Diffusion of ICT in Rural Areas Community for Socio-Economic Development under the Platform of E-CLRC

This research study proposed a framework for Community Learning and Resources Center for ICTs literacy, awareness, skills and use in disadvantage and rural areas of developing countries, in order to improve the quality of education and socio-economic in youth using the artistic use of ICTs towards accomplishing the goal such as “No child Left Behind” owing to lack of access and monetary resources in rural and remote areas. The study conducted with tie relationship with National ICT strategy  (NICTS) and Education for All(World Education forum Dakar 2000 (WEF2k)) , it compares and lists the benefits of E-CLRC in context of NICT strategy and WEF 2000,  A series of seminars, workshops and group discussion conducted in selected areas of Gilgit-Baltistan of Pakistan including schools, communities and parents. This was a voluntarily initiated by youth to start an ICT awareness campaign in the rural areas of Pakistan. It also aims to find out the current ICT implementation level in schools and other educational Institutions. This E-CLRC will increase access to valuable information that gratifies diversified needs of various segments such as ICTs, socio-economic development and team work capability of native populace. Keywords: Information and communication technologies, E-Community Learning Resources Center, World Education Forum, CBES

Gemmological Characteristics of Gemstone Varieties Found in the Pegmatite of Haramosh Area, Gilgit-Baltistan

Haramosh valley is located in eastern side of Gilgitcity (Fig. 1). Geographically it is located between74°44' 17.37 " E and 35° 51 '8.97 " N. The area is asub range of Karakoram in the south-central region ofthe Rakaposhi–Haramosh mountains. Haramosh valleyis famous for its gemstones which are well known inthe world. The first gem mine was discovered in 1951in the area of Haramosh valley in Gilgit. Theprominent four localities of gem-bearing pegmatitesoccur in the vicinity of the Haramosh peak, Shengusalong Indus river, Haramosh Bulachi village, and thesetting of Khaltoro pasture. Along with glaciers,Hindukush Karakorum and Himalayan ranges host avariety of precious stones (Agheem et al., 2014). Inrecent decade Haramosh valley received moreattention because of the occurrence of a variety ofgems in pegmatite veins. Gemstone varieties related topegmatites are also found in other parts of GilgitBaltistan, like Shigar, Shengus, and Stuk Nala (Kazmiet al., Laurs et al., 1998).Pegmatites are found widelyin Gilgit-Baltistan Pakistan within the mountain rangesof Karakoram (Laurs et al. 1998). These macroliticpegmatite’s are mainly associated with leucogranites inHaramosh Massif, which is famous for recent rapiduplift (Laurs et al., 1998; Zeitler 1985). Variouscrystals of topaz, tourmaline, beryl, and quartz arebeing mined from these macrolitic pegmatite’s (Laurset al., 1998). Famous tourmaline crystal (10cm) ofPakistan is found in Stuk Nala of Nanga ParbatHaramosh Massif (Laurs et al., 1998)

Revisiting Routing Protocols to Design Energy Aware Wireless Body Area Network

Wireless body area networks (WBANs) a special type of wireless sensor networks (WSNs) in which sensor nodes to actualize continuous wearable wellbeing observing of patients are able to provide improved healthcare services in a distributed infrastructure less environments. However, the mobile node, due to less battery power, can easily suffer from the problem of energy level when control packets are transfer among nodes—a problem that can occurs by the fact that some sensor nodes may select wrong cluster head with inappropriate path and waste the resources. Although many energy efficient methods have been designed for the traditional sensor networks, there has been limited focus on incorporating WBANs into energy efficient schemes. Therefore, in order to incorporate above issue we revisit the already designed traditional energy efficient methods with cluster head selection protocols and optimal path transformation. Therefore, we encourage researchers to insert WBANs with existing methods to improve performance. However, some work has been done in WBANs that uses energy efficient methods to manage the routing issue, this research domain requires further research attention. Therefore, we discuss the current research work and purpose many future directions of research

Landslide Susceptibility Assessment Using Bivariate Method: A Case Study from River Neelum and Jehlum Catchment Area

Landslide is a frequently occurring natural calamity in the northern areas of Pakistan. The current study is aimed to assess the susceptibility of landslide hazard to highlight the vulnerable areas for the purpose of risk reduction along Neelum and Jehlum rivers in district Muzaffarabad. A data-driven predictive approach was adopted to conduct this study by using Weight of Evidence (WOE) model along with eleven conditioning factors. A spatial distribution map of landslides was prepared using orthophoto, previous records, and derivatives (hill shad, topographic openness, slope, aspect, curvature) of Digital Elevation Model (DEM). The results show that the roads, lithology, and rivers are the most important triggering factors for landslides in both valleys. Approximately 30% of the area is under low susceptibility zone in Jhelum valley while only 13% of the area falls under low susceptibility zone in Neelum river valley. In Jhelum river valley the medium susceptibility zone covers 35% of the total area whereas, Neelam river valley has 26% of the total area under medium susceptibility zone. Around 61% of the land in the Neelam river valley and 35% of the land in the Jhelum river valley are under high susceptibility zone. The area under high hazard lies in the north-east of the district due to multiple conducive factors to trigger landslides including weak lithology (mudstone, sandstone, shales, and clays), high altitude along steep slopes and excessive precipitation (1800 mm/ year). Furthermore, the high hazard zone in study area is not suitable for construction purpose but was suitable for plantation. The validation result (89.41%) is justifying the performance of this model

A Comparison Between Schlumberger and Wenner Configurations in Delineating Subsurface Water Bearing Zones: A Case Study of Rawalakot Azad Jammu and Kashmir, Pakistan

The Schlumberger and Wenner Electrical Resistivity Survey techniques have been used in comparison for the determination of groundwater potential in District Rawalakot, Azad Jammu and Kashmir. The terameter SAS4000 with accessories was used for data acquisition. The data were processed by employing IPI2WIN software to determine the depth, thickness and true resistivity of the subsurface layers. The present study indicated the subsurface depth coverage of Schlumberger configuration is greater than Wenner configuration. The apparent resistivity maps using both Wenner and Schlumberger techniques at the same locations have been prepared at 3m, 4m, 9m, 10m, 27m, 30m, 50m, 51m, 100m, and 150m depths respectively for groundwater assessment. The differences in resistivity contour closures, in both types of maps, arise due to lateral variations of subsurface lithology. Longitudinal conductance, transverse resistance and anisotropic maps were also prepared. The different contour closures in the Wenner map were due to mixed lithology of alluvium with variable water contents. The subsurface geology i.e. clay, sandstone boulder clay, and dry sandy soil were interpreted which are in close agreement with the surface geology of the area. The aquifers of the project area are designated as confined and unconfined good water potential indicated by low values of resistivity. The water-bearing strata consist of sand, gravel, boulder clay and sandy clay

Predicting Emerging Trends on Social Media by Modeling it as Temporal Bipartite Networks

The behavior of peoples' request for a post on online social media is a stochastic process that makes post's ranking highly skewed in nature. We mean peoples interest for a post can grow/decay exponentially or linearly. Considering this nature of the evolutionary peoples' interest, this paper presents a Growth-based Popularity Predictor (GPP) model for predicting and ranking the web-contents. Three different kinds of web-based real datasets namely Movielens, Facebook-wall-post and Digg are used to evaluate the performance of the proposed model. This performance is measured based on four information-retrieval metrics Area Under receiving operating Characteristic (AUC), Novelty, Precision, and Kendal's Tau. The obtained results show that the prediction performance can be further improved if the score is mapped onto a cumulative predicted item's ranking.https://doi.org/10.1109/ACCESS.2020.297613

Data redundancy reduction for energy-efficiency in wireless sensor networks: a comprehensive review

Wireless Sensor Networks (WSNs) play a significant role in providing an extraordinary infrastructure for monitoring environmental variations such as climate change, volcanoes, and other natural disasters. In a hostile environment, sensors' energy is one of the crucial concerns in collecting and analyzing accurate data. However, various environmental conditions, short-distance adjacent devices, and extreme usage of resources, i.e., battery power in WSNs, lead to a high possibility of redundant data. Accordingly, the reduction in redundant data is required for both resources and accurate information. In this context, this paper presents a comprehensive review of the existing energy-efficient data redundancy reduction schemes with their benefits and limitations for WSNs. The entire concept of data redundancy reduction is classified into three levels, which are node, cluster head, and sink. Additionally, this paper highlights existing key issues and challenges and suggested future work in reducing data redundancy for future research

Application of neural network and electrodynamic sensor as flow pattern identifier

Purpose: Solid particles flowing in a pipeline is a common mode of transport in industries. This is because pipeline transportation can avoid waste through spillage and minimizes the risk of handling of hazardous materials. Pharmaceutical industries, food stuff manufacturing industries, cement, and chemical industries are a few industries to exploit this transportation technique. For such industries, monitoring and controlling material flow through the pipe is an essential element to ensure efficiency and safety of the system. The purpose of this paper is to present electrical charge tomography, which is one of the most efficient, robust, cost-effective, and non-invasive tomographic methods of monitoring solid particles flow in a pipeline. Design/methodology/ approach: Process flow data are captured by fitting an array of 16 discrete electrodynamic sensors about the circumference of the flow pipe. The captured data are processed using two tomographic algorithms to obtain tomographic images of the flow. Then a neural network tool is used to improve image resolution and accuracy of measurements. Findings: The results from the above technique show significant improvements in the pipe flow image resolution and measurements. Originality/value: The paper presents electrical charge tomography, which is one of the most efficient, robust, cost-effective, and non-invasive tomographic methods of monitoring solid particles flow in a pipeline