Exploring the Usage of Information Technology for Library Automation

Abstract The basic objective of this research study is to provide a detailed perspective of the current scenario of public libraries workings and procedures in Karachi (Pakistan) and propose automation with an implementation strategy. The study elaborates on the needs of automated library management system components ideally packaging into an ALMS. Differences between the available library management system(s) and proposed ALMS have been highlighted as well. This study recommends the development as well as implementation architectures, development technologies required human resources, and Infrastructure (i.e. servers, client machines, etc.) for ALMS as a preferred system for public libraries in Karachi. In this study, we have proposed a new model for public libraries that refocuses them on the vital task of knowledge management coherent within their communities by way of forming a hub for sharing and disseminating pertinent knowledge. A multi-layered architecture has been proposed for managing information on both local and global levels by creating a connection among multiple instances of the system via the internet. Statistical data collected by surveying thirty public libraries all over Karachi played a pivotal role in the proposed system design. Different aspects of the system have been identified, quantified and grouped into robust and flexible modules to facilitate the common interactions with the application. The system incorporates modules as pluggable and/or reusable components using the MVC design pattern to ease the process of adding, modifying, and/or deleting modules without affecting the integrity of the system. The system features an extremely fast NoSQL database for local storage for real-time and offline search (while the internet is down). All local databases are combined to form a global database to facilitate the passive users (book readers) of the system. The system also defines four different user-views to provide multi-level access of either the local or global database to its users. Since the horizon of technology is very fragmented, the system is designed to be extremely portable by using Electron framework which enables the application to cover all major platforms Windows, Linux, and Macintosh which are most widely used Operating systems by Institutions

A Review on Text Detection Techniques

Text detection in image is an important field. Reading text is challenging because of the variations in images. Text detection is useful for many navigational purposes e.g. text on google API’s and traffic panels etc. This paper analyzes the work done on text detection by many researchers and critically evaluates the techniques designed for text detection and states the limitation of each approach. We have integrated the work of many researchers for getting a brief over view of multiple available techniques and their strengths and limitations are also discussed to give readers a clear picture. The major dataset discussed in all these papers are ICDAR 2003, 2005, 2011, 2013 and SVT(street view text).

Impact of Climate Change on Land use/Land cover of Chakwal District

Alterations in land use and land cover, either natural or anthropogenic can disturb the balance of fragile ecosystems. Climate change plays a unique role in governing the structure and state of land features and alters the structure of ecosystem as well as its services required by earth. Human health and environment are matter of concern due to changes induced by human in its natural environment (Jat et al., 2008). Human has an urge to remain near nature, for that they shift from dense urban areas to less dense areas (Western, 2001). So is the case of new housing societies where the land mafias intimate the people about new settlements (Zaman and Baloch, 2011), which are made by cutting the forests, removing trees and disturbing the ecosystem. For proper planning and management of natural resources, it is necessary to study the land cover and its associated changes (Asselman and Middelkoop, 1995). Modelling of changes within land cover to identify environmental trends on the local, national or regional level, have been realized in the scientific community (Nath et al., 2020). GIS/RS provides continuous change dynamics (Berlanga-Robles and Ruiz-Luna, 2011) of land cover/land use, i.e. by satellite monitoring (Ruiz-Ruano et al., 2016). The understanding of land cover changes is necessary for decision making (Lu et al., 2004) in the natural resource management (Seif et al., 2012). This study was carried out to identify the impact of changes in climate upon land use and land cover of Chakwal district from 1995 to 2020. Geospatial techniques were applied to estimate the differences in land features, using different time interval satellite datasets (Table 1). Six major classes of land features including, agriculture, bare land, built-up, forest, shrubs/grass and water were selected for this study, with respect to time

Universities’ Role in Developing Vocational Education in Jordan

This study examined the role of universities in developing vocational education and transforming TVET in developing workforce towards globalization. To achieve the objectives of the study, a scale of the role of universities in developing vocational education was developed. The study population consisted of all faculty members at Al-Balqa Applied University who were (1400) faculty members. The study sample consisted of (50) members of the teaching staff who teach vocational courses who were selected randomly. The results of the study showed that the role of universities in developing vocational education came to a medium degree. Considering these results, the study recommended universities to continuously update the vocational education equipment and workshops

Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data

Flash floods are the most dangerous kinds of floods because they combine the destructive power of a flood with incredible speed. They occur when heavy rainfall exceeds the ability of the ground to absorb it. The main aim of this study is to generate flash flood maps using Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) models in the river’s floodplain between the Jhelum River and Chenab rivers. A total of eight flash flood-causative physical parameters are considered for this study. Six parameters are based on remote sensing images of the Advanced Land Observation Satellite (ALOS), Digital Elevation Model (DEM), and Sentinel-2 Satellite, which include slope, elevation, distance from the stream, drainage density, flow accumulation, and land use/land cover (LULC), respectively. The other two parameters are soil and geology, which consist of different rock and soil formations, respectively. In the case of AHP, each of the criteria is allotted an estimated weight according to its significant importance in the occurrence of flash floods. In the end, all the parameters were integrated using weighted overlay analysis in which the influence value of drainage density was given the highest weight. The analysis shows that a distance of 2500 m from the river has values of FR ranging from 0.54, 0.56, 1.21, 1.26, and 0.48, respectively. The output zones were categorized into very low, low, moderate, high, and very high risk, covering 7354, 5147, 3665, 2592, and 1343 km2, respectively. Finally, the results show that the very high flood areas cover 1343 km2, or 6.68% of the total area. The Mangla, Marala, and Trimmu valleys were identified as high-risk zones of the study area, which have been damaged drastically many times by flash floods. It provides policy guidelines for risk managers, emergency and disaster response services, urban and infrastructure planners, hydrologists, and climate scientists

Characterizing Spatiotemporal Variations in the Urban Thermal Environment Related to Land Cover Changes in Karachi, Pakistan, from 2000 to 2020

Understanding the spatiotemporal patterns of urban heat islands and the factors that influence this phenomenon can help to alleviate the heat stress exacerbated by urban warming and strengthen heat-related urban resilience, thereby contributing to the achievement of the United Nations Sustainable Development Goals. The association between surface urban heat island (SUHI) effects and land use/land cover features has been studied extensively, but the situation in tropical cities is not well-understood due to the lack of consistent data. This study aimed to explore land use/land cover (LULC) changes and their impact on the urban thermal environment in a tropical megacity—Karachi, Pakistan. Land cover maps were produced, and the land surface temperature (LST) was estimated using Landsat images from five different years over the period 2000–2020. The surface urban heat island intensity (SUHII) was then quantified based on the LST data. Statistical analyses, including geographically weighted regression (GWR) and correlation analyses, were performed in order to analyze the relationship between the land cover composition and LST. The results indicated that the built-up area of Karachi increased from 97.6 km² to 325.33 km² during the period 2000–2020. Among the different land cover types, the areas classified as built-up or bare land exhibited the highest LST, and a change from vegetation to bare land led to an increase in LST. The correlation analysis indicated that the correlation coefficients between the normalized difference built-up index (NDBI) and LST ranged from 0.14 to 0.18 between 2000 and 2020 and that NDBI plays a dominant role in influencing the LST. The GWR analysis revealed the spatial variation in the association between the land cover composition and the SUHII. Parks with large areas of medium- and high-density vegetation play a significant role in regulating the thermal environment, whereas the scattered vegetation patches in the urban core do not have a significant relationship with the LST. These findings can be used to inform adaptive land use planning that aims to mitigate the effects of the UHI and aid efforts to achieve sustainable urban growth.the Strategic Priority Research Program of the Chinese Academy of Sciencesthe National Natural Science Foundation of ChinaPeer Reviewe

The Relationship Between Neighborhood Characteristics and Homicide in Karachi, Pakistan

The geographical concentration of criminal violence is closely associated with the social, demographic, and economic structural characteristics of neighborhoods. However, few studies have investigated homicide patterns and their relationships with neighborhoods in South Asian cities. In this study, the spatial and temporal patterns of homicide incidences in Karachi from 2009 to 2018 were analyzed using the local indicators of spatial association (LISA) method. Generalized linear modeling (GLM) and geographically weighted Poisson regression (GWPR) methods were implemented to examine the relationship between influential factors and the number of homicides during the 2009–2018 period. The results demonstrate that the homicide hotspot or clustered areas with high homicide counts expanded from 2009 to 2013 and decreased from 2013 to 2018. The number of homicides in the 2017–2018 period had a positive relationship with the percentage of the population speaking Balochi. The unplanned areas with low-density residential land use were associated with low homicide counts, and the areas patrolled by police forces had a significant negative relationship with the occurrence of homicide. The GWPR models effectively characterized the varying relationships between homicide and explanatory variables across the study area. The spatio-temporal analysis methods can be adapted to explore violent crime in other cities with a similar social context

Analysis and mapping of lunar wrinkle ridges (LWRs) using automated LWRs detection process with LROC-WAC and LOLA data

Maps of lunar wrinkle ridges (LWRs) were created from 70°N to 70°S and 140°E to 140°W (extracted and highlighted the major LWRs area) using automated LWRs detection process with Lunar Reconnaissance Orbiter Camera wide range angle camera and Lunar Orbiter Laser Altimeter data. Automatic detection of LWRs is challenging because the ridges are of irregular shapes and many ridges have been eroded and/or degraded over time. It’s a preliminary study of automated ridge detection from DEM data. Statistics and measurements of the extracted LWRs, including orientation, extent, length, height, and elevation offset, were performed based on the mapping of lunar ridges. The identified ridges were classified based on their orientation, distribution, direction, and each class were further divided over basalts, and nearby highlands. According to the findings, 3,375 segments with a total length of 26,455.01 km were identified, and the average elevation offset, width, and height of all the wrinkle ridges were 40.39 m, 3.47 km, and 0.29 km respectively after weighting by length. The LWRs were divided into three morphologies and distributions: parallel ridges, isolated ridges, and concentric ridges. The vast majority of LWRs were found in basalts area, with an extension into neighboring highland. The relations between the morphological parameters were further quantitatively analyzed, and a similar linear correlation between the width and height was found in each class of lunar ridges, implying that small and large ridges were formed as a continuum and that the three classes of ridges were probably formed by some common processes. Finally, the relations between the lunar wrinkle ridges and other geomorphic phenomena were analyzed, indicating that purely volcanic origin or buried premare structures are difficult to reconcile with the investigation. In addition, the consistency between the occurrence of the lunar wrinkle ridges and the thickness of lunar maria indicates that the formation of lunar wrinkle ridges is closely related to the lunar maria; nevertheless, the statistical NW direction of individual classes of LWRs also proposes the presence of an appropriate stress field during the process of their formation

Modelling of land use and land cover changes and prediction using CA-Markov and Random Forest

We used the Cellular Automata Markov (CA-Markov) integrated technique to study land use and land cover (LULC) changes in the Cholistan and Thal deserts in Punjab, Pakistan. We plotted the distribution of the LULC throughout the desert terrain for the years 1990, 2006 and 2022. The Random Forest methodology was utilized to classify the data obtained from Landsat 5 (TM), Landsat 7 (ETM+) and Landsat 8 (OLI/TIRS), as well as ancillary data. The LULC maps generated using this method have an overall accuracy of more than 87%. CA-Markov was utilized to forecast changes in land usage in 2022, and changes were projected for 2038 by extending the patterns seen in 2022. A CA-Markov-Chain was developed for simulating long-term landscape changes at 16-year time steps from 2022 to 2038. Analysis of urban sprawl was carried out by using the Random Forest (RF). Through the CA-Markov Chain analysis, we can expect that high density and low-density residential areas will grow from 8.12 to 12.26 km2 and from 18.10 to 28.45 km2 in 2022 and 2038, as inferred from the changes occurred from 1990 to 2022. The LULC projected for 2038 showed that there would be increased urbanization of the terrain, with probable development in the croplands westward and northward, as well as growth in residential centers. The findings can potentially assist management operations geared towards the conservation of wildlife and the eco-system in the region. This study can also be a reference for other studies that try to project changes in arid are as undergoing land-use changes comparable to those in this study