Mehran University Research Journal of Engineering and Technology

6

Authors: Chandio A.D., Abro S.H.

The βNiAl coating was deposited onto Nickel based CMSX-4 superalloy by in-situ CVD (Chemical Vapor Deposition) method. Main focus of this contribution was to study the influence of aluminizing time and temperature on the microstructure and thickness of the coating; this was followed by examination by XRD (X-Ray Diffraction), electron microscope. Results suggest that an incremental variation in temperature alters the coating activities from HA (High Activity) to LA (Low Activity). This is exhibited by the resultant CT (Coating Thickness) since HA coatings are thicker than LA counterparts. The microstructure of the coating formed at low temperature (or HA ones) showed a large amount of α-Cr precipitates while one formed at high temperature (or LA ones) exhibited lower amounts of such precipitates. Moreover, incremental aluminizing time showed linear trend of CT at initial stage, thereafter (10 hrs) it leveled off. Whereas it does not affect microstructure of the coating

10

Authors: Demircan S., Kahramanli H.

ER (Emotion Recognition) from speech signals has been among the attractive subjects lately. As known feature extraction and feature selection are most important process steps in ER from speech signals. The aim of present study is to select the most relevant spectral feature subset. The proposed method is based on feature selection with optimization algorithm among the features obtained from speech signals. Firstly, MFCC (Mel-Frequency Cepstrum Coefficients) were extracted from the EmoDB. Several statistical values as maximum, minimum, mean, standard deviation, skewness, kurtosis and median were obtained from MFCC. The next process of study was feature selection which was performed in two stages: In the first stage ABM (Agent-Based Modelling) that is hardly applied to this area was applied to actual features. In the second stageOpt-aiNET optimization algorithm was applied in order to choose the agent group giving the best classification success. The last process of the study is classification. ANN (Artificial Neural Network) and 10 cross-validations were used for classification and evaluation. A narrow comprehension with three emotions was performed in the application. As a result, it was seen that the classification accuracy was rising after applying proposed method. The method was shown promising performance with spectral features.

10

Authors: Masood N., Jabeen G.

Schema merging is a process of integrating multiple data sources into a GCS (Global Conceptual Schema). It is pivotal to various application domains, like data ware housing and multi-databases. Schema merging requires the identification of corresponding elements, which is done through schema matching process. In this process, corresponding elements across multiple data sources are identified after the comparison of these data sources with each other. In this way, for a given set of data sources and the correspondence between them, different possibilities for creating GCS can be achieved. In applications like multi-databases and data warehousing, new data sources keep joining in and GCS relations are usually expanded horizontally or vertically. Schema merging approaches usually expand GCS relations horizontally or vertically as new data sources join in. As a result of such expansions, an unbalanced GCS is created which either produces too much NULL values in response to global queries or a result of too many Joins causes poor query processing. In this paper, a novel approach, TuSMe (Tuned Schema Merging) technique is introduced to overcome the above mentioned issue via developing a balanced GCS, which will be able to control both vertical and horizontal expansion of GCS relations. The approach employs a weighting mechanism in which the weights are assigned to individual attributes of GCS. These weights reflect the connectedness of GCS attributes in accordance with the attributes of the principle data sources. Moreover, the overall strength of the GCS could be scrutinized by combining these weights. A prototype implementation of TuSMe shows significant improvement against other contemporary state-of-the-art approaches.

10

Authors: Muhammad G., Marri A.,Shar A.M.

Thermal conductivity displays a key role in design of engineering structures where, thermal stresses resulting from heat and temperatures are of concern. Significant efforts were made to measure the thermal conductivity of different materials. For thermal conductivity characterization of soil samples it is essential to have very flexible set-up. Hence, this paper provides details about indigenously developed experimental setup for thermal conductivity measurement. The design of this newly developed setup is based on the basic principle of steady state heat flow. This experimental setup is designed in order to measure the thermal conductivity of various materials such as soils, rocks, concrete and any type of unbonded and bonded materials. In this paper, initially the theoretical background of the measurement techniques and the principle of heat flow are described, followed by design description and working procedure. The design has been kept very simple, adjustable for varying type and size of specimens and easy to operate with excellent level of accuracy as evident from system calibration. The accuracy and precision of the newly developed setup was verified by testing reference materials of known thermal conductivity and in the test results a high correlation coefficient (R^2 = 0.999) between experimental data and fitting curve was achieved.

12

Authors: Khoso S.A., Abro M.I., Agheem M.H.

Liberation size plays a significant role to select a correct and successful concentration method for natural iron ores. This paper aims to evaluate the liberation size of two newly discovered iron ores, namely Zard Koh and Kulli Koh, existing in Chagai region of Pakistan. Zard Koh iron ore is mainly composed of maghemite along with the pyrite, chlorite, grossular and admontite as gangue minerals, whereas, Kulli Koh iron ore is comprised of hematite mostly with quartz, dravite and kaolinite as the gangue minerals. The representative samples of ores were pulverized and sieved to different size fractions. The liberation size of iron bearing minerals and gangues was investigated by analyzing the different size fractions of each ore using XRF (X-Ray Fluorescence), SEM (Scanning Electron Microscope) attached with EDS (Energy Dispersive Spectroscope). The XRF results revealed that the most probable liberation size of Zard Koh and Kulli Koh ores is most likely existing at -75+45 and -150+106 m, respectively. In order to confirm this liberation size, further evidences were collected using SEM and EDS examinations. It is interesting to note that the results obtained from SEM and EDS were quite in agreement with XRF results.

14

Authors: Iqbal A., Touqir I., Ashfaque A., Khan N., Ashraf F.

WT (Wavelet Transform) is considered as landmark for image compression because it represents a signal in terms of functions which are localized both in frequency and time domain. Wavelet sub-band coding exploits the self-similarity of pixels in images and arranges resulting coefficients in different sub-bands. A much simpler and fully embedded codec algorithm SPIHT (Set Partitioning in Hierarchical Trees) is widely used for the compression of wavelet transformed images. It encodes the transformed coefficients depending upon their significance comparative to the given threshold. Statistical analysis reveals that the output bit-stream of SPIHT comprises of long trail of zeroes that can be further compressed, therefore SPIHT is not advocated to be used as sole mean of compression. In this paper, wavelet transformed images have been initially compressed by using SPIHT technique and to attain more compression, the output bit streams of SPIHT are then fed to entropy encoders; Huffman and Arithmetic encoders, for further de-correlation. The comparison of two concatenations has been carried out by evaluating few factors like Bit Saving Capability, PSNR (Peak Signal to Noise Ratio), Compression Ratio and Elapsed Time. The experimental results of these cascading demonstrate that SPIHT combined with Arithmetic coding yields better compression ratio as compared to SPIHT cascaded with Huffman coding. Whereas, SPIHT once combined with Huffman coding is proved to be comparatively efficient.

14

Authors: Noor S., Vali Uddin

Identifying activities of daily living is an important area of research with applications in smart-homes and healthcare for elderly people. It is challenging due to reasons like human self-occlusion, complex natural environment and the human behavior when performing a complicated task. From psychological studies, we know that human gaze is closely linked with the thought process and we tend to “look” at the objects before acting on them. Hence, we have used the object information present in gaze images as the context and formed the basis for activity prediction. Our system is based on HMM (Hidden Markov Models) and trained using ANN (Artificial Neural Network). We begin with extracting motion information from TPV (Third Person Vision) streams and object information from FPV (First Person Vision) cameras. The advantage of having FPV is that the object information forms the context of the scene. When context is included as input to the HMM for activity recognition, the precision increases. For testing, we used two standard datasets from TUM (Technische Universitaet Muenchen) and GTEA Gaze+ (Georgia Tech Egocentric Activities). In the first round, we trained our ANNs only with activity information and in the second round added the object information as well. We saw a significant increase in the precision (and accuracy) of predicted activities from 55.21% (respectively 85.25%) to 77.61% (respectively 93.5%). This confirmed our initial hypothesis that including the focus of attention of the actor in the form of object seen in FPV can help in predicting activities better.

14

Authors: Siyal A.A., Lakhair I., Babar M.M., Siyal P., Solangi G.S

The effluent water brought by RBOD (Right Bank Outfall Drain) is not only threat to the aquatic life of Manchar Lake but also the fertile agricultural lands which are being cultivated by use of lake water through Danastar Wah are at risk of salinization. The farming community of the area is scary of continual use of irrigation waters received through the Danastar Wah; they are of the view that the constant use of this water will ruin their fertile lands into salt-affected soils. Thus, keeping in view the fears of the farmers of the command area of Danastar Wah, a study was carried out to investigate the water quality of the Manchar Lake, RBOD MNV (Main Nara Valley) drain and Danastar Wah, and to examine soil salinity status of the area using Geo-referenced field and satellite imagery data for Kharif season of the year 2015. The results of the study showed that the EC (Electrical Conductivity) of the Danastar Wah water was below 1.2 dS/m. Thus, the water was suitable for irrigation purpose. In all the water samples, Na+, Ca2+ + Mg2+ and CO3 concentrations were found within the permissible limits, while no concentration of HCO3 was found in any of the water samples. In the command area, clay texture was dominant down to a depth of 60 cm soil profile. In the area about 37, 28, and 30% of the soils were normal (non-saline), saline and sodic, respectively; while only 5% of soils were saline-sodic. The cotton crop was identified as the major Kharif crop, occupying about 13.76% (2,844 ha) of the total command area, followed by rice crop grown on about 5.21% (1,078 ha) of the command area. The overall accuracy of image classification was 90% with a kappa coefficient of 0.86. Based on this study, it can be concluded that the water of the Danastar Wah can be used for irrigation purpose during Kharif season only with the condition that adequate land drainage is maintained. It is also suggested that before using the water of Manchar Lake, RBOD and Danastar Wah for Rabi season, analysis for water quality be conducted. GeoInformatics (GIS and RS) tools can be employed for spatial and temporal monitoring of water quality of the Manchar Lake.

16

Authors: Gul Z., Hafeez Y., Hashmi A.S, Ali S., Iqbal N.

Collaborative effort is required in DSD (Distributed Software Development) in order to develop software in manageable components. Immense effort is taking place due to the cultural, geographical and temporal distances among project teams in Pakistani Software Industry to this end. The purpose of this study is to propose a solution during DSD that will help the distributed teams in coordinating their activities. Our solution enhances the management associated activities and assists in optimal usage of team coordination in dispersed settings. The method that we used is single case study type, which involved distributed software business to assess the usefulness and efficiency related to Pakistan’s DSD industries, and has shown strong tendency of participants towards the effectiveness of proposed team coordination framework. Results indicate that the predictable solution will look up the group management, which is considered as a vigorous issue of Pakistani DSD industry. Furthermore, it will assist in resolving the problems of team coordination in distributed situation. One of the most significant current discussion about the proposed solution suggested that it helps in human communication methods team coordination in a distributed environment.

18

Authors: Jabbar M., Javaid Q., Arif M., Munir A., Ali J.,

Recommender Systems are valuable tools to deal with the problem of overloaded information faced by most of the users in case of making purchase decision to buy any item. Recommender systems are used to provide recommendations in many domains such as movies, books, digital equipment’s, etc. The massive collection of available books online presents a great challenge for users to select the relevant books that meet their preferences. Users usually read few pages or contents to decide whether to buy a certain book or not. Recommender systems provide different value addition factors such as similar user ratings, users past history, user profiles, etc. to facilitate the users in terms of providing relevant recommendations according to their preferences. Recommender systems are broadly categorized into content based approach and collaborative filtering approach. Content based or collaborative filtering approaches alone are not sufficient to provide most accurate and relevant recommendations under diverse scenarios. Therefore, hybrid approaches are also designed by combining the features of both the content based and collaborative filtering approaches to provide more relevant recommendations. This paper proposes an efficient hybrid recommendation scheme for mobile platform that includes the traits of content based and collaborative filtering approaches in addition of the context based approach that is included to provide the latest books recommendations to user.Objective and subjective evaluation measures are used to compute the performance of the proposed system. Experimental results are promising and signify the effectiveness of our proposed hybrid scheme in terms of most relevant and latest books recommendations.