Asian Journal of Engineering, Sciences & Technology
Abbreviated key title: AJEST
Published by: Iqra University
Months: March & September
Start year: 2011
Title: A Proposed Disaster Recovery Model for Customer Relationship Management using Cloud Computing Author(s): Engr. Ali Ahmed, Huma Ali Ahmed
Abstract: These days we have seen that data has been generated in very huge amounts which requires recovery services. Cloud computing provides a huge platform for sharing the data on many places. It introduces a lot of services like infrastructure as a service (IaaS) that provides virtual and physical resources, software as a service (SaaS) which delivers software that provides remote accessibility for consumers over the Internet, platform as a service (PaaS) that delivers computing tracks mostly includes in programming languages and operating systems and network as a service (NaaS) that provides actual network transport data connectivity services. Now we have another recovery service named disaster recovery as a service (DRaaS) which is used to replicate data on multiple servers. DRaaS can be used at the time when servers lost data and unable to provide information. In this research paper, we are going to propose a model for customer relationship management (CRM) using DRaaS which will reduce the problem for data loss. This model will also resolve the latency issues over the cloud for CRM users.
Title: Human Motion Based Energy Harvester for Bio-Medical Devices Author(s): Muneeb Ullah Anjum, Farid ullah Khan
Abstract: This paper presents a human motion based electromagnetic energy harvester for bio-medical devices. This harvester is composed of a Teflon tube, cylindrical magnets, rubber spring and wound coils. The developed energy harvester is tested on an experimental setup which has been developed to test power generation capability of the device with the vibration shaker at 3 g acceleration level. The combined open circuit maximum voltage of 4140 mV is generated by the harvester at 19 Hz and 3 g. Moreover, the harvester produced an optimum load power of 1.89 mW at a load resistance of 25 W and successfully recharges a 1.5 V battery in 60 min.
Title: Aggregate Model: An Approach to Improve Query Response Time for Bulky Data Author(s): Aniqa Nawaz Bhutto, Suhni Abbasi, Sanober Behrani
Abstract: Sensor network is collection of huge number of sensor nodes to capture and monitor the physical sensing capabilities such as temperature, sound, light, humidity, pressure, etc. At the Present sensor networks supposed to be active and pre-programmed devices that can continuously forward data to the central storage location for analysis and to performing oine queries. For such tremendously growing data from sensors, prevailing tools and methods are required to process data eciently and accurately instantly; otherwise the response time of data processing will be too much annoying. To overcome this challenge, an aggregation model was designed to improve query response time to overall improve the quality of the sensor network data. The developed model consists four sub modules i.e. source, time, query, and data module. Source module comprises dierent aggregate functions. Time module is about to apply aggregation at three dierent time intervals. Query Module had defined that one finest aggregation level is not sucient to answer all queries because each query varies in their nature. Data module was performed to improve the accuracy of the data. The result of the study revealed that applying the aggregation at dierent time intervals improved the query response time and accuracy measurement has the significant impact on the quality of the data.
Title: Fuzzy Logic Based Adaptive Traction Control System Author(s): Imtiaz Hussain Kalwar, Mansaf Ali Abro, Ali Asghar Khoso
Abstract: significant role is played by traction control system (TCS) in road vehicles, because slip occurs during driving on wet road or snowy surface. However, it is very dangerous to drive on the icy or snowy road without traction control system, because in that condition the vehicle can lose its path. In such condition, to control a vehicle is very difficult task for drivers. Drivers can regulate easily the traction torque of vehicle driving on difficult surface by using TC system. It also makes our journey safe. Owing to such system high way automation system can be made safer. In high way automation system it plays very crucial role as well. Therefore, TCS estimates the slip of each wheel and distribute traction torque between the wheels. Thus, it makes better the longitudinal performance of a given vehicle. In simulation it is analyzed that traction control system plays important role in road vehicles. So, there are four different cases of traction torque distribution shown while driving on different road conditions. Therefore, traction torque is distributed with respect to the slip of each wheel. In case of increasing slip in either of the wheel the traction torque will be distributed accordingly. Actually, in the given system a torque is distributed corresponding to the slip of each wheel. When a wheel loses its traction then traction control system activates and minimizes the torque of the given wheel. In contrast, it will involve maximum traction torque to opposite wheel. Similarly, it can be observed that traction torque will be reduced to the wheel which is spinning. Control system will observe the whole phenomenon of slip and distribute traction torque either high or low according to the value of slip. However in this research work cost effective and very simple techniques are adopted.
Title: Performance Analysis of MMSE Channel Estimation in Multiuser Massive MIMO System under Log-Normal Shadowing Author(s): Muhammad Ahsan Shaikh, Vali Uddin, Muhammad Moinuddin
Abstract: This paper analyzes the performance of MMSE channel estimation in multiuser massive MIMO system under the Log-Normal shadowing. In this system, there are K number of decentralized User Equipment (UE) with single antenna and large number of antennas at the base station (BS). Pilot symbols are utilized for time division duplex (TDD) channel estimation. Performance of MMSE channel estimation of two existing algorithms is analyzed at different values of power pathloss, at different number of users, and at different number of antennas at the BS in the system. Results show that the performance of channel estimation degrades with the increase in the number of antennas at BS and the number of users in the system due to increase in the channel path. Performance of the two algorithms in channel estimation is also compared for different values of power path loss.
Title: Multi-mode Vibration based Electromagnetic type Energy Harvester for Structural Health Monitoring Author(s): Iftikhar Ahmad, Farid ullah Khan
Abstract: A multi-mode vibration based electromagnetic type energy harvester has been illustrated in this work. The harvester consists of two planar movable coils (PMCs), acrylic spacers and permanent magnets placed on a membrane (latex). Fabrication and experimentation of the prototype is presented. The PMC and acrylic spacers are fabricated through computer numerical control (CNC) machine. The prototype is characterized at a frequency sweep of 5-200 Hz under various acceleration levels. The device has three resonant frequencies of 73 Hz, 100 Hz and 123 Hz at relatively higher acceleration level of 3 g. Single PMC of the prototype at resonant frequency (first) of 73 Hz and a vibration level of 3 g yields a voltage amplitude of 16.6 mV and output power of 65.24 W.
Title: Standby Mode Minimization and Periodic Controlling For Efficient Building Energy Management System Using Fuzzy Logic and Image Processing Tool Author(s): Engr.Waqar Tariq, Ir. Dr .Lutfi Othman, Engr.Abid Mustafa
Abstract: In regards of smart and efficient energy management, many think that standby mode is purely the solution in reducing the electrical usage. However, the standby mode of electrical appliances is also among one of the main factors that contributes to the electrical wastage as the appliances still consume electrical energy during the standby operation. This research mainly focuses on creating a Fuzzy Expert System (FES) with a combination of image processing that minimizes the standby mode or phantom load and to evaluate the performance of the created dummy load system based Prototype. Applying the results of this research, the standby mode of the electrical appliances can be controlled automatically and manually and also minimized based on the desired fuzzy rules set. Hence it can be concluded that minimal use of electrical energy in standby mode or phantom load in electronic appliances can be achieved by using techniques of image processing and fuzzy controls which will can ensure minimum wastage of electricity.
Title: Electricity Demand Forecasting: A Pakistans Perspective Author(s): Suhail Ahmed Shaikh Nayyar Hussain Mirjat Wajahat Shabbir Korejo Gordhan Das Walasai Abdul Sattar Larik Arsalan Hussain
Abstract: Accurate and realistic electricity demand projection has attained greatest ever importance in overall energy planning. Various methods are found in the literature for electricity demand forecasting ranging from econometric models to statistical tools and the energy models. The demand of electricity in the country has increased along with the number of electricity consumers in Pakistan over last 2-3 decades. However, the countrys energy and power departments capacity to rationally forecast electricity demand and subsequent planning as well as the implementation of developed strategies has not delivered to meet the demand. This paper examines the long-term electricity demand forecasting approaches and specifically reviews the demand projection studies as well as methodologies used in the past. There are mainly five consumer groups identified in the electricity sector of Pakistan i.e. domestic, commercial, industrial, agriculture and other. The growth parameters of each of these groups are pivotal to more accurate electricity demand projection. The Water and Power Development Authority (WAPDA) for nearly 40 years following the independence was responsible for power sector planning. However, following the restructuring of WAPDA, National Transmission and Dispatch Company (NTDC) in coordination with Distribution Companies (DISCOs) undertake electricity demand projection studies. This review finally identifies various loopholes in electricity planning and suggests various parameters and steps which require due consideration for electricity demand forecasting in Pakistan.
Title: Predicting User Mood by Classifying Music Genres from Facebook Shares and Likes Author(s): Sanober Behrani , Suhni Abbasi, Aniqa Nawaz Bhutto
Abstract: Music is part of art when it comes to recreation entertainment or it can be considered as the source of therapeutic medium. The music is grouped in different genres, the most common way to differentiate among these genres is to label an artist or song as belonging to a specific genre, like classical, pop, folk, ghazal, bhangra, rock, Noha, Naat/Hamd and many others. However, prediction of user mood such as positive, negative, energetic, sleepy by analyzing their music genres specifically for Indian and Pakistani songs is still a key issue. One of the most common way to get peoples likes about their music, movies, books etc is Social Networking Sites. Thus, the music related data were collected from Facebook Social Network Users. The collected data holds many issues such as duplication of the data, missing data, noise and intentional errors. After performing the data cleaning process, mid-level features were extracted from each instance and data set was prepared for music genre classification. The training and testing set was prepared using 10-cross fold options. J48 classifier, Decision tree and ROC plot are used for prediction model. For the classification of music genres, the results indicated 0.894 True positive rates for the entire genre whereas the average False Positive rate for different genres is close to zero. For prediction of the mood prediction True Positive rate is close to or equal to 1 for almost all the identified moods. Recall values for all the mood is also significant except the mood EXCITED.
Title: Semantic Feature Extraction using Feed-Forward Neural Network for Music Genre Classification Author(s): Danyal Imran , Hina Wadiwala, Muhammad Atif Tahir, Muhammad Rafi
Abstract: Music genre is a conventional category that identifies some piece of music as belonging to a shared tradition or set of conventions characterized by similarities in form, style or subject matter. Traditional method of genre classification tends to extract features and use them to predict labels. These features are independent of each other and do not provide meaning to music genre classification process. In order to achieve semantic meaning of features, feed-forward neural network model with stochastic gradients descent and back propagation algorithm with the categorical cross entropy loss function is investigated in this paper. The main objective is to identify complex patterns that can help in music genre classification. Experiments are performed on AMG1608 dataset and results have indicated significant performance gains when compared with existing approaches.
Title: Sentiment Classification of Customer Reviews Using Bayesian Classifier Author(s): Muhammad Rizwan Rashid Rana, Muhammad Aun Akbar, Tauqeer Ahmad
Abstract: Sentiment Classification is the process of exploring sentiments, emotions, opinions and facts in the sentences which are expressed by the people. Machine learning techniques and Lexicon based techniques are mostly used in sentiment classification to predicate sentiments from customers reviews and comments. In this paper, we aim to classify movie reviews in positive and negative classes by using Naive Bayes classifier (Machine Learning algorithm). Experimental results shows that accuracy of Naive Bayes classifier on large movie reviews dataset is 86.8%.
Title: Performance Analysis of Short Distance Wireless Sensor Networks using MoteView Author(s): Waseem Ahmed, Mehboob Ul Haq, Saqib Ali, Bilal A. Alvi, M. Irfan Anis
Abstract: Current era of advancement in microelectroniccommunication and networking has inspired researchers to analyse, design and develop cost effective integrated sensing, computing and communicating through Wireless Sensor Network (WSN). WSN is a group of lowpowered, tiny devices capable to sense the environment, gather and process that sensed data and communicating with each other to achieve certain results of common tasks. In this paper, the results and models of experiments supported and using the Wireless sensor equipment with distances extending from 80m to 100m are presented. The results illustrate that Short distance wireless sensor networks (SDWSN) are conceivable and the distance affect the quality of those links.
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