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Authors: Essam A. Al-Bahkali, Mahir H. Es-saheb, Jonny Herwan

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In this study the elastic-plastic stress distribution in weld-bonded joint, fabricated from austenitic stainless steel (AISI 304) sheet of 1.00 mm thickness and Epoxy adhesive Araldite 2011, subjected to axial loading is investigated. This is needed to improve design procedures and welding codes, and saving efforts in the cumbersome experiments and analysis. Therefore, a complete 3-D finite element modelling and analysis of spot welded, bonded and weld-bonded joints under axial loading conditions is carried out. A comprehensive systematic experimental program is conducted to determine many properties and quantities, of the base metals and the adhesive, needed for FE modelling, such like the elastic – plastic properties, modulus of elasticity, fracture limit, the nugget and heat affected zones (HAZ) properties, etc. Consequently, the finite element models developed, for each case, are used to evaluate stresses distributions across the entire joint, in both the elastic and plastic regions. The stress distribution curves are obtained, particularly in the elastic regions and found to be consistent and in excellent agreement with the published data. Furthermore, the stresses distributions are obtained in the weld-bonded joint and display the best results with almost uniform smooth distribution compared to spot and bonded cases. The stress concentration peaks at the edges of the weld-bonded region, are almost eliminated resulting in achieving the strongest joint of all processes.

Keywords: Spot Welded, Weld-Bonded, Load-Displacement curve, Stress distribution

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Authors: Karanja Kibicho, Anthony Sayers

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Due to adverse pressure gradient along the diverging walls of wide-angled diffusers, the attached flow separates from one wall and remains attached permanently to the other wall in a process called stalling. Stalled diffusers render the whole fluid flow system, in which they are part of, very inefficient. There is then an engineering need to try to understand the whole process of diffuser stall if any meaningful attempts to improve on diffuser efficiency are to be made. In this regard, this paper provides a data bank contribution for the mean flow-field in wide-angled diffusers where the complete velocity and static pressure fields, and pressure recovery data for diffusers in the fully stalled flow regime are experimentally measured. The measurements were carried out at Reynolds numbers between 1.07×105 and 2.14×105 based on inlet hydraulic diameter and centreline velocity for diffusers whose divergence angles were between 30Ôùª and 50Ôùª. Variation of Reynolds number did not significantly affect the velocity and static pressure profiles. The wall static pressure recovery was found to be more sensitive to changes in the Reynolds number. By increasing the velocity from 10 m/s to 20 m/s, the wall static pressure recovery increased by 8.31%. However, as the divergence angle was increased, a similar increase in the Reynolds number resulted in a higher percentage increase in pressure recovery. Experimental results showed that regardless of the wall to which the flow was attached, both the velocity and pressure fields were replicated with discrepancies below 2%.

Keywords: Two-dimensional, wide-angled, diffuser, stall, separated flows, subsonic flows, diffuser flow regimes

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Authors: Junya Takenami, Md. Azhar Uddin, Eiji Sasaoka, Yasushi Shioya, Tsuneyoshi Takase

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In this study, we sought to investigate the mercury removal efficiency of manganese oxides from natural gas. The fundamental studies on mercury removal with manganese oxides sorbents were carried out in a laboratory scale fixed bed reactor at 30 °C with a mixture of methane (20%) and nitrogen gas laden with 4.8 ppb of elemental mercury. Manganese oxides with varying surface area and crystalline phase were prepared by conventional precipitation method in this study. The effects of surface area, crystallinity and other metal oxides on mercury removal efficiency were investigated. Effect of Ag impregnation on mercury removal efficiency was also investigated. Ag supported on metal oxide such titania and zirconia as reference materials were also used in this study for comparison. The characteristics of mercury removal reaction with manganese oxide was investigated using a temperature programmed desorption (TPD) technique. Manganese oxides showed very high Hg removal activity (about 73-93% Hg removal) for first time use. Surface area of the manganese oxide samples decreased after heat-treatment and resulted in complete loss of Hg removal ability for repeated use after Hg desorption in the case of amorphous MnO2, and 75% loss of the initial Hg removal activity for the crystalline MnO2. Mercury desorption efficiency of crystalline MnO2 was very low (37%) for first time use and high (98%) after second time use. Residual potassium content in MnO2 may have some effect on the thermal stability of the adsorbed Hg species. Desorption of Hg from manganese oxides occurs at much higher temperatures (with a peak at 400 °C) than Ag/TiO2 or Ag/ZrO2. Mercury may be captured on manganese oxides in the form of mercury manganese oxide.

Keywords: Mercury removal, Metal and metal oxide sorbents, Methane, Natural gas.

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Authors: Achela K. Fernando, Xiujuan Zhang, Peter F. Kinley

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A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Keywords: Artificial Neural Networks, Back-propagationlearning, Combined sewer overflows, Forecasting.

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Authors: A. Abbas Khalaf, L. Issazadeh, Z. Arif Abdullah, J. Hassanpour

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In order to evaluate the growth and yield properties of two Sorghum-Sudangrass hybrids under different irrigation levels, an investigation was done in the experiment site of Collage of Agriculture, University of Duhok, Kurdistan region of Iraq (36°5´38^⸗ N, 42°52´02^⸗ E) in the years 2015-16. The experiment was conducted under Randomized Complete Block Design (RCBD) with three replications, which main factor was irrigation treatments (I₁₀₀, I₇₅ and I₅₀) according to evaporation pan class A and type of Sorghum-Sudangrass hybrids (KH12SU9001, G₁) and (KH12SU9002, G₂) were factors of subplots. The parameters studied were: plant height (cm), number of green leaves per plant; leaf area (m²/m²), stem thickness (mm), percent of protein, fresh and dry biomass (ton.ha^-1) and also crop water productivity. The results of variance analysis showed that KH12SU9001 variety had more amount of leaf area, percent of protein, fresh and dry biomass yield in comparison to KH12SU9002 variety. By comparing effects of irrigation levels on vegetative growth and yield properties, results showed that amount of plant height, fresh and dry biomass weight was decreased by decreasing irrigation level from full irrigation regime to 5 _o% of irrigation level. Also, results of crop water productivity (CWP) indicated that improvement in quantity of irrigation would impact fresh and dry biomass yield significantly. Full irrigation regime was recorded the highest level of CWP (1.28-1.29 kg.m^-3).

Keywords: Deficit irrigation, growth, Sorghum-Sudangrass hybrid, yield.

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Authors: M. Veerasham

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The refractory high entropy alloys are potential materials for high-temperature applications because of their ability to retain high strength up to 1600°C. However, their practical applications were limited due to poor elongation at room temperature. Therefore, decreasing the average valence electron concentrations (VEC) is an effective design strategy to improve the intrinsic ductility of refractory high entropy alloys. In this work, the high-entropy alloy TaNbHfZrTi was processed at room temperature by each step reverse rolling up to a 90% reduction in thickness. Subsequently, the reverse rolled 90% samples were utilized for annealing treatment at 800°C and 1000°C for 1 h to understand phase stability, microstructure, texture, and mechanical properties. The reverse rolled 90% condition contains body-centered cubic (BCC) single-phase; upon annealing at 800 °C, the formation of secondary phase BCC-2 prevailed. The partial recrystallization and complete recrystallization microstructures were developed for annealed at 800°C and 1000°C, respectively. The reverse rolled condition and 1000°C annealed temperature exhibit extraordinary room temperature tensile properties with high ultimate tensile strength (UTS) without compromising loss of ductility called “strength-ductility” trade-off. The reverse-rolled 90% and annealing treatment carried out at temperature about 1000°C for 1 h consist of UTS 1430 MPa and 1556 MPa with an appreciable amount of 21% and 20% elongation, respectively. The development of hierarchical microstructure prevailed for the annealed 1000°C which led to the simultaneous increase in tensile strength and elongation.

Keywords: refractory high entropy alloys, reverse rolling, recrystallization, microstructure, tensile properties

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Authors: Rupali, Anil Kumar Jaiswal

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Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: Physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model.

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Authors: Wern Lin Yeo, Choo Kim Tan, Sook Ling Lew

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The purpose of this study is to determine the relationship of anxiety level between male and female undergraduates at a private university in Malaysia. Convenient sampling method used in this study in which the students were selected based on the grouping assigned by the faculty. There were 214 undergraduates who registered the probability courses had participated in this study. Mathematics Anxiety Rating Scale (MARS) was the instrument used in study which used to determine students’ anxiety level towards probability. Reliability and validity of instrument was done before the major study was conducted. In the major study, students were given briefing about the study conducted. Participation of this study was voluntary. Students were given consent form to determine whether they agree to participate in the study. Duration of two weeks was given for students to complete the given online questionnaire. The data collected will be analyzed using Statistical Package for the Social Sciences (SPSS) to determine the level of anxiety. There were three anxiety level, i.e., low, average and high. Students’ anxiety level was determined based on their scores obtained compared with the mean and standard deviation. If the scores obtained were below mean and standard deviation, the anxiety level was low. If the scores were at below and above the mean and between one standard deviation, the anxiety level was average. If the scores were above the mean and greater than one standard deviation, the anxiety level was high. Results showed that both of genders were having average anxiety level. Among low, average and high anxiety level, frequency of males were found to be higher as compared to females. Hence, the mean values obtained for males (M = 3.62) was higher than females (M = 3.42). In order to be significant of anxiety level among the gender, the p-value should be less than .05. The p-value obtained in this study was .117. However, this value was greater than .05. Thus, there was no significant difference of anxiety level among the gender. In other words, there was no relationship of anxiety level with the gender.

Keywords: Anxiety level, gender, mathematics anxiety, probability and statistics.

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Authors: Sumathi Poobal, G. Ravindran

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Medical imaging uses the advantage of digital technology in imaging and teleradiology. In teleradiology systems large amount of data is acquired, stored and transmitted. A major technology that may help to solve the problems associated with the massive data storage and data transfer capacity is data compression and decompression. There are many methods of image compression available. They are classified as lossless and lossy compression methods. In lossy compression method the decompressed image contains some distortion. Fractal image compression (FIC) is a lossy compression method. In fractal image compression an image is coded as a set of contractive transformations in a complete metric space. The set of contractive transformations is guaranteed to produce an approximation to the original image. In this paper FIC is achieved by PIFS using quadtree partitioning. PIFS is applied on different images like , Ultrasound, CT Scan, Angiogram, X-ray, Mammograms. In each modality approximately twenty images are considered and the average values of compression ratio and PSNR values are arrived. In this method of fractal encoding, the parameter, tolerance factor Tmax, is varied from 1 to 10, keeping the other standard parameters constant. For all modalities of images the compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the decompressed image is arrived by PSNR values. From the results it is observed that the compression ratio increases with the tolerance factor and mammogram has the highest compression ratio. The quality of the image is not degraded upto an optimum value of tolerance factor, Tmax, equal to 8, because of the properties of fractal compression.

Keywords: Fractal image compression, IFS, PIFS, PSNR, Quadtree partitioning.

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: Time history dynamic analysis, basic modal displacement, earthquake induced demands, shear steel structures.

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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The widespread popularity of mobile devices and the development of artificial intelligence (AI) have led to the widespread adoption of deep learning (DL) in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace, a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Additionally, we propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. Using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We conduct an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace outperformed FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: Mobile computing, deep learning apps, sensitive information, static analysis.

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Authors: Bernat-Carles Serdà Ferrer, Arantza Del Valle Gómez

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The Quality of Life (QoL) paradigm is multidimensional, dynamic and modular and its definition differs across the cancer continuum. The challenge in the interpretation of QoL data in clinical research is that QoL is influenced by psychological phenomena such as adaptation to illness. This research aims to obtain a valid and sensitive assessment of QoL change over the continuum disease, and to evaluate a rehabilitation programme aimed at inverting the observed decrease in QoL when patients return to daily living activities. The sample comprised 66 men. Patients were first assessed to establish a baseline (P1-diagnosis). This was followed by a post-test (P2-discharge) and a then-test measurement (P3-retrospective evaluation) and after returning home patients were randomized in experimental and control groups. The experimental group attended a rehabilitation programme over 24 weeks (P4). Results show that from baseline to post-test, QoL decreased significantly. The recalibration then-test confirmed a low QoL in all periods evaluated. Significant differences between the experimental and control groups prove the positive effect of the Exercise Rehabilitation Programme (ERP) on QoL. Understanding the real dynamic of QoL over time would help to adapt rehabilitation programmes by improving sensitivity and efficacy and provide professionals with a more accurate perception of the impact of treatment and side effects on patients’ QoL. Our results underline the importance of changing the approach adopted by health professionals towards one of watchful waiting on patients’ QoL until their complete recovery in daily life.

Keywords: Prostate cancer, quality of life, rehabilitation programme, response shift.

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Authors: Shih-Wen Hsiao, Rong-Qi Chen

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In the field of fashion design, 3D Mannequin is a kind of assisting tool which could rapidly realize the design concepts. While the concept of 3D Mannequin is applied to the computer added fashion design, it will connect with the development and the application of design platform and system. Thus, the situation mentioned above revealed a truth that it is very critical to develop a module of 3D Mannequin which would correspond with the necessity of fashion design. This research proposes a concrete plan that developing and constructing a system of 3D Mannequin with Kinect. In the content, ergonomic measurements of objective human features could be attained real-time through the implement with depth camera of Kinect, and then the mesh morphing can be implemented through transformed the locations of the control-points on the model by inputting those ergonomic data to get an exclusive 3D mannequin model. In the proposed methodology, after the scanned points from the Kinect are revised for accuracy and smoothening, a complete human feature would be reconstructed by the ICP algorithm with the method of image processing. Also, the objective human feature could be recognized to analyze and get real measurements. Furthermore, the data of ergonomic measurements could be applied to shape morphing for the division of 3D Mannequin reconstructed by feature curves. Due to a standardized and customer-oriented 3D Mannequin would be generated by the implement of subdivision, the research could be applied to the fashion design or the presentation and display of 3D virtual clothes. In order to examine the practicality of research structure, a system of 3D Mannequin would be constructed with JAVA program in this study. Through the revision of experiments the practicability-contained research result would come out.

Keywords: 3D Mannequin, kinect scanner, interactive closest point, shape morphing, subdivision.

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Authors: N.H. Abdurahman, Y. M. Rosli, N. H. Azhari, S. F. Tam

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The direct discharge of palm oil mill effluent (POME) wastewater causes serious environmental pollution due to its high chemical oxygen demand (COD) and biochemical oxygen demand (BOD). Traditional ways for POME treatment have both economical and environmental disadvantages. In this study, a membrane anaerobic system (MAS) was used as an alternative, cost effective method for treating POME. Six steady states were attained as a part of a kinetic study that considered concentration ranges of 8,220 to 15,400 mg/l for mixed liquor suspended solids (MLSS) and 6,329 to 13,244 mg/l for mixed liquor volatile suspended solids (MLVSS). Kinetic equations from Monod, Contois and Chen & Hashimoto were employed to describe the kinetics of POME treatment at organic loading rates ranging from 2 to 13 kg COD/m3/d. throughout the experiment, the removal efficiency of COD was from 94.8 to 96.5% with hydraulic retention time, HRT from 400.6 to 5.7 days. The growth yield coefficient, Y was found to be 0.62gVSS/g COD the specific microorganism decay rate was 0.21 d-1 and the methane gas yield production rate was between 0.25 l/g COD/d and 0.58 l/g COD/d. Steady state influent COD concentrations increased from 18,302 mg/l in the first steady state to 43,500 mg/l in the sixth steady state. The minimum solids retention time, which was obtained from the three kinetic models ranged from 5 to 12.3 days. The k values were in the range of 0.35 – 0.519 g COD/ g VSS • d and values were between 0.26 and 0.379 d-1. The solids retention time (SRT) decreased from 800 days to 11.6 days. The complete treatment reduced the COD content to 2279 mg/l equivalent to a reduction of 94.8% reduction from the original.

Keywords: COD reduction, POME, kinetics, membrane, anaerobic, monod, contois equation.

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Authors: Mohammed Sani Abdulai

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Government budgets are the primary instruments for formulating and implementing a country’s fiscal policy objectives, development priorities, and the overall socio-economic aspirations of its people. Thus, in this paper, the author examined the Government of Ghana’s budgets with respect to their functions, coverage, classifications, and integration with the country’s chart of accounts. The author did so by amalgamating the research findings of extant literature with (a) the operational and procedural guidelines underpinning the formulation and execution of the government’s budgets; (b) the recommendations made by various development partners and thinktanks on reforming the country’s budgeting processes and procedures; and (c) the lessons Ghana could learn from the budget reform efforts of other countries. By way of research findings, the paper showed that the Government of Ghana’s budgets in terms of function are both eclectic and multidimensional. On coverage, the paper showed that the country’s budgets duly cover the revenues and expenditures of the general government (i.e., both the central and sub-national governments). Finally, on classifications, the paper noted with delight the Government of Ghana’s effort in providing classificatory codes to both its national development agenda and such international development goals as the AU’s Agenda 2063 and the UN’s Sustainable Development Goals. However, the paper found some significant lapses that require a complete overhaul and structuring on the integrations of its budget classifications with its chart of accounts. Thus, the paper concluded with a detailed examination of the challenges confronting the country’s current chart of accounts and recommendations for addressing them.

Keywords: Budget, budgetary transactions, budgetary governance, Chart of Accounts, classification, composition, coverage, Public Financial Management.

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Authors: Nurul Bahiyah Ahmad Khairudin, Habibah A Wahab

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A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.

Keywords: 3D model, Chicken villin headpiece subdomain, Molecular dynamic simulation NMR-MDavg, RMSD.

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Authors: Chen Chou, Feng-Tyan Lin

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Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.

Keywords: Big Data, ITS, influence range, living area, central place theory, visualization.

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Authors: Ashly Joseph, Jithu Paulose

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In an era where misleading information may quickly circulate on digital news channels, it is crucial to have efficient and trustworthy methods to detect and reduce the impact of misinformation. This research proposes an innovative framework that combines Natural Language Processing (NLP), Reinforcement Learning (RL), and Blockchain technologies to precisely detect and minimize the spread of false information in news articles on social media. The framework starts by gathering a variety of news items from different social media sites and performing preprocessing on the data to ensure its quality and uniformity. NLP methods are utilized to extract complete linguistic and semantic characteristics, effectively capturing the subtleties and contextual aspects of the language used. These features are utilized as input for a RL model. This model acquires the most effective tactics for detecting and mitigating the impact of false material by modeling the intricate dynamics of user engagements and incentives on social media platforms. The integration of blockchain technology establishes a decentralized and transparent method for storing and verifying the accuracy of information. The Blockchain component guarantees the unchangeability and safety of verified news records, while encouraging user engagement for detecting and fighting false information through an incentive system based on tokens. The suggested framework seeks to provide a thorough and resilient solution to the problems presented by misinformation in social media articles.

Keywords: Natural Language Processing, Reinforcement Learning, Blockchain, fake news mitigation, misinformation detection.

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Authors: Yu-Cheng Chou, Po Ting Lin

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The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.

Keywords: Multiple Commodities, Multi-State Flow Network (MSFN), Time Constraints, Worst-Case Reliability (WCR)

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Authors: Meysam Jamali, Ebrahim Moghimi, Zean Alabden Jafarpour

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Karst term is the determiner of a variety of areas or landforms and unique perspectives that have been formed in result of the of the ingredients dissolution of rocks constituter by natural waters. Shiraz area with an area of 5322km2 is located in the simple folded belt in the southern part of Zagros Mountain of Fars, and is surrounded with Limestone Mountains (Asmari formation). Shiraz area is located in Calcareous areas. The infrastructure of this city is lime and absorbing wells that the city can influence the Limestone dissolution and those accelerate its rate and increase the cavitation below the surface. Dasht-e Arjan is a graben, which has been created as the result of activity of two normal faults in its east and west sides. It is a complete sample of Karst plains (Polje) which has been created with the help of tectonic forces (fault) and dissolution process of water in Asmari limestone formation. It is located 60km. off south west of Shiraz (on Kazeroon-Shiraz road). In 1971, UNESCO has recognized this plain as a reserve of biosphere. It is considered as one of the world’s most beautiful geological phenomena, so that most of the world’s geologists are interested in visiting this place. The purpose of this paper is to identify and introduce landscapes of Karst features shiraz city and Dasht-e Arjan including Karst dissolution features (Lapiez, Karst springs, dolines, caves, underground caves, ponors, and Karst valleys), anticlines and synclines, and Arjan Lake.

Keywords: Dasht-eArjan, Fault, Karst features, Shiraz City, Zagros.

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Authors: Keiko Shimazu, Yasuhiro Maida, Tetsuya Sugata, Daisuke Tamakoshi, Kenji Makabe, Haruki Suzuki

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In this paper, we report how to acquire serious victims’ locations in the Acute Stage of Large-scale Disasters, in an Emergency Information Network System designed by us. The background of our concept is based on the Great East Japan Earthquake occurred on March 11^th, 2011. Through many experiences of national crises caused by earthquakes and tsunamis, we have established advanced communication systems and advanced disaster medical response systems. However, Japan was devastated by huge tsunamis swept a vast area of Tohoku causing a complete breakdown of all the infrastructures including telecommunications. Therefore, we noticed that we need interdisciplinary collaboration between science of disaster medicine, regional administrative sociology, satellite communication technology and systems engineering experts. Communication of emergency information was limited causing a serious delay in the initial rescue and medical operation. For the emergency rescue and medical operations, the most important thing is to identify the number of casualties, their locations and status and to dispatch doctors and rescue workers from multiple organizations. In the case of the Tohoku earthquake, the dispatching mechanism and/or decision support system did not exist to allocate the appropriate number of doctors and locate disaster victims. Even though the doctors and rescue workers from multiple government organizations have their own dedicated communication system, the systems are not interoperable.

Keywords: Crisis management, disaster mitigation, messing, MGRS, Satellite communication system.

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Authors: G. V. Byrd, B. B. Ghaley, E. Hayashi

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In urban farming, research and innovation are taking place at an unprecedented pace, and soilless growing technologies are emerging at different rates motivated by different objectives in various parts of the world. Local food production is ultimately a main objective everywhere, but adoption rates and expressions vary with socio-economic drivers. Herein, the status of hydroponics and aquaponics is summarized for four countries with diverse socio-economic settings: Europe (Denmark), Asia (Japan and Nepal) and North America (US). In Denmark, with a strong environmental ethic, soilless growing is increasing in urban agriculture because it is considered environmentally friendly. In Japan, soil-based farming is being replaced with commercial plant factories using advanced technology such as complete environmental control and computer monitoring. In Nepal, where rapid loss of agricultural land is occurring near cities, dozens of hydroponics and aquaponics systems have been built in the past decade, particularly in “non-traditional” sites such as roof tops to supplement family food. In the US, where there is also strong interest in locally grown fresh food, backyard and commercial systems have proliferated. Nevertheless, soilless growing is still in the research and development and early adopter stages, and the broad contribution of hydroponics and aquaponics to food security is yet to be fully determined. Nevertheless, current adoption of these technologies in diverse environments in different socio-economic settings highlights the potential contribution to food security with social and environmental benefits which contribute to several Sustainable Development Goals.

Keywords: Aquaponics, hydroponics, soilless agriculture, urban agriculture.

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Authors: B. Chouhan, A. Denesyuk, J. Heino, M. S. Johnson, K. Denessiouk

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Integrins are a large family of multidomain α/β cell signaling receptors. Some integrins contain an additional inserted I domain, whose earliest expression appears to be with the chordates, since they are observed in the urochordates Ciona intestinalis (vase tunicate) and Halocynthia roretzi (sea pineapple), but not in integrins of earlier diverging species. The domain-s presence is viewed as a hallmark of integrins of higher metazoans, however in vertebrates, there are clearly three structurally-different classes: integrins without I domains, and two groups of integrins with I domains but separable by the presence or absence of an additional αC helix. For example, the αI domains in collagen-binding integrins from Osteichthyes (bony fish) and all higher vertebrates contain the specific αC helix, whereas the αI domains in non-collagen binding integrins from vertebrates and the αI domains from earlier diverging urochordate integrins, i.e. tunicates, do not. Unfortunately, within the early chordates, there is an evolutionary gap due to extinctions between the tunicates and cartilaginous fish. This, coupled with a knowledge gap due to the lack of complete genomic data from surviving species, means that the origin of collagen-binding αC-containing αI domains remains unknown. Here, we analyzed two available genomes from Callorhinchus milii (ghost shark/elephant shark; Chondrichthyes – cartilaginous fish) and Petromyzon marinus (sea lamprey; Agnathostomata), and several available Expression Sequence Tags from two Chondrichthyes species: Raja erinacea (little skate) and Squalus acanthias (dogfish shark); and Eptatretus burgeri (inshore hagfish; Agnathostomata), which evolutionary reside between the urochordates and osteichthyes. In P. marinus, we observed several fragments coding for the αC-containing αI domain, allowing us to shed more light on the evolution of the collagen-binding integrins.

Keywords: Integrin αI domain, integrin evolution, collagen binding, structure, αC helix

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Authors: A. Soria-Verdugo, A. Morato-Godino, L. M. García-Gutiérrez, N. García-Hernando

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The evolution of the pyrolysis of sewage sludge in a fixed and a fluidized bed was analyzed using a novel measuring technique. This original measuring technique consists of installing the whole reactor over a precision scale, capable of measuring the mass of the complete reactor with enough precision to detect the mass released by the sewage sludge sample during its pyrolysis. The inert conditions required for the pyrolysis process were obtained supplying the bed with a nitrogen flowrate, and the bed temperature was adjusted to either 500 ºC or 600 ºC using a group of three electric resistors. The sewage sludge sample was supplied through the top of the bed in a batch of 10 g. The measurement of the mass released by the sewage sludge sample was employed to determine the evolution of the reaction rate during the pyrolysis, the total amount of volatile matter released, and the pyrolysis time. The pyrolysis tests of sewage sludge in the fluidized bed were conducted using two different bed materials of the same size but different densities: silica sand and sepiolite particles. The higher density of silica sand particles induces a flotsam behavior for the sewage sludge particles which move close to the bed surface. In contrast, the lower density of sepiolite produces a neutrally-buoyant behavior for the sewage sludge particles, which shows a proper circulation throughout the whole bed in this case. The analysis of the evolution of the pyrolysis process in both fluidized beds show that the pyrolysis is faster when buoyancy effects are negligible, i.e. in the bed conformed by sepiolite particles. Moreover, sepiolite was found to show an absorbent capability for the volatile matter released during the pyrolysis of sewage sludge.

Keywords: Bubbling fluidized bed, pyrolysis time, segregation effects, sewage sludge.

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

Abstract:

Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries.

In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530.

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Authors: Ana Lambelho

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In an economic crisis such as the one that shook (and still shake) Europe, one does not question the importance of the measures that encourage the hiring and integration of young people into the labour market. In the mentioned context, enterprises tend to reduce the cost of labour and to seek flexible contracting instruments. The professional internships allow innovation and creativity at low cost, because, as they are not labour contracts, the enterprises do not have to respect the minimum standards related to wages, working time duration and so on. In Portugal, we observe a widespread existence of training contracts in which the trainee worked several hours without salary or was paid below the legally prescribed for the function and the work period. For this reason, under the tripartite agreement for a new system of regulation of labour relations, employment policies and social protection, between the Government and the social partners, in June 2008, foresaw a prohibition of professional internships unpaid and the legal regulation of the mandatory internships for access to an activity. The first Act about private internship contracts, i.e., internships without public funding was embodied in the Decree-Law N. 66/2011, of 1^st June. This work is dedicated to the study of the legal regime of the internship contract in Portugal, by analysing the problems brought by the new set of rules and especially those which remains unresolved. In fact, we can conclude that the number of situations covered by the Act is much lower than what was expected, because of the exclusion of the mandatory internship for access to a profession when the activity is developed autonomously. Since the majority of the activities can be developed both autonomously or subordinated, it is quite easy to out of the Act requirements and, so, out of the protection that it confers to the intern. In order to complete this study, we considered not only the mentioned legal Act, but also the few doctrine and jurisprudence about the theme.

Keywords: Intern, internship contact, labour law, Portugal.

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Authors: Jonathan N. Nayga, Emelita B. Valdez, Mila R. Andres, Beulah B. Estrada, Emelina A. Lopez, Rogelio B. Tamayo, Aubrey Joy M. Balbin

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Goat production is one of the activities included in integrated farming in the Philippines. Goats are raised for its meat and regardless of breed the animal is slaughtered for this purpose. In order to document the carcass yield of different goats slaughtered, five (5) different breeds of goats to include Purebred Boer and Anglo-nubian, Crossbred Boer and Anglo-nubian and Philippine Native goat were used in the study. Data on slaughter parameters, carcass characteristics, and sensory evaluation were gathered and analyzed using Complete Random Design (CRD) at 5% level of significance and the results of carcass conformation were assessed descriptively. Results showed that slaughter data such as slaughter/live weight, hot and chilled carcass weights, dressing percentage and percentage drip loss were significantly different (P>0.05) among breeds. On carcass and meat characteristics, pure breed and upgraded Boer were found to be moderately muscular while Native goat was rated as thin muscular. The color of the carcass also revealed that Purebred and crossbred Boer were described dark red, while Native goat was noted to be slightly pale. On sensory evaluation, the results indicated that there was no significant difference (P>0.05) among breeds evaluated. It is therefore concluded that purebred goat has heavier carcass, while both purebred Boer and upgrade are rated slightly muscular. It is further confirms that regardless of breed, goat will have the same sensory characteristics. Thus, it is recommended to slaughter heavier goats to obtain more carcasses with better conformation and quality.

Keywords: Carcass quality, goat, sensory evaluation, slaughter.

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: Political tendency, prediction, sentiment analysis, Twitter.

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Authors: S. Figueiredo, M. Alves Martins, C. Silva, C. Simões

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This study integrates a larger research empirical project that examines second language (SL) learners’ profiles and valid procedures to perform complete and diagnostic assessment in schools. 102 learners of Portuguese as a SL aged 7 and 17 years speakers of distinct home languages were assessed in several linguistic tasks. In this article, we focused on writing performance in the specific task of narrative essay composition. The written outputs were measured using the score in six components adapted from an English SL assessment context (Alberta Education): linguistic vocabulary, grammar, syntax, strategy, socio-linguistic, and discourse. The writing processes and strategies in Portuguese language used by different immigrant students were analysed to determine features and diversity of deficits on authentic texts performed by SL writers. Differentiated performance was based on the diversity of the following variables: grades, previous schooling, home language, instruction in first language, and exposure to Portuguese as Second Language. Indo-Aryan languages speakers showed low writing scores compared to their peers and the type of language and respective cognitive mapping (such as Mandarin and Arabic) was the predictor, not linguistic distance. Home language instruction should also be prominently considered in further research to understand specificities of cognitive academic profile in a Romance languages learning context. Additionally, this study also examined the teachers’ representations that will be here addressed to understand educational implications of second language teaching in psychological distress of different minorities in schools of specific host countries.

Keywords: Second language, writing assessment, home language, immigrant students, Portuguese language.

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Authors: Redouane Tlemsani, Abdelkader Benyettou

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Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology.

This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data.

Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables.

In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization.

The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition.

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