Mehran University Research Journal of Engineering and Technology

6

Authors: Sadaf Noshin; Humaira Kanwal; Abrar Ahmad

Energy consumption of lighting can be reduced by using different daylight control strategies. The rise in environmental distresses requires the necessity of natural light control systems. Light shelf is considered as excellent lighting control scheme that provides great lighting production and inexpensive prospect via entering the daylight inside the space. The aims of this study shows that the daylight efficiency and visual productivity are affected by the design parameters of light shelf such as its angle, location and height. In this research, Autodesk Ecotect 2011 is used for the daylight simulation of summer solstice and winter solstice days under overcast sky conditions on a nominated theoretical study space of an institutional building. Daylight simulation is carried out to evaluate the illuminance requirement within the selected space and analysis is also executed on the model with selected categories of light shelves including different positions, heights and angles. The acquired data is then exported on Radiance software intended for complete day-light investigation. The results of this research shows that external light shelf at a height of 7' and an angle of 20˚ is the most appropriate choice in prevailing the glare and it also enhanced the illuminance level to11.5% in 21st June and 10.6% in 21st December as compared to without light shelves. Furthermore, the shaded range is decreased by the rise in the angle of Light shelf which has a tendency to increase the inside average lighting. Hence, significant consideration should be given to the height and position of light shelves, since it has a superior effect on light shelf performance.

7

Authors: Maryam Zaffar, Manzoor Ahmad Hashmani, K.S. Savita, Syed Sajjad Hussain Rizvi, Mubashar Rehman

The Educational Data Mining (EDM) is a very vigorous area of Data Mining (DM), and it is helpful in predicting the performance of students. Student performance prediction is not only important for the student but also helpful for academic organization to detect the causes of success and failures of students. Furthermore, the features selected through the students’ performance prediction models helps in developing action plans for academic welfare. Feature selection can increase the prediction accuracy of the prediction model. In student performance prediction model, where every feature is very important, as a neglection of any important feature can cause the wrong development of academic action plans. Moreover, the feature selection is a very important step in the development of student performance prediction models. There are different types of feature selection algorithms. In this paper, Fast Correlation-Based Filter (FCBF) is selected as a feature selection algorithm. This paper is a step on the way to identifying the factors affecting the academic performance of the students. In this paper performance of FCBF is being evaluated on three different student’s datasets. The performance of FCBF is detected well on a student dataset with greater no of features.

8

Authors: Ayesha Amir Siddiqi, Attaullah Khawaja, Adnan Hashmi

Computed Tomographic (CT) imaging is extensively implemented for liver tumor visualization and detection. Computer aided image processing algorithms can provide aid to the physicians and radiologists in detecting deadly diseases of liver specifically cancerous liver tumors. This paper presents a novel image processing technique to automatically classify liver for its abnormality without going through the liver segmentation stage. The study is conducted on a dataset of 39 samples of abdominal CT images. The CT dataset comprises of images bearing unhealthy liver. The unhealthy liver is further divided into livers bearing malignant tumors namely hepatoma and benign tumors namely hemangiomas. The methodology adopted for the study comprises of feature extraction from original CT images of all types of liver with special focus on textural information. The extracted features undergo the process of classification for malignancy and benignancy of the liver tumor. The classifiers used for textural feature analysis include Support Vector Machines (SVM), K-Nearest Neighbor (KNN) and ensemble classifier. Amongst these classifiers SVM yields a classification accuracy of 100% as compare to KNN and ensemble classifier which give the classification accuracy of 94.7% and 52.6% respectively. The proposed method of classification applied on entire abdominal CT scans without segmentation is performed by using the feature extraction matrix of structural similarity index (SSIM), which gives an improved classification accuracy of 100% as compared to the traditional GLCM matrix. The methodology can be tested to classify the liver for malignancy using other non-invasive techniques of ultrasounds and Magnetic Resonance Imaging (MRI) as well.

8

Authors: Muhammad Mithal Lund; Muhammad Ibrahim Keerio; Shamsuddin Tunio; Allah Wadhayo Gandahi; Inayatullah Rajpar

An experiment was executed at experimental farm of Sindh Agriculture University Tandojam to quantify the losses in grain yield and quality of wheat in relation to time and method of harvesting. The experiment involved three bread wheat varieties (Kiran-95, Mehran-89 and TD-1) and two harvesting methods; conventional method using Sickle and mechanized method using Reaper. The harvesting times considered were: 5-days-before-maturity (DBM), 5-Days-after-maturity (DAM), 10 DAM, and 15 DAM. The data were recorded for grain yield, yield components (harvest index, seed index, etc.) and some grain quality traits (shriveled & broken grain losses). The results highlighted that, harvesting with reaper was most effective and economical in terms of losses to grain yield and quality over sickle (manual) method of harvesting. Compared to the other harvesting times tested in this study, the wheat crop harvested at proper physiological maturity (5 DAM) was found to be most effective and beneficial to maintain quality and obtain maximum grain yield. Generally, wheat crop harvested through conventional method using sickle showed more harvesting losses at different harvesting intervals. Among three wheat cultivars, the cultivar TD-1 harvested with sickle (manual method) at proper maturity, 5 DBM and 5, 10 and 15 DAM showed 5.55%, 6.54%, 7.09%, 8.06% and 9.45% harvesting losses; and 8.79%, 10.46%, 10.67%, 11.76% and 13.25% hauling losses, respectively. Contrarily, when same cultivar TD-1 was harvested through mechanized method using reaper, the respective treatment plots showed 5.35%, 6.09%, 6.21%, 7.07% and 8.49% harvesting losses, and 8.57%, 9.89%, 9.54%, 10.45% and 11.99% hauling losses to grain yield, respectively. This study suggests that wheat crop should be harvested with reaper at proper physiological maturity. Among the three bread wheat varieties included in the study, the variety Kiran-95 proved to be the most resistant to grain yield and quality losses.

10

Authors: Mushtaq Ahmad Khan; Zawar Hussain Khan; Haseeb Khan; Sheraz Khan; Suhail Khan

Image denoising is a fundamental problem in both image processing and computer vision with numerous applications. It can be formulated as an inverse problem. Variational methods are commonly used to solve noise removal problems. The Total Variation (TV) regularization has evolved from an image denoising method for images corrupted with multiplicative noise into a more general technique for inverse problems such as denoising, deblurring, blind deconvolution, and inpainting, which also encompasses the Impulse, Poisson, Speckle, and mixed noise models. Multiplicative noise removal based on TV regularization has been widely researched in image science. In multiplicative noise problems, original image is multiplied by a noise rather than added to the original image. This article proposes a novel meshless collocation technique for the solution of a model having multiplicative noise. This technique includes TV and local collocation along with Multiquadric Radial Basis Function (MQ-RBF) for the solution of associated Euler-Lagrange equation for restoring multiplicative noise from digital images. Numerical examples demonstrate that the proposed algorithm is able to preserve small image details while the noise in the homogeneous regions is removed sufficiently. As a consequence, our method yields better denoised results than those of the current state of the art methods with respect to the Peak-Signal to Noise Ratio (PSNR) values.

11

Authors: Muhammad Awais Shafique; Eiji Hato

Household trip data is of crucial importance for managing present transportation infrastructure as well as to plan and design future facilities. It also provides basis for designing new policies, implemented under Transportation Demand Management, and assessing their effectiveness. With passage of time, methods used for household trip data collection have evolved, starting from the conventional face-to-face interviews or paperand-pencil interviews, moving on to mail-back surveys and internet-based surveys, before finally reaching to the recent approach of passive data gathering. Recording travel data automatically will require the use of modern technology present in the form of various sensors, and employing intelligent algorithms to infer the required information from these sensors’ data. These sensors can be integrated into a purpose-built device or more recently can be present in smartphones. The current study provides a comprehensive review of the research done in the field of travel mode detection from data passively collected with the help of various devices. The review starts from Global Positioning System (GPS) loggers and moves to cover purpose-built wearable devices containing additional sensors and finally ending with the most modern approach of incorporating smartphones. The summary tables presented in this study are of great value to the researchers trying to get insight of this research field.

13

Authors: Neelam Mukhtar; Mohammad Abid Khan; Nadia Chiragh; Asim Ullah Jan; Shah Nazir

Although work has been done in Urdu Sentiment Analysis by researchers but still there is a lot of room for improvement in the form of achieving higher accuracy. Therefore, in this research, the accuracy of Urdu Sentiment Analysis in multiple domains is enhanced by dealing negations using Lexicon-based approach, one of the broadly used approaches for performing Sentiment Analysis. Negations in Urdu Sentiment Analysis are particularly focused in this research because of their effective role in Sentiment Analysis. Both local and long distance negations are considered. For achieving this goal, a corpus with 6025 Urdu sentences, from 151 blogs that belong to 14 different genres is taken in which use of negations is carefully observed. Two major steps are taken in this regard. First, to deal with the morphological negations, this type of negations is included in the negative word file of the Urdu Sentiment Lexicon developed for performing Sentiment Analysis of Urdu blogs. Secondly, rule-based approach is used for handling the implicit and explicit negations. Rules are designed that can deal with both implicit and explicit negations effectively. Implementation of these rules increased the accuracy of Sentiment Analyzer from 73.88% to 78.32% with 0.745, 0.788 and 0.745 Precision, Recall and Fmeasure respectively, which is statistically significant improvement.

13

Authors: Rashid Hameed, Usman Akmal; Qasim S. Khan; Muhammad Ahsan Cheema; Muhammad Rizwan Riaz

A large volume of concrete debris is being produced in many countries on the globe due to the demolition of old concrete structures and testing of concrete specimens in laboratories. One of the ways to reuse concrete debris is to produce Recycled Aggregates (RA) and use them in new concrete. In recent years, Recycled Aggregates Concrete (RAC) has experienced increasing demand in various non-structural and structural applications. In reinforced concrete structures, one of the sources of brittle failure is sudden loss of bond between reinforcing bars and concrete in anchorage zones. Therefore, for the structural application of any new kind of concrete such as fiber reinforced RAC, knowledge of bond characteristics of reinforcing bars embedded in concrete becomes essential for determining the overall structural response under different modes of loading. In this regard, this study experimentally investigated the effect of fibers on the bond stress-slip behavior of deformed steel re-bar embedded in RAC. Concrete mixes having 0, 50 and 100% RAs were prepared with and without the addition of fibers. Two types of fibers were investigated in mono form: hooked-ends steel and polypropylene fibers. The dosage of steel and polypropylene fibers was kept 40 and 4.4 kg/m3, respectively. Axial compression and standard pull-out tests were performed. Test specimens for pull-out test were prepared using deformed steel re-bars of 19mm (#6) diameter. The results of strength tests confirmed that the compressive strength of concrete is decreased by replacing Natural Aggregates (NA) with RAs. For bond behavior of steel re-bar, the results of this study showed that replacement of 50% NA with RAs did not affect the bond response of steel bar, however, 100% replacement of NA with RAs showed detrimental effect on bond stress slip behavior. The results further showed that the addition of both types of fibers made it possible to recover the loss in compressive strength, bond strengths and bond toughness occurred because of replacing NA with RAs. In case of RA concrete mixes containing hooked-ends steel fibers, strength values were found even greater than the strength values of Natural Aggregates Concrete (NAC). From the results of this study, it was found that it is possible to design a structural concrete mix using 100% RAs and steel fibers at relatively low dosage of 40kg/m3.

15

Authors: Ayesha Haroon; Irfan Shafqat Javed; Huma Rehmat Baig; Ali Nasir, Arslan Ashraf

Over the past two decades, developing distributed energy sources in electric power grid have created new challenges related to the power quality, voltage adjustment and proficient energy utilization. Power electronic converters are widely used to interface the emerging energy systems (without and with energy storage) and smart buildings with the transmission and distribution systems. Flexible Ac Transmission Systems (FACTS) and Voltage-Source Converters (VSC), with smart dynamic controllers, are emerging as stabilization and power filtering equipment to improve the power quality. FACTS devices are of vital significance for tackling the problem of voltage instability which is inevitable and leads to losses in transmission system networks. These devices provide fast voltage regulation, ensure system stability and reactive power compensation. In this regard, modeling, control and appropriate placement of these devices in the transmission lines have been of great importance for researchers of power transmission systems. By using high speed power electronic converters, FACTS perform many times faster than the conventional compensation techniques. FACTS not only provide fast voltage regulation but also damping of active power oscillations and reactive power compensation. Hence, they increase the availability and reliability of the power systems. But, the functioning of a FACTS device extremely reckons upon its parametric quantity, appropriate placement, and sizing in the power network. In this paper, an extensive literature survey is presented to discuss and investigate these parameters of FACTS devices.

19

Authors: Naveed Khan Baloch; Ayaz Hussain; Muhammad Iram Baig

The decreasing size of the transistor has increased the vulnerability towards faults. Increasing number of cores on a single chip has made the concept of Network on Chip (NoC) a standard communication backbone among cores. This facility comes with vulnerability of faults in the system due to decreasing size of transistors. A permanent fault in the network leads to undesirable consequence such as permanent blocking of flits or failure of the whole router. Preserving the router in the operational state has a significant impact on the reliability of the system. Permanent fault in buffers and pipeline stages of the router has a high impact on performance. The proposed router architecture Protector provides faults protection to both buffers and pipelines stages by exploiting the concepts of borrowing from other resources, using bypass paths and by creating multiple paths to reach output. The proposed router incurred an area overhead of 30% as compared to the baseline design. Reliability analysis using Silicon Protection Factor indicates that the proposed router has better fault tolerance efficiency as compared to state of the art. Latency analysis using PARSEC and SPLASH-2 benchmarks indicates proposed router incurs 13% and 16% latency overhead in the presence of faults.