International Journal of Innovations in Science & Technology
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Hedonism and Repurchase: Determining Value for Money and Repurchase Intentions in Mall
Get PDFThis research determines, how the customers intend on buying and how their perceptions of currency values are affecting their shopping experiences in Pakistan To do so, a questionnaire with a sample size of 360 respondents. To achieve the research objectives, a quantitative investigation was conducted. Information was gathered from malls and a few supermarkets in Multan. According to this study, a buyer’s repurchase represents found a key indicator of their status, amusement, idea, and level of satisfaction. The association between the study and the social value of the currency was found negative. However, no correlation was found between exploration and intention of purchase in the proposed study area. Furthermore, the outcome of this study showed that the value of the currency was positively influenced by repurchase objectives. This research presented novel perceptions on the nature of hedonism, repurchase intention, and the emergence of more engaging shopping strategies encouraging consumers to enjoy their goods in depth. Interventions of the study revealed an entertaining shopping mechanism with more valuable and happy footsteps. By providing a large variety of fresh things i.e., a greater selection of products, friendly sales employees, interesting shopping areas, regular access to shopping information, and a high level of service, it is recommended to boost the recreational and practical elements of shopping. The analysis showed the number of customers could steadily rise in future who repurchase the product
Temporal Variations In Ice Cap Of Antarctica And Greenland
Get PDFThe Antarctic and Greenland polar ice caps are the largest mass of ice in world. Globally the climate system is considerably affected by these ice sheets. Several natural and anthropogenic activities have affected the balance of mass of ice sheets. Ice sheets mass loss is a consequence of changes of patterns of precipitation, changing wind patterns, increasing global temperature and increased glacial flow. Nearly 75% of the ice mass loss has been observed in these regions since last ten years. A sharp increase in ice mass loss in Antarctic and Greenland regions are detected through 0.3mm increase in sea level per year. In this research paper Satellite remote sensing techniques including Enhanced Thematic Mapper Plus (ETM+) is used to monitor and reveal the patterns of ice melt and glacier flow in these regions.
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Identifying the Causes and Protective Measures of Road Traffic Accidents (RTAs) in Bahawalpur City, Pakistan
Get PDFRoad Traffic Accident (RTA) is a growing public issue and fall among the four top causes of mortality and morbidity globally. The main objective of this study was to identify the causes and protective measures of road traffic accidents in Bahawalpur City. Primary data was gathered through a structured questionnaire during a field survey in selected five public places as sample sites i.e. Larry Ada, University Chowk, Bahawal Victoria Hospital (BVH), One Unit Chowk, and Melad Chowk. Secondary data of road accidents was gathered form National Highway and Motor Way Police (NH&MP) while primary data was gathered from 150 respondents (30 from each study site) and analyzed in SPSS software by applying descriptive statistics and road accident risk index (RARI). Findings revealed that the main causes of these accidents include increase in population (62.66%), increase in demand for vehicles (22%), bike drivers (69.33%), overtaking of the vehicles (51.33%), over speed and hustle to reach the destination (34.66%). One wheeling is also a major reason, which results in the death of teenage drivers (52%), violation of the traffic rules (25.33%). RARI results also suggest the relationship between the affected persons and the road traffic accidents. Lastly, few suggestions were proposed to overcome the ratio and severity of road traffic accidents because these accidents are predictable and largely preventable through multi-disciplinary coherent strategies.
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Monitoring of Mangrove Cover of Western Indus Delta Karachi Pakistan
Get PDFThe coastline of Pakistan comprises of five significant sites comprising of mangroves including Indus Delta which contains extensive mangroves zones and termed as the largest arid mangrove found globally. This study evaluate the current extent of mangroves along the Western edge of Indus Delta and provide the most recent forest cover assessment of mangroves. Moreover, this study identifies the changes occurred in forest cover from the years 2000 to 2020. Landsat 5 Thematic Mapper (TM), 8 Operational Land Imager (OLI) and Landsat 7 ETM data were used for mangroves mapping through supervised classification method. The results displayed that total area of mangrove forest cover was nearly 279.094km², 395.77km², 306.58km² in the years 2000, 2010 and 2020 respectively. This study indicates an increase in area of mangrove cover from 29% to 41% from the year 2000 to 2010. Regeneration of mangrove mostly took place around the southern region of the Indus Delta. The mangrove specie has decreased from 41% to 31% from the year 2010 to 2020. The major causes of this reduction were urban water and industrial pollution, over-fishing in Indus delta, freshwater diversion for agriculture, and overharvesting of mangroves by the local communities, coastal erosion and sedimentation.
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Effects of COVID-19 Pandemic on Food Chain and Poverty in Pakistan
Get PDFCOVID-19 pandemic has severely affected the food supply throughout the world. Pandemics affect the economy of nations badly but a number of countries were facing food insecurity even before COVID-19 pandemic. In this paper yearly data of food security is collected from the year 2015 to 2020 to inspect the consequences of poverty and COVID-19 pandemic through spatial regression analysis. The analysis shows that the food insecurity index has increased up to 33.5% by the year 2020 due to prevailing COVID- 19 pandemic. The Asian residents which are already living in developing countries have faced higher food insecurity between the years 2015 and 2018. The spatial regression analysis babbled that the discriminations like race, religion and creed doesn’t play any significant role in poverty and food insecurity. The primary factor of food insecurity is poverty. The poverty affected strongly during the years 2015 and 2018, the condition was worsened by the arrival of COVID-19 pandemic in 2020.
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SRTM DEM Based Neotectonics From Non-Linear Analysis: A Paradigm Through Fractal Analysis
Get PDFNeotectonics amend the river base and causes landscape erosion. This study explores the DEM based differentiation of neotectonics in the northern regions of Pakistan. This method involves vertical and non-linear dissection base on digital evaluation method. This study uses Gliding Box Technique (GBM and GBT) and Box Counting method to evaluate Lacunarity (LA), Succolarity (SA) or 3-Fractals, and Fractal Dimensions (FD). 3-fractals are an attribute used for the recognition of spatial patterns, specifically to compute and differentiate natural textures including natural patterns. This study also investigates vertical dissection using DEM SRTM having spatial resolution of 90m. DEM SRTM measures surface area, plane area as well as the surface ratio. The vertical areas are investigated to make dissection maps and to identify the affects of neotectonics on the roughness of surface. Low value of surface roughness indicates flattened drainage basins and inclination of slope. The Raikot Fault shows higher values of surface roughness towards NE- SW. The surface roughness is mapped to recognize relative uplifts, uneven regions, depressions and pits. Analysis through non-linear method identifies the regions affected by neotectonics activity. Tectonics activity causes deformation and instability in drainage networks.
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Heart Attack Risk Prediction with Duke Treadmill Score with Symptoms using Data Mining
Get PDFThe healthcare industry has a huge volume of patients’ health records but the discovery of hidden information using data mining techniques is missing. Data mining and its algorithm can help in this situation. This study aims to discover the hidden pattern from symptoms to detect early Stress Echocardiography before using Exercise Tolerance Test (ETT). During this study, raw ETT data of 776 patients are obtained from private heart clinic “The Heart Center Bahawalpur”, Bahawalpur, South Punjab, Pakistan. Duke treadmill score (DTS) is an output of ETT which classifies a patient’s heart is working normally or abnormally. In this work multiple machine learning algorithms like Support Vector Machine (SVM), Logistic Regression (LR), J.48, and Random Forest (RF) are used to classify patients’ hearts working normally or not using general information about a patient like a gender, age, body surface area (BSA), body mass index (BMI), blood pressure (BP) Systolic, BP Diastolic, etc. along with risk factors information like Diabetes Mellitus, Family History, Hypertension, Obesity, Old Age, Post-Menopausal, Smoker, Chest Pain and Shortness Of Breath (SOB). During this study, it is observed that the best accuracy of 85.16% is achieved using the Logistic Regression algorithm using the split percentage of 60-40.
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Global Temperature Variations Since Pre Industrial Era
Get PDFThe global temperature trends are being changed due to anthropogenic activities. The natural ecosystems and human societies are affected by this rapid climate change. These changes are caused by the increasing concentration of carbon dioxide and other green house gases including methane and oxides of nitrogen and sulphur. These changes can be identified using accurate data related to variations in temperature and precipitation. We used MODIS GLOVIS LST V6 global datasets to compute pixel-based temperature and mapped the trends. The considerable warming trends are exhibited by Arctic regions which are warming twice as compared to other parts of world. The largest increase in precipitation occurs in Northern Europe at the rate of 12.9mm per decade. The concentration of carbon dioxide has been raised up to 4.14 ppm in atmosphere by December 2020. This increased concentration has raised the global temperature up to 1.2°C since pre industrial era. Remotely sensed datasets provided promising results.
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LSM: A Lightweight Security Mechanism for IoT Based Smart City Management Systems using Blockchain
Get PDFSmart cities utilize digital technologies for the improvement of its services’ quality and performance by reducing resources’ cost and consumption, with a commitment of action and efficiency to its citizens. The increased urban migration has led to many problems in cities, such as traffic congestion, waste management, noise pollution, energy consumption, air pollution, etc., as nowadays COVID-19 pandemic has seized the whole world. So, it is necessary to carry out its standard operating procedures (SOPs), including less human interaction. Thus, technology plays a vital role via Internet-of-Things (IoT) based systems. In this paper, a lightweight security mechanism (LSM) is proposed to enrich the IoT based systems. Blockchain technology is integrated, and its completely decentralized peer-to-peer (P2P) technology enables the users’ authentication and authorizes legitimate procedures. The IoT based management system is developed to monitor some of the aforementioned problems and solve solid waste, air, and noise monitoring systems. The Ethereum blockchain is used to implement a smart contract based framework for the system’s security and access control. The evaluation of performance of the LSM demonstrates that it is an efficient and lightweight tool in terms of cost, resources, and computation and superior over related security studies.
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Algorithm-Driven Optimization of ZnCo₂O₄@CuO Core-Shell Architectures for High-Performance Supercapacitors
Get PDFThis study investigates the electrochemical performance of ZnCo₂O₄@CuO core–shell nanostructures as advanced electrode materials for supercapacitors. ZnCo₂O₄, a spinel metal oxide, offers high theoretical capacitance and environmental compatibility but suffers from low electrical conductivity and structural instability. To address these limitations, we synthesized ZnCo₂O₄@CuO composites using a hydrothermal method, leveraging CuO\u27s excellent electrical conductivity and chemical stability to enhance the core material\u27s properties. Comprehensive characterization confirmed the formation of a hierarchical core–shell structure with improved surface area and uniform elemental distribution. Electrochemical testing revealed that ZnCo₂O₄@CuO electrodes exhibited significantly enhanced specific capacitance (882 F g⁻¹ at 4 mA cm⁻²), superior rate capability, and excellent cycling stability, retaining ~90.2% of their initial capacitance after 4000 cycles. An asymmetric supercapacitor device assembled with these electrodes delivered a maximum energy density of 46.66 Wh kg⁻¹ and power density of 800 W kg⁻¹. These findings demonstrate the potential of ZnCo₂O₄@CuO core–shell nanostructures as high-performance, durable, and cost-effective materials for next-generation energy storage applications