrid composites by reinforcing two different fibers into a matrix. Because of the synergistic effect of reinforcements these hybrid composites offer better overall properties. The selection of appropriate combination of fibers, fiber contents and fiber surface treatments are the key for enhancing the properties of hybrid composite materials. This chapter presents the comprehensive review of performance of different phenolic hybrid composites in a view of selection of appropriate phenolic hybrid composite for industrial and domestic use.

Social media is the most challenging one for analyzing the text and the social media application is a tool for expressing the opinion without facing any fear. At the same time, there will be a lot of crime and violence occurs on the internet. Especially the women who are in a popular position like celebrities, politicians, and also the common people are facing the threats of violence are in social media. So they feel insecure in society. Still, there will be a problem for analyzing the text. It is very too difficult to classifying the text on social media. Through the machine learning technique, it would be done effectively. It filtered the unwanted text and then it reports to the respective office. So it will help the government to protect the women in social media. In this paper, a survey on online abuse as well as a study about sentiment analysis. According to this paper, it helps many researchers to get an idea of the sentiment analysis in social media. Similarly, the survey is done in a combination of the different techniques and also drafted drawbacks.Keywords-Support vector machine (SVM), Naive Bayes classification, Sentiment analysis, Social networking site.

In recent years, the usage of solar energy as a source to produce power has increased exponentially as it provides a clean and efficient alternative to depleting non-renewable resources. The normal working period of a photovoltaic (PV) panel is 20 years, but due to defects in manufacturing or atmospheric condition changes, the efficiency and the lifespan of the panel decrease each year. The objective of this review article is to present and analyze the different methods that can be used to reduce the degradation rate of the PV cells in an economically viable way. Open-source frameworks are important to make any solution affordable; hence we explore the usage of python language in developments relating to improvement in the performance of PV cells. Based on this review a practically employable solution to improve working conditions for PV cells can be obtained.

In recent years, conventional energy sources are depleting and getting exhausted. In replacement of this, solar Photovoltaic (PV) systems are used because of its free availability, renewabiiity and less operating cost. But the constraints such as low efficiency, dependability on weather conditions are overcome by using maximum power point tracking(MPPT) algorithms and efficient converters to produce the maximum power output. MATLAB/Simuiink is used to model and analyze PV array, MPPT algorithms, and converters. In this paper, recent research developments in PV array, various MPPT techniques, many efficient Converters are presented. This paper will give an overall idea about the present research trends in the field of Solar Photovoltaic systems.

Magnetic resonance technology set a new course in the wireless power transfer (WPT) sector. WPT is derived from inductive power transfer (IPT) which is developed many decades back. After this much time, the transfer efficiency increased from 70% to more than 95% and transfer distance from few centimeters to several meters. A converging pattern in the trade off between transfer efficiency and the air gap distance is visible in every novel designs. This pattern is achieved through the optimum selection and design of compensator, wireless transformer and the battery packs. As the conservation of energy and exploration of renewable energy resources became a common aspect in every novel technological entities, solar power and fuel cells made its debut to wireless charging. A detailed analysis of different types of wireless charger topologies implemented and proposed in plugged in hybrid electric vehicle (PHEV) charging applications are presented in this paper. The recent attempts to integrate the renewable energy sources to the wireless charging is covered. Two winding model is taken for the analysis of the state of art efficiency. For enhancing the performance of wireless charging system, various compensation techniques are validated based on different topologies. Maximum efficiency and charging condition for a given impedance is explained and derived comprehensively. Different winding designs for wireless transformer is described with comparison. Magnetic coupler selection, battery selection and different safety standards for WPT design are mentioned in this paper.

Recently, Sentimental Analysis (SA) attains most important attention while making a decision when it used for extracting and classifying the sentiments existing in web-based reviews which are written by a customer. Here, SA is used as a sentiment classification (SC) issue where the reviews are classified as positive and negative factors which are based on internet reviews. This work projects an efficient SA technique for online reviews by the combination of Feature Selection (FS) as well as classification. The Firefly (FF) and Levy flights (FFL) models are used to extract features from web-based review and Multilayer Perceptron (MLP) is employed to classify the sentiments. For experimentation, a benchmark DVD dataset is employed to test the effectiveness of the presented model. The final outcome reveals that the proposed FF-MLP method attains effective classifying operation from every dataset on behalf of various performance metrics.

Wireless power transmission (WPT) is becoming an inevitable technology of the 21st century. As the power is transmitted by electromagnetic induction through air medium, the chances of electromagnetic (EM) radiation will be high in the vicinity of the wireless charger. The effect of this radiation can be harmful to human, based on its strength and frequency. Various standards are implemented to fix the radiation limits in the bearable level. Since different standards follow different principles and fixing different limits, the lack of a common scale creates misconception to the manufactures and researchers. This paper discusses in detail about all the existing standards for the WPT applications and comparing it. As the available devices and technologies are relatively delicate and costly, a simplified EM radiation measurement mechanism is presented in the paper. A 100W electric vehicle charger is tested using the method.

The World Health Organization has submitted a report in 2017 which declared that a population of nearly 36 million people are blind out of 253 million visually impaired people. Braille books in the tactile format are very helpful for the visually impaired people to gain knowledge but the availability of these resources is limited. With the improvement of electronic innovation, Braille ended up being appropriate to PC helped generation in light of its coded structures. Programming based content to-Braille interpretation has been ended up being a fruitful arrangement in Assistive Innovation. Various research studies and papers describe the methods for obtaining machine readable document from textual image. In future, character recognition might serve as a key role to create a paperless environment that helps the visually impaired people to gain enormous amount of educational materials. In current world the innovations and advancements in modern scientific systems has expanded the boundaries of human effort like Optical Character Recognition. In the field of machine learning and pattern matching Handwritten recognition has gained lot of attention. A novel method is proposed to convert Handwritten text into Braille text due to which huge resources of Handwritten text materials will be available in Braille text that helps the visually impaired and low vision people to expand their knowledge. The novelty of this system has gained a better accuracy.

This paper proposes an efficient drive system for 3-phase Induction Motor with a front end Vienna Rectifier and SPWM Inverter. The front end Vienna Rectifier is controlled using closed loop hysteresis control which improves the input power factor and eliminates the use of large filters. On the other hand SPWM is used as the switching technique for the inverter. The switching sequence has been generated using dsPIC30f4011 micro-controller. SPWM technique reduces the harmonic content and along with the V/f control it provides an efficient speed control of Induction Motor. The whole system has been simulated and validated on PSIM software

The multilevel inverters are in the focus in recent years. This is due to their advantages over the conventional three-level inverters. It is possible to obtain a nearly sinusoidal waveform using multilevel inverters. Due to this, the power quality is also improved. Also, they made possible to use the medium power switches in the high power applications. In this paper, new asymmetric 49-level cascaded multilevel is proposed by adding two 25-level multilevel inverters. The two inverters are operated at a delay with respect to each other, and the outputs of them are added in the load, thus obtaining a 49-level output. The main advantage of this inverter is that even if a switch is damaged the particular inverter module can be isolated and it can be operated in 25-level mode. This enables no much depletion in power quality and moreover, it assures the continuity of power supply. The viability and effectiveness of the proposed inverter is confirmed through simulation and experimental using laboratory experimental set-up..

This Paper proposes a Multiple Input Interleaved Boost Converter (MIIBC) for renewable energy applications. As the increasing demand on renewable energy resources, power electronic devices are obligatory to fit the fragmentary nature of these sources. Generally, DC-DC Boost converter is used for low voltage application systems supplied by batteries. For lofty power requisition Boost converter isn’t as adept, as a result of high input current ripple that is added to the current flowing out of fuel cell and this input current causes reduction in battery life. The multiple input converter (MIC) provides compensation of mismatching of electrical characteristics of sources such as Fuel cell and Photovoltaic cell. The main purpose of multiple input converter is of four different aspects cost, potential modularity, reliability, and flexibility. The interleaved boost converter (IBC) consists of two parallel connected boost converters with 180° phase shift switching. This provides reduced input and output ripple, higher efficiency, and also maintains high power density. The dc inputs to the MIIBC are 50 V photovoltaic (PV) module and a 45V/6.5kW fuel cell, which are modelled using the MATLAB/Simulink.

In recent years suicides are proliferating because of work stress and depression. Different types of suicides are performed based on mentality of person. Out of many methods hanging attempt is one of the major causes for demise. It is the act of killing oneself intentionally by suspending from an anchor point. Hanging rate can be reduced by detecting the suicidal tendency of a person in advance. Though there are many technologies like door alarm thick blankets etc for identifying the hanging but their limitations results in inefficiency of the system. Latest technologies like machine learning, deep learning etc are been used in various security mechanisms. Therefore, in the proposed system, deep learning concept with the help of Self organised mapping is used to extract the features after videos are captured from surveillance camera. This proposed system will provide efficient results in determining the hanging attempts in advance when compared to the traditional methods.