bluuebunny/crossref_metadata_2025 huggingface dataset:
Changes in Microbial Community as Affected by Soil Compaction and Organic Matter Amendment
Authors: Ishak Lily , Brown Philip H.
Published: March 2019

Soil compaction may threaten agricultural sustainability through its impact on altering soil microbial structure and function. This occurs as a result of the limitation of air permeability and oxygen availability, which has implications for soil nutrition and soil-borne disease. The present study aimed to assess compaction effect on changes of soil microbial communities over time and whether these changes were influenced by organic matter (OM) amendment. An experiment consisted of two levels of compaction (1.1 and 1.4 g cm-3) and two levels of OM (0 and 10 g kg-1). Soil microbial community attributes investigated were soil respiration, microbial biomass, activity and diversity. Data on microbial attributes were obtained from three-sampling times (10; 20; 80 days). The results showed that microbial respiration, biomass, activity and diversity changes over time and were higher in compacted soil than uncompacted soil in day-10, but then higher in uncompacted soil at day-20. An increase in microbial biomass, activity and diversity in uncompacted soil within 20 days were presumably associated with the availability of soil organic carbon (SOC), void space and aeration. However, microbial biomass, activity and diversity across the treatments declined in day-80, where bacteria and fungi performed a different pattern. Bacterial community was lower in compacted soil at day-80 and this might be an indicator of the effect of compaction and of the reduction in SOC availability. Meanwhile, fungal community was found to be higher in compacted soil over 80 days confirming the ability of fungal communities to survive under such an environment.
The Potential Areas for Crop Development in Morotai Island Regency, Indonesia
Authors: Sudjud Suratman , Hadun Ramli
Published: March 2019

The needs of food in Morotai Island Regency always increase over time, along with the increase in population. On the other hand, the available food potential is still low in productivity to meet the needs. Crop development in Morotai Island Regency, as an effort to fulfill local food needs, can still be done because the land resources potential is available and not optimally utilized. Agricultural land is the main resource for rural community development and food supply. The objectives of this research are: (1) To find out the potential of land resources and availability for crop development in Morotai Island Regency; (2) Identifying the advantages and prospects of crop development in Morotai Island Regency and (3) Preparing the recommendations for the development and management of land for crops in Morotai Island Regency. Data analysis consists of the needs and advantages of crops, farming feasibility, income, revenue, and land suitability. The results show that the suitable (S) land potential for the development of crops reaches 55,624.7 ha. Potentially suitable land for lowland rice, which classified as sufficiently suitable (S2), reaches 34,290.5 ha and marginally suitable (S3) land reaches 7,282.5 ha. Sufficiently suitable (S2) and marginally suitable (S3) lands for upland rice reach 25,040.3 ha and 28,932.8 ha respectively. As for corn cultivation, sufficiently suitable (S2) land reaches 25,040.3 ha and marginally suitable (S3) lands reaches 28,932.8 ha.  Development of food crops as a result of analysis of harvested LQ shows that base food crops in South Morotai District are wetland rice (1.06), corn (1.02). East Morotai sub-district is based on the development of wetland rice (1.14) and upland rice (1.02). Morotai Selatan Barat Subdistrict is the base for the development of lowland rice (1.42). North Morotai District is the base for the development of upland rice (1,15). While Morotai Jaya is the base for developing upland rice (1.49), corn (1.53).   Leading crop/s in South Morotai District are lowland rice and corn; Southwest Morotai is lowland rice; East Morotai are lowland rice and upland rice; North Morotai is upland rice; and Morotai Jaya are upland rice and corn.
Application of Embryo Transfer Technology to Improve Fertility Using GnRH Plus Progesterone and Estradiol Combination (FTAI) of Local South Pesisir Cow in West Sumatra
Authors: Udin Zaituni , Hendri - , Masrizal Masrizal
Published: March 2019

The objective of this research was to evaluate the effect of FTAI  on embryo production  that  used GnRH plus progesterone combination to synchronize ovulation of 3 different parity of donor from local pesisir cows  in west Sumatra. This study used timed embryo transfer program using GnRH plus progesterone combination in 3 local pesisir cows and 2 cows in time embryo program using estradiol plus progesterone of donor.  Ovarian ultrasonography was performed on d 0 (time of AI) and at flushing to determine ovulatory diameter and ovulation. On d 0 at the time CIDR implant + PGF2Î± injection and on d 7 started ovsynch protocol  administrated by injection GnRH and FSH for FTAI without detection estrus. The number and the quality of embryo was evaluated to determine the fertility of pesisir selatan cows. The result showed that the expression of estrus cows tend to high ovulation rate. The diameter size of a follicle was range from 5 to 15 mm with 10.67±2.96 mm in GnRH plus progesterone and 5 to 14 mm with mean was 8.75±2.05 mm in estradiol plus progesterone (P<0.005). The number of follicle ovulation was 27 in treatment A and 18 in treatment B (P<0.05). The number of CL and embryos was higher in treatment A.  CL was 19, with 18 embryos and in treatment B was 9 with 6 embryos. The quality of embryo range from 1-4 grade with the transferable embryos was higher in treatment A than treatment B (P<0.05). There was the linear regression between ovular follicle, CL and number of embryos recovery of local pesisir cows.  It was concluded that equal numbers of embryos and transferable embryo  by using  GnRH plus progesterone combination  of local pesisir cows.
Identification of Pig Adulterant in Mixture of Fat Samples and Selected Foods based on FTIR-PCA Wavelength Biomarker Profile
Authors: Saputra Irwan , Jaswir Irwandi , Akmeliawati Rini
Published: March 2019

Authenticity is an important issue in food industry. Tampering the authenticity of food product involves the adulteration of products with certain material. Various authentication techniques for detection of adulteration have been developed in line with the advent of current technology. Of particular interest,  Infrared (IR) spectroscopy; a rapid and non-destructive technique allowing the screening of a large number of samples has been shown to be able to detect pig derivatives in meat products. Following this, the present study aims to identify pig adulteration in different mixture of fat samples and some selected food; based on wavelength biomarker obtained from FTIR coupled with PCA analysis. Twenty-six fats at two frequencies along the graph (1236 and 3007 nm) were studied including samples representing Non Halal Food A (NHFA) fat,  Halal Food A(HFA) fat and Non Halal Food B (NHFB) fat.  At wavelength 1236 and 3007 nm along the spectrum; NHFA, HA and NHFB fat samples were easily identified at visibly good distance compared to other fat samples.  The first two samples; NHFA and NHFB were located very close to PF (Pig Fat) indicating that NHFA and NHFB samples contained pork fat while HA was located closer to CF, indicating that the sample possibly contained chicken fat. To this end, FTIR coupled with PCA has been shown to be a powerful tool to detect adulteration in meat products and as such can be recommended for authentication purposes.
Analysis of Gelatin Adulteration in Edible Bird’s Nest using Fourier Transform Infrared (FTIR) Spectroscopy
Authors: Jamalludin Nurul H. , Tukiran Nur A.
Published: March 2019

Fraudulent incorporation of cheaper materials such as porcine gelatin into edible bird’s nest (EBN) can evolve into a problem for reasons related to religious, allergy, ethical, and legal requirement. Thus, this study aimed to detect porcine gelatin in the processed EBNs by using a combination method of Fourier transform infrared (FTIR) and chemometrics analysis, Principal Component Analysis (PCA). The use of FTIR spectroscopy in food analysis is becomes more attractive because of its cost-effective nature, nondestructive measurements as well as convenience for screening purposes. This method has been established to be useful for adulteration detection and quantification in various food products. However, its application as a sole method is often not reliable as some transitions of the spectrums are very complex or weak, making evaluation difficult. Thus, in this study FTIR data were further analysed with the chemometrics analysis. By considering all the data obtained, chemometrics makes better results feasible. Porcine gelatin exhibited a dominant band at Amide I indicating the adulteration of EBNs with porcine gelatin. The FTIR spectra were analysed using PCA in order to identify the adulteration percentage in the samples. In the assessment of the spiked samples, this method could detect at the minimum of 5% of porcine gelatin in EBNs. This method would be advantageous for ensuring quality of the EBN products in the market.
Water Harvesting as a Technological Innovation and Greater Solving of Climatic Change Impact to Supply Fertigation
Authors: Bafdal Nurpilihan , Dwiratna Sophia , Suryadi Edy , Kendarto Dwi Rustam
Published: March 2019

Water is one critical factor in the agriculture sector and becomes the first barrier in agriculture production. In the dry season, water availability without depending on the season expertise should be able to find the technological innovation that can be used to the farmers, especially in the rural areas. Global climate change caused more long dry season and will impact to decrease of water from rainfall and runoff. Rainfall and runoff harvesting it means capturing water from rainfall where it falls or capturing in and can be stored it the torrents and ponds and good enough for resources of fertigation. Fertigation engineering is the application of supplying irrigation and fertilizer to crops and engineering principles to the solution of water management problem. Research of water harvesting with cultivated of red oval cherry tomato and planted was carried out at the greenhouse located in Universitas Padjadjaran Campus, West Java Province, Indonesia from January to Mei 2017. The research method is descriptive analysis, and the red oval tomato planted it on the autopot with growth media uses mixed of charcoal husk and zeolite with ratio 9: 1 and 15 cm height.  The amount of water harvesting from the green house’ rooftop is 20200,5 liter per year.The amount of water used by tomato plant used auto pot is 427,12 liter.    The research shows that the water used of red oval tomato where for initial stage 66 liter; development stage 36,22 liter; midseason stage 310,04 liter  and late seasons stage 14,86 liter; average total water used for red oval tomato at 8,21 liter/plant. The average yield of red oval tomato per plants using autopot where the lowest yield was 0.731 kg/plant while the highest yield of 1.648 kg/plant. The value of water use efficiency of red oval tomato is 10.kg/m3.
IT Risk Identification and Evaluation: a Case Study on XYZ University
Authors: Albertivan Daniel , Limantara Hendryantono , Rachmadiati Reza Annisa , Surantha Nico , Pamungkas Adik Wedsa
Published: March 2019

The purpose of this paper is to demonstrate that Failure Mode Effect Analysis (FMEA) can be applied to the educational field to identify various failure modes and its potential failure effect that could occur in anytime. FMEA is widely used in a design, a manufacturing or assembly process, or a product and service for identifying all possible failures. Risk identification is part of risk management. Therefore it is a critical first step of it. This paper is a case study on XYZ University which trying to implement risk management which only focused on how to identify the risk using FMEA. FMEA needs some parameters to be defined which are severity values, the likelihood of occurrence, and detection. Risk Priority Number (RPN) is a matrix that indicates potential risk calculated by multiplying the three components, and it used to classify which should be taken care of first based on the highest RPN value. Filtering the ticketing system and mapped the incidents that happened to the current business process is how the data collected, also the interview to end user for validation. The result of this paper is astonishing because it is different from the initial expectation that business process like LMS or network facility will get the highest RPN value, but after doing all the process, it is found that telecommunication is at the top. Surely this provides a new perspective to risk management to be slicker in handling potential one.
Physicochemical Properties of Egg Yolk Powder from Eggs of Different Types of Bird
Authors: Wei Lim Jing , Alkarkhi Abbas F.M. , Huda Nurul
Published: March 2019

The goal of this study was to determine whether the physicochemical properties of egg yolk powders produced from eggs from different types of bird (Fighting chicken, Kampung chicken, Serama chicken, Leghorn chicken, Guineafowl, and Turkey) differ from each other and from those of commercial egg yolk powder. The powders were analysed to determine yield; proximate composition; colour, solubility; water holding capacity (WHC); and emulsion activity and stability. Egg yolk powders were prepared by separating the egg yolk manually followed by blast freezing and freeze drying. The weight of the egg ranged from 22.16 g for Serama to 66.25 g for Turkey. The lowest yield of egg yolk liquid was found in Leghorn egg (27.63) and highest in Serama egg (44.31).  Egg yolk powder yield was also lowest for Leghorn eggs (12.85%) , followed by Turkey (15.85%), Guineafowl (16.22%), Kampung (16.48%), Fighting (16.62%), and the highest for Serama (18.92%). All parameters studied except WHC differed significantly (p < 0.05) among at least some of the different egg yolk powders. Egg yolk powder from Serama chicken had the highest protein content (40.77%), lowest fat content (51.96%), highest solubility (20.20 oBrix), and lowest WHC (79.78 %). Egg yolk powder from Fighting chicken had the highest emulsion activity (54.13%) and that from Leghorn chicken had the highest emulsion stability (48.41%). Egg yolk powder from Guineafowl had the highest yellowness intensity (72.21), whereas the value was lowest (35.84) for commercial egg yolk powder. In conclusion, physicochemical properties of egg yolk powder depend on the source of the eggs.
Segmentation of Carpal Bones Using Gradient Inverse Coefficient of Variation with Dynamic Programming Method
Authors: Jantan Sadiah , Muad Anuar Mikdad , Hussain Aini
Published: March 2019

Segmentation of the carpal bones (CBs) especially for children above seven years old is a challenging task in computer vision mainly because of poor definitions of the bone contours and the occurrence of the partial overlapping of the bones. Although active contour methods are widely employed in image bone segmentation, they are sensitive to initialization and have limitation in segmenting overlapping objects.  Thus, there is a need for a robust segmentation method for bone segmentation. This paper presents an automatic active boundary-based segmentation method, gradient inverse coefficient of variation, based on dynamic programming (DP-GICOV) method to segment carpal bones on radiographic images of children age 5 to 8 years old. A mapping procedure is designed based on a priori knowledge about the natural growth and the arrangement of carpal bones in human body. The accuracy of the DP-GICOV is compared qualitatively and quantitatively with the de-regularized level set (DRLS) and multi-scale gradient vector flow (MGVF) on a dataset of 20 images of carpal bones from University of Southern California. The presented method is capable to detect the bone boundaries fast and accurate. Results show that the DP-GICOV is highly accurate especially for overlapping bones, which is more than 85% in many cases, and it requires minimal user’s intervention. This method has produced a promised result in overcoming both issues faced by active contours method; initialization and overlapping objects.
Effect of Mechanical Tumbling Parameters on Surface Roughness and Edge Radius of Medical Grade Cobalt Chromium Alloy
Authors: Nanda Is Prima , Hassim Mohd Hazwan , Idris Mohd Hasbullah , Jahare Muhammad Hafiz , Arafat Andril
Published: March 2019

Smoothly polished prosthesis surface is a crucial requirement in medical application and important feature that determine the proper response to corrosion and biocompatibility in the human body. Tumbling is one of the pre-polishing processes that can be conducted in order to improve the surface roughness of the machined prosthesis. However, the using of ceramic media for the tumbling process in medical application is not widely reported. This study was conducted to investigate the effect of mechanical tumbling parameters on the surface roughness of medical grade CoCr alloy by using alumina (Al2O3) based ceramic media. The experiment was performed with a different level of rotational speed (35, 55, and 75 rpm) and soaking time (4, 6 and 8 hours) of the tumbling process. The surface roughness of specimens before and after the process was measured using Mitutoyo Formtracer CS-5000 and the edge radius was measured using Olympus SZX9 microscope integrated with I-solution Lite software. It was figured that 6 hours tumbling time at 55 rpm showed the most significant reduction (32 %) in surface roughness (Ra) of the CoCr alloy specimen, while 8 hours tumbling time at 75 rpm showed the highest effect on the edge radius of the specimen at 63 % increment.
Real-Time Wheat Classification System for Selective Herbicides Using Broad Wheat Estimation in Deep Neural Network
Authors: Ullah Arif , Mohd Nawi Nazri , Arifianto Anditya , Ahmed Imran , Aamir Muhammad , Khan Sundas Naqeeb
Published: March 2019

Identifying seed manually in agriculture takes a long time for practical applications. Therefore, an automatic and reliable plant seeds identification is effectively, technically and economically importance in agricultural industry. In addition, the current trend on big data and data analysis had introduced scientist with many opportunities to use data mining techniques for better decision in various application. Recently, there are various number of applications that use computer-aided in improving the quality in controlling system. Classifying different types of wheat hold significant and important role in agriculture field. An improvement on such kind of system that makes distinctions based on shape color and texture of wheat plantation is crucial. The main objective of this paper is to develop a machine vision system which identifies wheat base on its location. For this purpose, a real time robotics system is developed in order to find plant in sorrowing area using pattern recognition and machine vision. For real-time and specific herbicide applications, the images are categorized in either expansive or precise categories via algorithm following the principal of morphological operation. Different experiments were conducted in order to gauge the efficiency of the proposed algorithm in terms of distinguishing between various types of wheats. Furthermore, the experiments also performed admirably amid varying field conditions. The simulation results show that the proposed algorithms exhibited 94% success rate in terms of categorizing wheat population which consists of 80 samples and out of them 40 are narrow and 40 broad.
An Algorithm for Plant Disease Visual Symptom Detection in Digital Images Based on Superpixels
Authors: Salazar-Reque Itamar F. , HuamÃ¡n Samuel Gustavo , Kemper Guillermo , Telles Joel , Diaz Daniel
Published: March 2019

Quantifying diseased areas in plant leaves is an important procedure in agriculture, as it contributes to crop monitoring and decision-making for crop protection. It is, however, a time-consuming and very subjective manual procedure whose automation is, therefore, highly expected. This work proposes a new method for the automatic segmentation of diseased leaf areas. The method used the Simple Linear Iterative Clustering (SLIC) algorithm to group similar-color pixels together into regions called superpixels. The color features of superpixel clusters were used to train artificial neural networks (ANNs) for the classification of superpixels as healthy or not healthy. These network parameters were heuristically tuned by choosing the network with the best classification performance to obtain the automatic segmentation of the diseased areas. The performance of the classifier was measured by comparing its automatic segmentations with those manually made from a database with public and private images divided into nine groups by visual symptom and plant. The mean error of the area obtained was always below 11%, and the average F-score was 0.67, which is higher than that found by the other two approaches reported in the literature (0.57 and 0.58) and used here for comparison.
Evaluation of Packet Tracer Application Effectiveness in Computer Design Networking Subject
Authors: Ambiyar - , Yondri Surfa , Irfan Dedy , Putri Meilani , Zaus Mahesi Agni , Islami Syaiful
Published: March 2019

The dynamics of technological progress in various fields indirectly affect the world of education. One of the indications can be seen in the use of media as a learning tool. This study aims; 1) to investigate the effectiveness of the packet tracer learning media application, 2) to investigate the responses of the students to such applications, 3) to determine the appropriate media used in a learning process.  The research is carried out in the subject of Computer Design Networking. The evaluation research is employed by using a mixed method of qualitative and quantitative approach. The quantitative analysis involved 58 students, while the qualitative analysis involved one productive teacher, one curriculum representative, and four students. Data are analysed by using quantitative and qualitative data analysis techniques. The results show that, the effectiveness of learning media with packet tracer is high i.e., 82.76%, which covers three aspects; software engineering, learning aspects, and display aspects. This means that this packet tracer learning media can be applied as a solution to the limitation of facilities and infrastructures of network practices by considering certain learning situations and conditions. The results indicate that this application is very useful to deal with the high cost of practising tools. It makes the students more enthusiastic and motivated during the learning process. Hence, by implementing this learning method, the interaction and the learning outcomes of the student can be increased.
A Software Development Methodology for Secure Web Application
Authors: Lee Junho , Woo Jungwoong , Lee Cheongan , Joo Kyungsoo
Published: March 2019

In recent years, there has been a demand for Web applications with complex functions. In addition, most web applications efficiently manage data based on databases. While the key and critical dimension of developing these Web applications is analysis and design, most object-oriented analysis and design methods do not have a consistent view of the database. In addition, Java Enterprise Edition (EE) -based technologies are used in Web application implementations, but they do not provide any correlation with the database. On the other hand, as users' demands for security increase, security becomes more important. To this end, Java EE and database systems provide security solutions. However, it does not provide any correlation with object-oriented analysis and design methodology. As a result, it is difficult to develop secure web applications in a consistent way from analysis to implementation. In this paper, we propose a consistent software development methodology from analysis to implementation of secure web applications. The proposed software development methodology for web application development uses UMLsec, a security-emphasized modeling language, and object-relational (O-R) mapping for relational database design. It also uses Java servlets and SQL to implement analysis and design results based on role-based access control (RBAC). The software development methodology for the secure web application proposed in this paper has been applied to the development of the online banking system, from the design stage of the user's requirements analysis to the implementation of the web application.
Co-existence Issue in IoT Deployment using Heterogeneous Wireless Network (HetNet): Interference Mitigation using Cognitive Radio
Authors: Mishra Ayaskanta
Published: March 2019

In today’s era of Machine-to-Machine (M2M) communication, where a tiny embedded device is having enough functionality and computational power to be network enabled for various applications aided with sensors, relays, and actuators to make Internet-of-Things (IoT) a reality. IoT is not a technology by itself rather a vision to interconnect every single piece of intelligent electronics using existing LAYER-I and II data communication standards and the internet based on OSI Layer Architecture. In the context of deployment of such IoT networks, it is imperative; a heterogeneous wireless network will be most viable for the need of different application-specific scenarios. The primary goal of this paper is to propose a Cognitive Radio (CR) Algorithm for mitigation of interference based on the analytical and empirical model of packet error rate (PER) for IEEE 802.15.4 network in the presence of IEEE 802.11 b/g/n network operating in the 2.4 GHz unlicensed industrial scientific medical (ISM) frequency band. The power spectral density (PSD) of three standards widely deployed IEEE 802.11 b/g/n are considered for determining the interference power of overlapping channels of IEEE 802.11 b/g/n. To create a test-bed for an Empirical Model Digi’s XBEE® 802.15.4 Zigbee modules is used for IEEE 802.15.4 and Intel/ Qualcomm (Atheros) WiFi Alliance adaptors are considered and IEEE 802.11 to validate the analytical model.
Considerations for Cost Estimation of Software Testing Outsourcing Projects
Authors: Ismail Fatin Filzahti , Razali Rozilawati , Mansor Zulkefli
Published: March 2019

Software testing outsourcing appears to be the best alternative to acquire better software quality with competent ratification by extrinsic parties who have the capability to do it. Through the effort, organizations are peeking to promising benefits constitute in it such as current testing technology, experts, an abridgment of the project’s duration and more concentration on the main organisation’s activity. Along with these benefits, one important reason that encourages the decision is optimization of cost expenditure, which the strategy is perceived as a good move for a competitive organization. However, implementing such preference eventually results in a different outcome. Organizations have to bear the higher cost and incur losses of cost deviation from the expected estimation. The conflicting between cost and benefits raises an important concern of striving better cost estimation for such projects. This paper aims to address this interest by analyzing the existing literature in order to identify the contributing factors towards better cost estimation for software testing outsourcing project-context. The analysis is done using the content analysis method. The results could be divided into two categories; which are the cost items and contributing factors. Cost items consist of direct cost and indirect cost, which refers to the expenses for the project. While the contributing factors consist of people and environment, which are needed to produce accurate cost estimation. The findings provide an insight to excogitate attentively the essentials in the endeavor of improving the exactitude of cost estimation for software testing outsourcing project.
Factors Affecting Information Quality in the Malaysian Public Sector
Authors: Hassan Erizamsha , M. Yusof Zawiyah , Ahmad Kamsuriah
Published: March 2019

Information is an important asset that can determine the success or failure of an organization. Hence, the quality of information should not be compromised, instead, it should be an organization's priority. Information should be managed efficiently and effectively to ensure its availability whenever needed, especially for making decisions. Without information quality management, an organization may be seemed unaccountable, holds no integrity, not transparent and competent, thus affecting performance. Most organizations do not implement information quality management because the factors that affect the quality of information are not identified. This study aims to identify the relationship between selected factors and the quality of information. The quantitative data were collected through questionnaire surveys distributed to public organizations (federal public services, state public services, federal statutory bodies, state statutory bodies, and local authorities) throughout Malaysia as the unit of analysis. Questionnaires were distributed from May to September 2017 and involved 273 respondents. Pearson’s product-moment correlation coefficient was utilized to analyze the relationship between the factors and information quality. The findings reveal that most of the factors have a high level of correlation. The analysis shows that public organizations need to prioritize the factors focused in this study, especially those identified with a high level of correlation, to optimize information quality. The findings can be a guide for developing policies, strategies, or programmes related to information quality management in organizational decision-making and performance enhancement, thus highlighting and empowering information quality management in public organizations.
Lexical Disambiguation (CKBD): A Tool to Identify and Resolve Semantic Conflicts Using Context Knowledge
Authors: Al Tahat Said , Ahmad Kamsuriah
Published: March 2019

The schema matching process is a fundamental step in a schema integration system, and its quality impacts the overall performance of the system. Recently, a large number of schema matching approaches have been developed. Until today, the performance of schema matching is inherently uncertain and requires improvement. The most difficult task is inferring the real-world semantics of data from the information provided by schema labels in their representations. Usually, schemas with identical semantics are represented by different vocabularies and only their own designers can completely understand. A schema may contain synonyms and homonyms words. Therefore, it is necessary to understand how the schema elements are "presented"; it is often hard to get aware meaning associated with elements names, due to the semantic ambiguity of human language. Semantic ambiguity problem means the capability of being understood in two or more possible senses. Having more than one meaning for an individual schema element would cause confusion in interpretation of schema name. This may affect negatively on the matching result. Therefore, this paper aims to resolve this problem of semantic ambiguity and represent the intended meaning of the schema labels name, by introducing the CKBD (Context Knowledge-Based Disambiguation) approach. The CKBD is obtained by integrating two pieces of context knowledge:  semantic domain and more frequency used into a disambiguation processor.  Finally, the CKBD is implemented and is tested in a real dataset.  The result is deeply grounded in the ability to detect schema name intended meaning.
Multilayer Perceptron (MLP) and Autoregressive Integrated Moving Average (ARIMA) Models in Multivariate Input Time Series Data: Solar Irradiance Forecasting
Authors: Munandar Devi
Published: March 2019

Solar irradiance needs to estimate power consumptions for requiring of saving energy. The demand accomplished with providing facilities to predict. Time series data is a dataset that has complex problems. Using multilayer perceptron (MLP) and autoregressive integrated moving average (ARIMA) with multivariate input to solve the problem of predicting solar irradiance. The dataset is collected from solar irradiance sensor by an online monitoring station with 10 minutes data interval for 18 months. Prediction experimented with t, t-2, and t-6 data inputs that represent t as the day to get the predictive model (t+1). In ARIMA model, optimization was obtained in the input parameter (t-6) and ARIMA(1,1,2) with minimum RMSE is 43.91 W/m2, whereas MLP model used single layer, 10 neurons and using relu activation function to predict with minimum RMSE is 8.68 W/m2 using (t) input parameter. The deep learning model is better than the statistical model in this experiment. RMSE, MSE, MAE, MAPE, and R2, are used as an evaluation for model performance.
21st Century Skills Mastery Amongst Science Foundation Programme Students
Authors: Turiman Punia , Tengku Wook Tengku Siti Meriam , Osman Kamisah
Published: March 2019

The rapid growing of knowledge economy that relies on the advancement of ICT has changed the trend of employment and social life. Employers in this century are looking for competitive, innovative and global employees. As a consequence, students should be prepared to acquire 21st-century skills so that they can be successful in the employment and social life. Before that, this study has examined the mastery level of the 21st-century skills amongst science foundation programme students. This study has also investigated the relationships between former school location and gender on the mastery levels of the 21st-century skills. A total of 240 students from two foundation colleges participated in this quantitative study. The findings indicated that the mastery level of the 21st-century skills was high. All subdomains of the 21st-century skills were at a high mastery level. However, economy literacy as one of digital era literacy subdomains showed a moderate level. Meanwhile, creativity as one of the inventive thinking subdomains also showed a moderate level, and interactive communication as one of effective communication subdomains also showed a moderate level. Findings also revealed that there were no significant differences between former school location and gender on the mastery levels of the 21st-century skills amongst science foundation programme students.
Uniform Distorted Scene Reduction on Distribution of Colour Cast Correction
Authors: Talib Muhamad Lazim , Nasruddin Mohamad Faidzul , Sheikh Abdullah Siti Norul Huda
Published: March 2019

Scene in the photo occulated by uniform particles distribution can degrade the image quality accidently. State of the art pre-processing methods are able to enhance visibility by employing local and global filters on the image scene. Regardless of air light and transmission map right estimation, those methods unfortunately produce artifacts and halo effects because of uncorrelated problem between the global and local filter’s windows. Besides, previous approaches might abruptly eliminate the primary scene structure of an image like texture and colour. Therefore, this study aims not solely to improve scene image quality via a recovery method but also to overcome image content issues such as the artefacts and halo effects, and finally to reduce the light disturbance in the scene image. We introduce our proposed visibility enhancement method by using joint ambience distribution that improves the colour cast in the image. Furthermore, the method is able to balance the atmospheric light in correspondence to the depth map accordingly. Consequently, our method maintains the image texture structural information by calculating the lighting estimation and maintaining a range of colours simultaneously. The method is tested on images from the Benchmarking Single Image Dehazing research by assessing their clear edge ratio, gradient, range of saturated pixels, and structural similarity metric index. The scene image restoration assessment results show that our proposed method had outperformed resuls from the Tan, Tarel and He methods by gaining the highest score in the structural similarity index and colourfulness measurement. Furthermore, our proposed method also had achieved acceptable gradient ratio and percentage of the number of saturated pixels. The proposed approach enhances the visibility in the images without affecting them structurally.
A Modified Event Grouping Based Algorithm for The University Course Timetabling Problem
Authors: Kralev Velin Spasov , Kraleva Radoslava Stankova , Kumar Sachin
Published: March 2019

This paper presents a study of a modified event grouping based algorithm (MEGB) for university course timetabling problem (UCTP). Multiple models to describe the problem and multiple approaches to solving it are pointed out. The main idea of the modification is that through reduction on the generated solutions the execution time of the standard event grouping based algorithm (EGB) will be reduced, too. Also, an implementation of the modified algorithm based on the described approach is presented. The methodology, conditions and the aims of the experiment are described. The experimental results are analyzed and conclusions are made. When increasing the number of the groups, the execution time of the MEGB algorithm increases and equates with the execution time of the EGB algorithm. The best results are obtained with the first 30% of the groups formed. In these groupings, the execution time of the MEGB algorithm is much less than the execution time of the EGB algorithm. This is because, in the EGB algorithm, every change in the event ordinance creates a new timetable, and all events are repositioned on it. This process is optimized by creating a partial timetable, whereby the ordinance of events in groups before the current does not change. In addition, a comparative analysis between the MEGB algorithm and two other algorithms for UCTP, respectively a genetic algorithm with the local search method (GALS) and a local search algorithm based on chromatic classes (CCLS) is made as well. The obtained results show that the MEGB algorithm and the CCLS algorithm generate better solutions for smaller input data sets, while the GALS algorithm generates better solutions for larger input data sets. However, in terms of the execution time, it was ascertained that the GALS algorithm runs slowest among the others.
Sedimentation Dynamics of the Lower Part of Sentolo Formation at Niten Stream Traverse, Girimulyo, West Progo
Authors: Pambudi Setyo , Isnaniawardhani Vijaya , Winantris Winantris , Sudradjat Adjat
Published: March 2019

Previous geologists showed that Sentolo Formation was interfingering with Jonggrangan Formation and both of them laid unconformably on Old Andesite Formation. The aim of this study is a deeper understanding of the sedimentation dynamics of Sentolo Formation in order to know its stratigraphic relationship to Old Andesite Formation. Petrographic analysis was used to describe the microfacies. Paleontological analysis was used to know the age and sedimentation environment. Stratigraphic measurement of Sentolo Formation in the section of Niten Stream traverse showed that Sentolo Formation was sedimented on the basin environment (SMF3/FZ1; SMF2/FZ1), deep shelf margin (SMF3/FZ3) to foreslope (SMF4/FZ4). The paleontological data indicate that these sedimentary rocks was depositing during Early Miocene until the beginning of Middle Miocene (N6 - N9). Sedimentary rock succession is generally dominated by layered limestone with tuff sandstones that develop well in the lower - middle layer. It indicates that the dynamic of basin sedimentation which formed during that period was influenced by volcanic activity that gradually weakened and caused the basin relatively quiet, producing thick limestone.
Integrating Business Intelligence and Analytics in Managing Public Sector Performance: An Empirical Study
Authors: Zulkifli Abai Nur Hani , Yahaya Jamaiah , Deraman Aziz , Hamdan Abdul Razak , Mansor Zulkefli , Yah Jusoh Yusmadi
Published: March 2019

Business intelligence and analytics (BIA) is emerging as a critical area to boost organizational performance. Nowadays, data is not only important and valuable to the organization but recognized as necessary to spike the organization performance and success. As a result, many organizations spend a considerable amount of investment toward obtaining faster accurate information on a real-time basis. The previous study revealed that even though many organizations use business intelligence technologies for obtaining information, yet they still lack analytics implementation. Therefore, this study aims to discover the integrated implementation factors of business intelligence and analytics in managing organizational performance, particularly for organizations of the public sector. In achieving this, a depth literature review was carried out to identify the influential factors in the implementation of business intelligence, business analytics, and performance management. The subject matter experts in Business Intelligence (BI), Business Analytics (BA) and Organisational Performance Management (OPM) were invited to participate in this empirical study, which was conducted in Malaysia. The study was carried out through interviewing experts, in order to identify the essential factors for business intelligence and data analytics implementation. Twenty essential factors and sixty-four sub-factors were identified and analyzed to construct the integrated factors in BIA and OPM implementation. The result of the study revealed four integrated factors of the BIA and OPM implementation, such as skill, documentation, visualization, and work culture. Finance, data management, software, strategic planning, and decision-making are other factors integrated with BI, BA, and OPM respectively. Finally, this study illustrates the integrated factors in a visual form.
FPGA Implementation of Hand-written Number Recognition Based on CNN
Authors: Giardino Daniele , Matta Marco , Silvestri Francesca , Spanò Sergio , Trobiani Valerio
Published: March 2019

Convolutional Neural Networks (CNNs) are the state-of-the-art in computer vision for different purposes such as image and video classification, recommender systems and natural language processing. The connectivity pattern between CNNs neurons is inspired by the structure of the animal visual cortex. In order to allow the processing, they are realized with multiple parallel 2-dimensional FIR filters that convolve the input signal with the learned feature maps.  For this reason, a CNN implementation requires highly parallel computations that cannot be achieved using traditional general-purpose processors, which is why they benefit from a very significant speed-up when mapped and run on Field Programmable Gate Arrays (FPGAs). This is because FPGAs offer the capability to design full customizable hardware architectures, providing high flexibility and the availability of hundreds to thousands of on-chip Digital Signal Processing (DSP) blocks. This paper presents an FPGA implementation of a hand-written number recognition system based on CNN. The system has been characterized in terms of classification accuracy, area, speed, and power consumption. The neural network was implemented on a Xilinx XC7A100T FPGA, and it uses 29.69% of Slice LUTs, 4.42% of slice registers and 52.50% block RAMs. We designed the system using a 9-bit representation that allows for avoiding the use of DSP. For this reason, multipliers are implemented using LUTs. The proposed architecture can be easily scaled on different FPGA devices thank its regularity. CNN can reach a classification accuracy of 90%.
Effect of Firing Temperatures on Physico - Mechanical Properties of Clay Bricks Containing Reeds
Authors: Salman Ghazwan Abdulsamad , Salih Shakir Ahmed
Published: March 2019

This research studies the effect of changing burning temperature on some properties of clay bricks containing reed crumbs. The experimental program includes production of clay bricks by adding (5-25) % by weight of reed crumbs to the clay before burning. The effect of addition of reed crumbs on properties of the produced brick such as dry density, Water absorption, and compressive strength were studied. Results of this research showed that it is possible to produced lightweight clay brick by adding (5-25) % of reed crumbs. Result also showed that a relatively good dry density and compressive strength could be obtained from the produce clay bricks made from addition of 5% reed crumbs. This type of brick led to save environment from huge amounts of agricultural wastes which its burning led to huge environmental pollution. It is discovered that, rising burning temperature from 800°C to 900°C and then to 1000°C causes a slight decrease in compressive strength and bulk densities values of the produced lightweight fired clay bricks containing reed. On the other hand rising burning temperature to the same degree as above causes a slight increase in the values of water absorption of the manufacture lightweight fired clay bricks containing reed. The laboratory experiments showed that lightweight fired clay bricks containing reed crumbs could be manufacture in the same factories of production of ordinary bricks without need to new machines. The steps of manufacturing this kind of bricks were found in this research the same for the ordinary one. The process of manufacture of lightweight clay bricks containing reed showed economical method of producing this kind of bricks.
The Impact of Employee Involvement and Empowerment in Lean Manufacturing System Implementation towards Organizational Performances
Authors: Roslin Eida Nadirah , Ahmed Shamsuddin , Ahamat Mohamad Asmidzam , Bahrom Mohd Zaki , Ibrahim Norazlin
Published: March 2019

Lean Manufacturing System (LMS) implementations in Malaysia’s automotive industry has not been extensive in its expected reach, as extensive inquiries revealed it being adopted as a “pick-and-choose” system for certain processes or only upon determined levels within the industry. Current implementation strategy does not permit the industry to gain total benefits from the system itself. Undeniably, a few significant factors are being given less significance in multiple stages of LMS’ execution. Employee involvement and employee empowerment have been identified as part of these contributing factors in a successful implementation of LMS in an organization. However, important criterion with its contributing aspects of these factors is not given the necessary attention, translating into a lamer impact upon companies embarking on a LMS deployment. This paper examines the impact of these two factors in the implementation of a lean manufacturing system towards achieving organizational performances in the automotive industry. A questionnaire-survey was administered to gauge the impact of these two factors in an implementation process of a lean manufacturing system and later analyzing the effect towards their organizational performances. Data from 204 automotive parts manufacturers were gathered and analyzed. The correlation between the influencing factors, 5 lean activities and 6 organizational performances were measured. The results gained suggest that the integration between employee involvement and employee empowerment will be a valuable critical organizational capability impacting organizational performances towards the successful implementation of LMS in the Malaysian automotive industry.