Journal of Applied and Emerging Sciences最新文献

{"title":"A Machine Learned Approach to Identify the Anomalies in Load Pattern of Pakistan","authors":"Adeel Shams","doi":"10.36785/JAES.111488","DOIUrl":"https://doi.org/10.36785/JAES.111488","url":null,"abstract":"The energy crisis of Pakistan is worsening day by day for different explicit and implicit reasons. Load pattern and its use in the studies of power system is a vital area. Here it is used for the identification and analysis of anomalies in the load pattern of Pakistan while using Support Vector Regressor Machine as a Machine Learning tool. The training phase has been provided with retrospective data of electrical load, temperature, and relative humidity so as to predict the future electrical load in the testing phase, based on the then data of temperature and relative humidity. Based on temperature, three groups of electrical load have been opted based on particle swarm optimization clustering namely moderate, cold and hot. The difference curve between the actual load and predicted load illustrated various anomalies in all of the three clusters. The high numbers of anomalies were found in the hot cluster whilst confirming the dependence of load pattern upon the weather parameters. The analysis of the difference curve between the patterns portrays to be deformed enormously. The analysis of the anomalies has also being carried out in terms of contextualized parameters.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"Simulation and Analysis of Active Power Filter for Mitigation of Power Quality Problems in a Wind Based Distributed Generation\"","authors":"I. A. Channa, M. A. Koondhar, Naveed Mohsin Mughal, Muhammad Shahzad Bajwa Bajwa, S. A. Bukhari, Muhammad Ismail Jamali","doi":"10.36785/2021111429","DOIUrl":"https://doi.org/10.36785/2021111429","url":null,"abstract":"The adoption of natural energy sources has seen a phenomenal rise during recent decades. The reason is an improvement in their energy conversion capabilities, as well as simplification of their associated electronic control circuitry. The result at their use at a localized distributed generation level. This work is an attempt to understand and present the power quality impacts of wind and solar power generation at a localized system of distribution voltage level. The simulation is finalized in MATLAB/SIMULINK. Next a very popular solving these power quality problems namely, active power filter beside its shunt type is tested over the simulated model. Moreover, its control algorithm is implemented mathematically with P-Q theory and the results are analyzed for better power quality improvement.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"4 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115995053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of noise on motor task functioning among young motorcyclist: A controlled experiment","authors":"Anila Ali, R. Hussain, Ali Asghar, S. Z. U. Hassan, G. Malghani, S. Khan, N. C. Dom","doi":"10.36785/jaes.111447","DOIUrl":"https://doi.org/10.36785/jaes.111447","url":null,"abstract":"Motorcycle is a complex machine, and its riding requires mental alertness along with mind and body coordination. On the road, motorcyclists are subjected to excessive level of noise (> 90 dBA). High noise exposure can impair the motor task functioning. The assessment of motor task (dexterity) of motorcyclists under noise exposure has not been examined formerly as well as their psychological health profiling. Therefore, this study is aimed to investigate the effects of noise-induced motor task functioning among young motorcyclists (19 – 24 yrs.). The controlled laboratory experiment was conducted on undergraduate university motorcyclists ( n = 60; 30 males, 30 females). Two groups were formed experimental (Exp-G; n = 30) and a controlled (Con-G; n = 30). The Exp-G operated motor activity test under 85-90 dBA motorcycle noise exposure, while Con-G exposed to controlled noise (65 dBA) levels. The sound level was examined concurrently by calibrated (114 dBA) Sound Level Meter. Purdue Pegboard battery test was used to measure motor task functioning consisting four subtests (Dominant Hand; Non-Dominant Hand; Both Hands; Assembly). The Independent sample t -test was used across all subtests to examine the comparison effect of motor task function (dexterity) between Exp-G and Con-G, and amongst genders. Result showed that the Con-G had significantly good quality presentation ( p 0.05). Based on mean values, male participants of the Exp-G performed better under high noise levels than females, while among Con-G, females performed better. The results demonstrated significant effect of motorcycle noise on decreased motor task functioning of the participants (Exp-G). Therefore, it concludes that on-road excessive noise level exposure can hinder the motor task functioning and can contribute to impair the reaction time on excruciating hazardous position.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117313811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Ontology-Driven Decision Support System for Rice Crop Production","authors":"Hifza Afzal, M. K. Kasi, B. Kasi, Bushra Naeem, S. K. Sami","doi":"10.36785/jaes.111410","DOIUrl":"https://doi.org/10.36785/jaes.111410","url":null,"abstract":"Agriculture domain now extensively uses the Internet of Things (IoTs) technology to provide farmers with proper and accurate information. Assisting farmers regularly and periodically in a more efficient manner is totally based on complete data, proper planning, and decision making. Connecting devices with each other through IoT has brought huge changes to traditional way of farming. However, it has also invited some challenges such as the semantic interoperability, quality and accuracy of data. In this paper, we extend a base farming ontology to include classes comprising of water, pesticides, and seeds information that is organized both seasonally and phase-wise. We have extended a farming ontology specifically a crop production domain using rice crop as a case study. Semantic Web Rule Language (SWRL) integrated with Jess rule engine is used for reasoning and inferencing to make devices understandable to each other. A collection of 54 SWRL rules reason about 101 OWL classes in order to maintain water irrigation in rice crops. It also provides pesticide and weedicide information for each growth stage along with seed information by identifying specific crop type. This helps the farmers to obtain better results in terms of production and sustainability from the collected data by offering them decision making support in the management of rice crops.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132830592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land Cover Classification using Machine Learning Approaches from High Resolution Images","authors":"Akhtar Jamil, A. A. Khan, A. Hameed, S. Bazai","doi":"10.36785/jaes.111501","DOIUrl":"https://doi.org/10.36785/jaes.111501","url":null,"abstract":"Land cover classification has become an interesting research area in the field of remote sensing. Machine learning techniques have shown great success for various application in the domain of land cover classification. This paper focuses on the classification of land covers obtained from high resolution images using two well-known classification methods by integrating with object-based segmentation technique. First, graph-based minimal spanning tree segmentation was applied to segment the original image pixels into objects. The segmented objects were then used to obtained spectral, spatial and texture features which were then combined to form a single high dimensional feature vector. These features were then used to train and test the artificial neural network (ANN) and support vector machine (SVM). The proposed method was evaluated on a dataset consisting of high resolution multi-spectral images with four classes (tea area, other trees, roads and builds, bare land). The experiments showed that ANN was more accuracy as it scored average accuracy of 82.60% while SVM produced 73.66%. Moreover, when postprocessing using majority analysis was applied, the average accuracy improved to 86.18%.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landslide Inventory and Landslide Susceptibility Mapping for China Pakistan Economic Corridor (CPEC)’s main route (Karakorum Highway)","authors":"Hasnain Abbas, A. A. Khan, D. Hussain, G. Khan, Syed Najam ul Hassan, Isma Kulsoom, Sadiqa Hussain, S. Bazai","doi":"10.36785/2021111461","DOIUrl":"https://doi.org/10.36785/2021111461","url":null,"abstract":"The development of landslide inventory is the first step towards landslide hazard management and planning. The proper inventory will also help to develop landslide susceptibility maps which will result to minimize economic and human losses. This work investigates landslide hazard mapping in the rugged mountain terrain vis-a-vis highly economically significant route between China and Pakistan i.e. Karakuram Highway (KKH). KKH is passing through the Karakorum mountainous region where landslides occur frequently and pose a serious threat to local travelers and tourists as well as to trading caravans. In this work, landslide inventory was developed (302 landslides) along KKH by visual interpretation of Sentinel and google images. Field survey was also carried to validate landslide datasets. The landslide dataset was divided into modelling/training (70%) and testing/validation (30%) datasets to develop and validate landslide susceptibility maps (LSM) using three models Frequency Ratio (FR), weight of evidence, and Analytic Hierarchy Process (AHP). To develop LSMs, landslide controlling factors that include Slope, Aspect, Landcover, Geology, Proximity to Fault, Distance to Road and Stream, and Precipitation are correlated and considered using GIS techniques. LSMs generated using testing datasets are validated by Area Under Curve (AUC) criterion.  The results show that weight of evidence, FR and AHP have success rate curves of 61%, 84% and 72%, respectively. In addition, most highly accurate three models are validated for their prediction power using testing landslide datasets. The results for prediction capacity for weight of evidence, FR and AHP are 72%, 64%, and 58%, respectively. At the end, landslide susceptibility index (LSI) maps were classified into susceptibility zones. We also compared variation of weights in each class in AHP and FR model. The overall trend of increase or decrease in weights remains same except in few classes like precipitation class. The validation and prediction results show that FR model is the most reliable and accurate model which can be used for landslide management and planning. Our results will be helpful to minimize landslide hazard losses along KKH, ultimately assisting in successful implementation of CPEC idea between China and Pakistan.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114452389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Efficient Node Deployment for Heterogeneous Wireless Sensor Networks","authors":"Shahzad Hassan, Shahida Khanam, M. Ahmad., Imtiaz Alam","doi":"10.36785/jaes.111486","DOIUrl":"https://doi.org/10.36785/jaes.111486","url":null,"abstract":"Wireless Sensor nodes are power-constrained devices and the lifetime of the nodes is significantly influenced by the deployment of the nodes. In the appropriate deployment of the nodes leads to inefficient network energy utilization which results in a minimized network lifetime. To enhance the network lifetime within the limited battery power, hierarchical heterogeneous routing has been proposed by various researchers and have significantly prolonged the network lifetime. In heterogeneous wireless sensor networks, the researchers have addressed mainly energy efficiency of the network but node deployment has been rarely addressed. Node deployment is a critical issue in heterogeneous wireless sensor networks since the nodes in these networks are energized with different energy levels. The simulation results obtained proved that the appropriate deployment of nodes can lead to a substantial amount of energy conservation.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125697769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Desulfurization of Mach Coal of Balochistan by Leaching Method","authors":"F. Mushtaq, A. Ullah, Asfandyar Khan, A. Waheed, S. Sultan, Ghulamullah Kakar, G. Khan, A. M. R. Abbasi","doi":"10.36785/jaes.111438","DOIUrl":"https://doi.org/10.36785/jaes.111438","url":null,"abstract":"Coal desulfurization prior to usage is frequently subjected to preprocessing to achieve clean fuel and reduce environmental impacts. In this study, desulfurization of Mach coal of Balochistan was investigated with different leaching solvents. The solvents used are NaOH and HNO 3 . Effects of particle size and solvent weight% on sulfur removal were studied, whereas the leaching temperature and the agitation time were kept constant. Desulphurization experiments were carried out for 12 samples of different composition based on different particle size and solvent weight%. Significant reduction in Sulfur was attained when the coal particle size of 10 Mesh was used. The results indicated that Sulfur reduction was highest of 44.88% when HNO 3 was used as compare to NaOH which gave maximum Sulfur reduction of 24.72%. Sulfur recovery was found to increase with increasing solvent concentration. Decreased desulfurization was observed with larger coal particle size of 6 Mesh. Leaching process using variable solvent concentration was found effective and could be inexpensive for desulfurization of coal.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122145532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient adsorption of Malachite Green from water by activated carbon of Date trunk fiber","authors":"R. Ullah, H. Muhammad, Saif Ullah, Sahid Mehmood, Nasir Abbas Khan, Fazal Haq, W. Uddin, Naeem Ullah, Z. Ali, Hammal Majeed","doi":"10.36785/jaes.111443","DOIUrl":"https://doi.org/10.36785/jaes.111443","url":null,"abstract":"Abstract: Water remains one of the most important mediums for the survival of Living organisms. However, because of the human activities, it has lost its nature and becomes extremely polluted. Among various pollutants, the synthetic dyes have huge contribution for the contamination of the natural water bodies because of their vast application in food, cosmetics, pharmaceutical, textile etc. The presence of such hazardous contaminants causes cancer, kidney failure, dysfunction of brain, infertility etc. Consequently, their removal is indispensable prior to releasing them in natural water resources. Here, low cost adsorbent (activated carbon) was prepared from date palm trunk fiber by using chemical activation using H 3 PO 4 as activating agent. That was utilized for removal of basic cationic dye Malachite Green as a model dye from water by using the Batch adsorption method. The effect of different parameters including adsorbent amount, pH and contact time were studied. The optimum conditions determined were adsorbent dosage 0.5g, contact time 20 minutes and pH5-7. From the result, we conclude that activated carbon of date fiber remains an efficient adsorbent for removal of Malachite Green and may prove the best low cost adsorbent for other dye effluents and wastewater treatment.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115907601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PI and Fuzzy Logic Controller based Comparative Analysis of Separately Excited DC Motor","authors":"M. A. Koondhar, I. A. Channa, S. A. Bukhari, Muhammad Ismail Jamali, Sadullah Chandio, A. Memon","doi":"10.36785/2021111414","DOIUrl":"https://doi.org/10.36785/2021111414","url":null,"abstract":"Separately excited dc motors (SEDCM) are generally used in laboratory and industrial applications due to their high efficiency, performance response and high torque. An idea is proposed in this paper by applying the PI and Fuzzy Logic Controller (FLC) to control the speed of SEDCM. Simulink model with and without PI and FLC has been developed in Matlab to analyze the performance of dc motor. Based on simulation results it is said that control characteristics of FLC are better than the conventional PI controller. The modeling of SEDCM and execution of the controllers is carried out in MATLAB.","PeriodicalId":199446,"journal":{"name":"Journal of Applied and Emerging Sciences","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129458353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}