ESTIRJ Volume 6, Issue3  Sept, 2022

Paper 1:DIGITAL IMAGE FORENSICS USING IMAGE-SIMILARITY (1-7)

Abstract: Digital image integrity and authenticity are becoming increasingly critical issues. Image forgeries are becoming quite simple to make. In order to demonstrate the integrity and validity of digital photographs, digital image forensics is required. Since there are so many effective methods for manipulating images, their veracity is being called into doubt, particularly when they are used to support claims for insurance, medical industry, or legal proceedings. By using numerous high-tech mechanisms discovered in the existing research, picture forensic approaches ascertain the integrity of photographs. In this study, the photographs are scrutinized for a specific kind of forgery in which a portion of an image is duplicated or hidden by being pasted onto another image. This type of forgery is called Copy-Move Forgery. In this paper, straightforward methodologies have been applied to determine the traces of forgery in the images with less code complexity and time consumption. The results of this research show that the suggested technique successfully detects several copy-move forgeries and accurately determines the copy-move forgery even when the images are tainted with noise, compression, and blurring. Therefore, the suggested method offers a computationally effective and trustworthy method of copy-move forgery detection that raises the credibility of photos in applications that focus on providing proof and contain sensitive information.

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Paper 2:SELF-CONSUMPTION AND COST ANALYSIS OF ON-GRID SOLAR PHOTOVOLTAIC SYSTEM FOR INDUSTRIAL LOAD: A CASE STUDY (8-12)

Abstract: Solar energy is dependent on time and seasons, which results their output in variable nature. The power generation cost from these resources is also high in developing countries due to import and tax. Therefore supportive policies and schemes like feed in tariff and net metering were introduced. But these schemes are not much attractive for consumers due to their insufficient FIT (Feed in Tariff) rates. These shortcomings can be avoided through self-consumption technique for roof top solar PV system, as this technique results in cheaper generation of electricity. This research work is done for installation of on grid PV system along with the cost analysis and self-consumption for industry of Kotri Sindh Pakistan. Proposed system results in the reduction of energy cost about 35.23% with respect to time of use rating model. Furthermore, proposed model guarantees the security of power by completing about 97% of annual energy demand. This proposed model can be used throughout the world by just applying required data sets of that area.

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Paper 3: COVID-19 DETECTION USING DEEP LEARNING IN CHEST X-RAYS IMAGES (13-21)

Abstract: The Covid-19 cases are increasing very rapidly which is causing problems and burden on medical system all over the world.The testing kits that are available in the world are very expensive and so every person can not afford testing, also these kits are limited and not available freely testing by (RT-PCR) is time taking procedure and also they are not reliable, sometimes it shows false report. In this study we proposed chest X-Ray to organize the determination of patients for additional RT-PCR checking. This might be helpful in an anxious adjustment where the current system is attempting to conclude whether to adhere the patient in hospital ward alongside other patients or relocate them in Covid-19 separate wards. It would likewise assist in distinguishing patients with great probability of Covid-19 with fake non-positive RT-PCR who might require testing continuously. More than this, we recommend the usage of modern Artificial Intelligence strategies to recognize the Covid-19 patients by utilizing CXR pictures in a mechanized way, specialy in those areas where radiologists are not easily accessible, and help make the proposed analytical testing innovation adaptable. We proposed Covid-19 Detection from X-Rays, a novel neural deep learning system to emergency patients for fitting testing. On the freely accessible Covid Chest X-Ray Dataset, my proposed model gives 99.10% exactness with 100% affectability (review) for the Covid-19.We essentially enhance the effectiveness on the consequences of Covid-Net on the same dataset.

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Paper 4: SICK BUILDING SYNDROMES: A CASE STUDY OF ADMINISTRATION BUILDING OF MEHRAN UNIVERSITY, JAMSHORO (22-28)

Abstract: The Term “Sick Building Syndromes SBS” is used to describe situations in which building occupants experience acute health and comfort effects that appear to be linked to time spent in a building, so Indoor Air Quality (IAQ) has a huge impact on the building as well as to its users. So, in this regard a research namely; “Sick building Syndromes: A Case Study of administration building of Mehran UET Jamshoro Sindh Pakistan” is carried out by me to give awareness to the employees and let them known about the environment in which they are working. The research paper relied upon the data collected through questionnaire based on the responses of respondent of the administration building. According to WHO (World Health Organization), health is not only the disease to be absent or not being sick; but also totally being well physically, psychologically and socially. Referring to this description, the effects of the environment and also the effects of the building, as an artificial environment, on the conservation and the continuity of this well-being status are subjects to researches and discussions while trying to find the solutions, this is because Indoor Air Quality (IAQ) is in very compromised situation and that is the main cause the people working inside office are being affected in Health as well as lack in efficiency, also no productivity in working condition be achieved. Furthermore, while conducting case study and questionnaire from administration building employees, I realized that there was number of issues regarding Indoor Air Quality that need to be highlighted. However, issues like sudden change in inside temperature increases and reflection of light in the form of Glare, Humidity, lack in environment quality, no proper air movement or crossing through windows, Highest amount of dust, noisy and loudness in the environment and work load, creates health problems as well, these kind of disturbances creates lack of interest in working and mostly depending on non-renewable resources building as well as employee’s health and comfort is in danger, therefore start increasing ventilation rates, removing pollutant sources, cleaning the air and the amount of flow of Air should be in highly considerations to create a best Indoor Environment that increases the efficiency and the interests of employees to work well during office hours.

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Paper 5: ENERGY SOURCES FOR CHARGING ELECTRIC VEHICLES IN PAKISTAN: A SOLUTION TO GLOBAL PROBLEM (29-34)

Abstract: The fossil fuel reserves, which provide energy for conventional automobiles, are almost at their limits. Additionally, these automobiles' exhaust fumes harm the environment by releasing more greenhouse gases into the atmosphere. Electric vehicles (EVs) are a brand-new form of transportation that are being developed to address these problems. Dependable charging infrastructure is also becoming more important as demand for electric cars rises to support the quick uptake of this mode of transportation by the general population. Local electricity grids are simultaneously under stress and need assistance from cheap, plentiful, and renewable alternative energy sources. This is the reason why highly praised renewable energy-based charging stations have lately appeared across countries. In this paper, we examine several forms of alternative energy sources, with a focus on charging infrastructure & reduction in emissions for electric vehicles in Pakistan. In terms of economics and environmental friendliness, the study offers thorough calculations of internal combustion engine emissions as well as an assessment of several renewable and non-renewable energy sources for electrical vehicle charging.

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Paper 6: EVALUATION OF THE DISTANCE BETWEEN THE BASE STATION AND THE SENSORS IN A WIRELESS BODY AREA NETWORK (35-41)

Abstract: Wireless Body Area Networks (WBANs) refer to a network of sensors that are deployed over the body of any human being, animal, or living thing. or non-living things to sense body-related parameters such as temperature, ECG, heartbeat, sugar level, etc. WBANs offer huge applications in health care, gaming, lifestyle, the military, etc. In WBANs, sensors are used and deployed on different parts of the human body to gather information on various parameters. After sensing the data, it has to be transmitted wirelessly to the base station and other sensing nodes. In this thesis, hardware like Iris motes, which are wireless sensor devices, and TinyOS software are used. The operating system for these gadgets is called TinyOS. An Iris mote is a wireless sensor. A network device that uses the unlicensed 2.4 GHz band to send data. It has 16 power levels and 16 channels, each with a 5 MHz bandwidth. Reliable communication is necessary for WBANs because they are a network of human-related parameters. If there is no reliability, even human life can be in danger. So, for reliable communication in WBANs, the estimation of optimal distances in frequency channels and power levels is of prime importance. This research will propose the optimal distance between sensors and base stations. for different frequency channels at different power levels for reliable communication in WBANs.

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