bluuebunny/crossref_metadata_2025 huggingface dataset:
MOTIVASI PEMBELAJARAN SEBAGAI PEMBOLEH UBAH PENGANTARA DALAM PERHUBUNGAN ANTARA BIMBINGAN PENYELIA DENGAN MOTIVASI KERJA (Learning Motivation as a Mediating Variable in the Relationship between Supervisory Guidance and Job Motivation)
Authors: Mohamad Nur Izzaty , Ismail Azman , Mohd Shariff Mohd Nor
Published: August 2020

Tujuan kajian ini adalah untuk menilai perhubungan antara bimbingan penyelia, motivasi pembelajaran dan motivasi kerja. Borang soal selidik telah digunakan untuk mengumpul data daripada pekerja di Agensi-agensi Pusat Kerajaan Persekutuan Malaysia, Putrajaya. Perisian SmartPLS telah digunakan untuk menilai kualiti data borang soal selidik dan menguji hipotesis-hipotesis kajian. Keputusan analisis model laluan SmartPLS menunjukkan bahawa kesan bimbingan penyelia terhadap motivasi kerja dipengaruhi secara tidak langsung oleh motivasi pembelajaran. Dapatan kajian ini menerangkan bahawa keupayaan penyelia mengamalkan bimbingan secara teratur dalam melaksanakan operasi kerja harian dapat membangkitkan motivasi pembelajaran dalam diri pekerja. Natijahnya, motivasi ini boleh pula mendorong mereka meningkatkan motivasi kerja. Dapatan kajian ini boleh digunakan sebagai panduan oleh pengamal untuk memahami kerumitan konsep motivasi pembelajaran dan merangka pelan tindakan strategi untuk meningkatkan kemahiran kejurulatihan kepimpinan bagi mencapai dan mengekalkan matlamat dan strategi organisasi dalam era globalisasi dan ekonomi berasaskan pengetahuan.   Kata Kunci: Bimbingan penyelia, motivasi pembelajaran, motivasi kerja, SmartPLS.     Abstract    The aim of this study is to assess the relationship between supervisors’ coach, learning motivation and job motivation. Survey questionnaires were used to collect data from employees at Malaysian Federal Government Central Agencies, Putrajaya. The SmartPLS was utilised to evaluate the quality of survey questionnaire data and hence test the research hypotheses. The outcomes of SmartPLS path model analysis display that effect of supervisors’ coach on job motivation has indirectly been affected by learning motivation. This outcome explains that the ability of supervisors to appropriately implement coaching in executing daily job operations had strongly invoked employees’ learning motivation. As a result, this motivation could lead to a higher job motivation. Further, this outcome may be used as a useful guideline to assist practitioners in upgrading their understanding of the complexity of learning motivation concept and draw strategic action plans to strengthen managerial coaching in maintaining and enhancing the organisational strategies and objectives in an era of globalisation and knowledge based economy.   Keywords: Supervisors’ coach, learning motivation, work motivation, SmartPLS.
CRYPTOGRAPHIC ALGORITHM USING MATRIX INVERSION AS DATA PROTECTION
Authors: Zirra Peter B. , Wajiga G.M.
Published: August 2020

This study aimed at providing algorithms to secure sensitive information in store or in transit via unsecure channels from the hands of the Internet criminals by scrambling the sensitive information into a set of linear equations in matrix form and deciphering by solving the systems of the linear equations in conjunction with the principles of the delta encoding scheme, a formula and a lookup alphanumeric position table. The algorithms were tested with samples of real data and the result practically demonstrated how systems of non-linear equations turned into linear equations are indeed of relevance in providing strong and complex encryption and decryption keys to protect sensitive information in store or in transit via unsecure channels. The proposed algorithms ensured that unauthorized users do not have access to sensitive and classified documents stored or transmitted to an intended recipient without a secret key. This means that, there is confidentiality, non-repudiation and integrity of our sensitive and classified information from the hands of unauthorized users on the Internet because of the robustness of the proposed algorithms.
VIABILITY OF THE EXTENDED TECHNOLOGY ACCEPTANCE MODEL: AN EMPIRICAL STUDY
Authors: Atiquil Islam Abu Yousuf Mohammed
Published: August 2020

The prime objective of this study is to validate the extended technology acceptance model (ETAM) by incorporating two intrinsic motivation attributes, namely, computer self-efficacy and satisfaction into the original TAM to compare its viability testing on their satisfaction of the wireless internet service at a university. Besides, it evaluates gender invariant of the causal structure of this extended TAM. A total of 285 students from five major faculties (Education, Human Sciences, Engineering, ICT and Economics) were taken as respondents. The questionnaire’s reliability and validity were established through a RASCH analysis. The results as analyzed by Structural Equation Modelling (SEM) indicate that students’ perceived ease of use had a statistically significant effect on their satisfaction. The study revealed that gender did not exert any influence as a moderating variable towards students’ satisfaction in using Wireless Internet. The findings contributed to a better understanding of the TAM and technology satisfaction among students.
SUPPLY CHAIN MANAGEMENT: A SYSTEM DYNAMICS APPROACH TO IMPROVE VISIBILITY AND PERFORMANCE
Authors: Wai Chan Kah , Ang Chooi-Leng
Published: August 2020

Competitiveness is one of the factors successful organizations excel in, and they will do anything necessary to gain an edge over their competitors. The system dynamics approach to simulation modelling is being considered as one of the methods to increase competitiveness. System dynamics is essentially a methodology suited to studying and managing complex feedback systems and provides a means for understanding the causes of industry behaviour. This research builds a complete system dynamics model for internal supply chain events (from order to ship-out) from the perspectives of a semiconductor company. System dynamics models are simulation-based models that allow the investigation and identification of discrepancies between the business policy and the actual practice of key events as well as provide a better visibility of the company’s system. With the understanding of the internal workings of the supply chain system, experiments with the simulation model could provide alternative configurations to achieve better performance. This research utilizes system dynamics to better understand the supply chain system and with it, to find better solutions through experimentations with a few key variables in the supply chain system. The result of this research reveals that the company could achieve 25% reduction in inventory cost should the recommendations be followed.
ASSIGNMENT OF SPECTRUM DEMANDS BY MERITS VIA ANALYTIC HIERARCHY PROCESS AND INTEGER PROGRAMMING
Authors: Ramli Razamin , Jamaluddin Faathirah , Engku Abu Bakar Engku Muhammad Nazri , Alias Mohamad Yusoff , Mahat Nor Idayu , Abdul Karim Mohd Zaini
Published: August 2020

Demand for wireless services is ever increasing due to wireless technology advances, which directly relates to the increasing demand for spectrum bandwidths. Due to the high demand, thus spectrum has become scarce. As a result, spectrum bandwidths have become important and need to be efficiently assigned to potential and demanding service providers. Thus, this paper proposes an integrated approach to solve a spectrum assignment problem. The integrated model is developed to efficiently determine the optimal spectrum assignment for the purpose of satisfying the identified relevant requirements and constraints or criteria. The development of the model has also taken into consideration the situation when the spectrum regulator wishes to choose the best provider or licensee based on merits. For that purpose, suitable weights based on qualitative criteria were obtained via Analytic Hierarchy Process and subsequently used as coefficients in the respective Integer Programming formulation. The integrated optimization model is able to tackle a multi-criteria spectrum problem and then solve the assignment problem by way of maximizing the total efficiency. The results exhibits a more efficient alternative as compared to the existing qualitative approach, as it is able to combine subjective judgments computation with a mathematically formulated approach to produce a systematic and consistent results.
A METRIC-BASED EVALUATION MODEL FOR APPLICATIONS ON MOBILE PHONES
Authors: Hussain Azham , Hashim Nor Laily , Nordin Nazib , Mohamad Tahir Hatim
Published: August 2020

A number of methods and measures have been used by researchers in software evaluation. Usability metrics is one of the approaches that has been used as a guideline to evaluate the quality of the system in many mobile applications. However, the metrics used for evaluation method keep changing due to new inventions of mobile phones. Thus, there is a need to create a dynamic model for evaluation that can grow together with new inventions and technology. In this paper, a dynamic usability metrics model for evaluation of mobile applications was designed. The model comprises usability goals, questions and metrics for evaluation of applications on mobile phones. To ensure that the model is reliable and effective, a usability study was conducted on two applications installed in different mobile phones. This model proves to be applicable for evaluation of mobile phone applications whereby its questions and metrics can be dynamically changed accordingly to comply with the requirements of the evaluators.
ENHANCED ABC-LSSVM FOR ENERGY FUEL PRICE PREDICTION
Authors: Mustaffa Zuriani , Yusof Yuhanis , Kamaruddin Siti Sakira
Published: August 2020

This paper presents an enhanced Artificial Bee Colony (eABC) based on Lévy Probability Distribution (LPD) and conventional mutation. The purposes of enhancement are to enrich the searching behavior of the bees in the search space and prevent premature convergence. Such an approach is used to improve the performance of the original ABC in optimizing the embedded hyper-parameters of Least Squares Support Vector Machines (LSSVM). Later on, a procedure is put forward to serve as a prediction tool to solve prediction task. To evaluate the efficiency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). From the experiment that was conducted, the proposed eABC-LSSVM shows encouraging results in optimizing parameters of interest by producing higher prediction accuracy for employed time series data.
NORMALIZATION OF NOISY TEXTS IN MALAYSIAN ONLINE REVIEWS
Authors: Samsudin Norlela , Puteh Mazidah , Hamdan Abdul Razak , Ahmad Nazri Mohd Zakree
Published: August 2020

The process of gathering useful information from online messages has increased as more and more people use the Internet and other online applications such as Facebook and Twitter to communicate with each other. One of the problems in processing online messages is the high number of noisy texts that exist in these messages. Few studies have shown that the noisy texts decreased the result of text mining activities. On the other hand, very few works have investigated on the patterns of noisy texts that are created by Malaysians. In this study, a common noisy terms list and an artificial abbreviations list were created using specific rules and were utilized to select candidates of correct words for a noisy term. Later, the correct term was selected based on a bi-gram words index. The experiments used online messages that were created by the Malaysians. The result shows that normalization of noisy texts using artificial abbreviations list compliments the use of common noisy texts list.
A GENERALIZED E-LEARNING USAGE BEHAVIOUR MODEL BY DATA MINING TECHNIQUE
Authors: Chayanukro Songsakda , Mahmuddin Massudi , Husni Husniza
Published: August 2020

Current study on e-Learning user’s behaviour model obtained the specific models. In many cases, the e-Learning user’s behaviour model for open source e-Learning system such as Moodle, which can predict learning outcome or learning performance is still defi cient and cannot generally apply in many institutions due to the fact that the majority of prediction models were developed particularly for certain institutions. This study proposes to produce a general model that can make a prediction of learning outcome inspired by Skinner’s theory, which explains the relationship between learner, achievement, and learner reinforcement. This study proposes similar patterns in e-Learning user’s behaviour models of different institutions by the data-mining technique based on the learning environment theory. Therefore, this research is conducted in three main phases; include data preparation from weblog of different institutions with the same e-Learning system, data extraction by the accurate classifi er model fi nding process and model verification for generating a verification pattern. The research outcome will be a similar pattern that could be used as a direction for creating a more appropriate e-Learning users’ behaviour model and could be used broadly in other higher institutions.
PERFORMANCE EVALUATION AND INDICES OF CYBER CAFÉ BUSINESS: A FACTOR ANALYTIC APPROACH
Authors: Adebayo Oluwadare Samuel
Published: August 2020

The advent of the World Wide Web has opened up a new vista of opportunities for investment in the Information Communication Technology (ICT) industry. In recent years, the cyber café business has attracted considerable investment, providing job opportunities for many people. On the other hand, it has also been observed that some hitherto vibrant cyber cafes are also closing down due to the fact that they could not break even. This study, is therefore, aimed at identifying the factors/indices that could enhance the performance of cyber cafes. A total of 250 users of cyber cafes in Akure, Ondo State, Nigeria were randomly selected and a structured questionnaire was administered on them. Data collected was analysed using factor analysis by principal component. The result revealed that four factors, namely quality of hardware, speed of processing, cost, and reliability of service are the major factors that influence users’ patronage. It is therefore recommended that investors and would-be-investors in the cyber cafe business should pay attention to these facors in order to enhance the success of their investment.
G2WAY: A PAIRWISE TEST DATA GENERATION STRATEGY WITH AUTOMATED EXECUTION SUPPORT
Authors: Zamli Kamal Zuhairi , Jamil Klaib Mohammed Fadel , Younis Mohammad Issam , Yeh Ong Hui
Published: August 2020

This paper discusses a new strategy, called G2Way, for pairwise test data generation. Unlike existing strategies, G2Way also supports (concurrent) automated execution integrated within the strategy itself. Furthermore, empirical evidence demonstrates that G2Way, in some cases, outperformed existing strategies in terms of the number of generated test data (as compared to that of AETG and its variations, IPO, SA, GA, ACA, and All Pairs). Notwithstanding the differences in the computing environment employed as well as the overhead incurred to permit automated execution, the test generation time is also within reasonable value.
HYBRID NSGA-II OPTIMIZATION FOR IMPROVING THE THREE-TERM BP NETWORK FOR MULTICLASS CLASSIFICATION PROBLEMS
Authors: Ibrahim Ashraf Osman , Shamsuddin Siti Mariyam , Qasem Sultan Noman
Published: August 2020

Recently, hybrid algorithms have received considerable attention from a number of researchers. This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions. The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems. Furthermore, the results indicate that the proposed hybrid method is a potentially useful classifi er for enhancing the classification process ability when compared with the multiobjective genetic algorithm based on the TBP network (MOGATBP) and certain other methods found in the literature.
AN OBJECT PROPERTIES FILTER FOR MULTI-MODALITY ONTOLOGY SEMANTIC IMAGE RETRIEVAL
Authors: Sulaiman Mohd Suffian , Nordin Sharifalillah , Jamil Nursuriati
Published: August 2020

Ontology is a semantic technology that provides the possible approach to bridge the issue on semantic gap in image retrieval between low-level visual features and high-level human semantic. The semantic gap occurs when there is a discrepancy between the information that is extracted from visual data and the text description. In other words, there is a difference between the computational representation in machine and human natural language. In this paper, an ontology has been utilized to reduce the semantic gap by developing a multi-modality ontology image retrieval with the enhancement of a retrieval mechanism by using the object properties filter. To achieve this, a multi-modality ontology semantic image framework was proposed, comprising of four main components which were resource identification, information extraction, knowledge-based construction and retrieval mechanism. A new approach, namely object properties filter is proposed by customizing the semantic image retrieval algorithm and the graphical user interface to facilitate the user to engage with the machine i.e. computers, in order to enhance the retrieval performance. The experiment results showed that the proposed approach delivered better results compared to the approach that did not use the object properties filter based on probability precision measurement.
iFREEPHONY: MINIMALISTIC INTERFACE DEVELOPED FOR THE VISUALLY IMPAIRED AND THE ELDERLY COMMUNITY IN BANGLADESH
Authors: Ahmed Nova , Nahar Fajilatun , Haque A.M. Masudul
Published: August 2020

Touchscreen-based phones can be challenging for people with visual impairment. These phones require special features to cater to their needs when it comes to a developing country’s perspective like Bangladesh. The interface needs to remain simple as well as it must support the required functionalities. It is often observed that touchscreen phones are not desirable for the user community in Bangladesh as it offers a complex set of functions. We have considered visually impaired personnel in terms of physical limitations and the community who falls in the older age limit as our target community. Our user study has confirmed that the visually impaired user community here asks for a simple and functional interface. We have designed, developed, and deployed a simple system ifreePhony that captures the minimalistic features. We have considered both the elderly and the visually impaired community in our user studies. It shows around 36% reduction in search time and around 57% increase in text typing compared to a traditional phone.
A NEW APPROACH TO HIGHWAY LANE DETECTION BY USING HOUGH TRANSFORM TECHNIQUE
Authors: Aminuddin Nur Shazwani , Mat Ibrahim Masrullizam , Mohd Ali Nursabillilah , Ahmad Radzi Syafeeza , Mohd Saad Wira Hidayat , Darsono Abdul Majid
Published: August 2020

This paper presents the development of a road lane detection algorithm using image processing techniques. This algorithm is developed based on dynamic videos, which are recorded using on-board cameras installed in vehicles for Malaysian highway conditions. The recorded videos are dynamic scenes of the background and the foreground, in which the detection of the objects, presence on the road area such as vehicles and road signs are more challenging caused by interference from background elements such as buildings, trees, road dividers and other related elements or objects. Thus, this algorithm aims to detect the road lanes for three significant parameter operations; vanishing point detection, road width measurements, and Region of Interest (ROI) of the road area, for detection purposes. The techniques used in the algorithm are image enhancement and edges extraction by Sobel filter, and the main technique for lane detection is a Hough Transform. The performance of the algorithm is tested and validated by using three videos of highway scenes in Malaysia with normal weather conditions, raining and a night-time scene, and an additional scene of a sunny rural road area. The video frame rate is 30fps with dimensions of 720p (1280x720) HD pixels. In the final achievement analysis, the test result shows a true positive rate, a TP lane detection  average rate of 0.925 and the capability to be used in the final application implementation.
INTELLIGENT RESPONSIVE INDOOR SYSTEM (IRIS): A POTENTIAL SHOPLIFTER SECURITY ALERT SYSTEM
Authors: Mohd Zahari Mohamad Kuzahier , Zaaba Zarul Fitri
Published: August 2020

Shoplifting can occur at any time and any place. From the big mall to a small shop, many security measures have been put in place as prevention tools. Apparently, there are numbers of shoplifting prevention tools in the market such as the Closedcircuit Television (CCTV), Electronic Article Surveillance (EAS) and Future Attribute Screening Technology (FAST). However, the cost issues and the ease of use always become the main concerns for the shopkeepers. Therefore CCTV was widely accepted because of the ease and affordable price. Although the CCTV is their main preference, it can be noted that CCTV operates in a static way where it can only records and monitor the incidents. This paper highlights the conventional CCTV issues and proposes the Intelligent Responsive Indoor System (IRiS) the as security crime prevention tool that uses face detection, recognition and behavior analysis to detect potential shoplifting intentions. Six small shop owners were interviewed to understand their insights on the problems and the need to further enhance the current CCTV. In addition, detailed discussions were provided in relation to the development of IRiS. Therefore, it can be suggested that IRiS provides a significant foundation and promises to be a security prevention tool to improve the conventional functions of the CCTV.
NEURAL NETWORK TRAINING USING HYBRID PARTICLEMOVE ARTIFICIAL BEE COLONY ALGORITHM FOR PATTERN CLASSIFICATION
Authors: Mahmood Al Nuaimi Zakaria Noor Aldeen , Abdullah Rosni
Published: August 2020

The Artificial Neural Networks Training (ANNT) process is an optimization problem of the weight set which has inspired researchers for a long time. By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks. Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima. Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues. Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. However, hybrid algorithms are also a fundamental concern in the optimization field, which aim to cumulate the advantages of different algorithms into one algorithm. In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application. The performance of the HPABC algorithm was investigated on four benchmark pattern-classification datasets and the results were compared with other algorithms. The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT. HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.
TOWARDS A MATHEMATICAL LIBRARY FOR UNUMs, AN ALTERNATIVE TO IEEE 754 FLOATING POINT NUMBERS
Authors: Risse Thomas
Published: August 2020

The 1985 IEEE 754 standard for the representation of and the arithmetic with floating point numbers has been reconsidered. On the one hand today, its technological assumptions are by no means longer valid. On the other hand, the irritating numerical phenomena which have been collected cast a doubt as to whether this much uncertainty in numerical results is fate. Fortunately, around 2015, Gustafson proposed UNUMs, a modification of the IEEE 754 standard with the potential to heal the said shortcomings. Till now, there are some attempts to implement his ideas, both in software and in hardware. With these activities well under way, the other necessity is development of a mathematical library for UNUMs when one wants UNUMs to become the new floating point standard. This paper presented the ideas leading to UNUMs, gave some hints on floating point units for UNUMs and illustrated the difficulties in developing the said mathematical library by the example of approximating zeroes of analytic functions.
IMPLEMENTATION ANALYSIS OF CUCKOO SEARCH FOR THE BENCHMARK ROSENBROCK AND LEVY TEST FUNCTIONS
Authors: Odili Julius Beneoluchi
Published: August 2020

This paper presents the implementation analysis of the benchmark Rosenbrock and Levy test functions using the Cuckoo Search with emphasis on the effect of the search population and iterations count in the algorithm’s search processes. After many experimental procedures, this study revealed that deploying a population of 10 nests is sufficient to obtain acceptable solutions to the Rosenbrock and Levy test functions (or any similar problem to these test landscapes). In fact, increasing the search population to 25 or more nests was a demerit to the Cuckoo Search as it resulted in increased processing overhead without any improvement in processing outcomes. In terms of the iteration count, it was discovered that the Cuckoo Search could obtain satisfactory results in as little as 100 iterations. The outcome of this study is beneficial to the research community as it helps in facilitating the choice of parameters whenever one is confronted with similar problems.
FRAMEWORK FOR MODELLING MOBILE NETWORK QUALITY OF EXPERIENCE THROUGH BIG DATA ANALYTICS APPROACH
Authors: Yusuf-Asaju Ayisat Wuraola , Md Dahalin Zulkhairi , Ta’a Azman
Published: August 2020

The increase in the usage of different mobile internet applications can cause deterioration in the mobile network performance. Such deterioration often declines the performance of the mobile network services that can influence the mobile Internet user’s experience, which can make the internet users switch between different mobile network operators to get good user experience. In this case, the success of mobile network operators primarily depends on the ability to ensure good quality of experience (QoE), which is a measure of users’ perceived quality of mobile Internet service. Traditionally, QoE is usually examined in laboratory experiments to enable a fixed contextual factor among the participants even though the results derived from these laboratory experiments presented an estimated mean opinion score representing perceived QoE. The use of user experience dataset involving time and location gathered from the mobile network traffic for modelling perceived QoE is still limited in the literature. The mobile Internet user experience dataset involving the time and location constituted in the mobile network can be used by the mobile network operators to make data-driven decisions to deal with disruptions observed in the network performance and provide an optimal solution based on the insights derived from the user experience data. Therefore, this paper proposed a framework for modelling mobile network QoE using the big data analytics approach. The proposed framework describes the process of estimating or predicting perceived QoE based on the datasets obtained or gathered from the mobile network to enable the mobile network operators effectively to manage the network performance and provide the users a satisfactory mobile Internet QoE.
COLLABORATION AND INNOVATION MODELS IN INFORMATION AND COMMUNICATION CREATIVE INDUSTRIES – THE CASE OF GERMANY
Authors: Stejskal Jan , Hajek Petr , Prokop Viktor
Published: August 2020

In rapidly changing environment of global knowledge economy, innovations play an important role in the process of gaining competitive advantage. Specifically, information and communication creative industries are dependent on constant technological breakthroughs, new sources of knowledge and high innovativeness. Moreover, new knowledge and innovation outputs of these industries subsequently affect products and processes of other businesses as well as innovation activities within different industries. Knowledge acquisition, utilization and dissemination therefore represent important processes that significantly influence the firms´ innovation activities. It was proven that cooperation is an important determinant that helps to spread the existing knowledge and to create new knowledge through knowledge spillover effects. The paper deals with the determinants of cooperation and innovation to examine numerous effects on both activities in German information and communication creative industries. We also test the role of the determinants of innovation performance and their influence on the economic effect of innovation activities in terms of the percentage of innovative products in total turnover. For our analyses, we are using data from Community Innovation Survey 2008-2010. We empirically show that firms from German information and communication creative industries can create innovations through the collaboration and confirm that both internal and external communication significantly contribute to the creation of innovation. Moreover, we confirm the influence of internal expenditures on R&D and observe significant influence of external expenditures on R&D. In conclusion, we also provide some practical implications for policy makers.
KNOWLEDGE INTEGRATION AMONG FLOOD DISASTER MANAGEMENT TEAM: LESSONS FROM THE KEMAMAN DISTRICT
Authors: Zakaria Nor Hidayati , Ahmad Mohammad Nazir , Mohd Noor Mohd Saiful Anuar , Ahmad Mazida
Published: August 2020

Although flooding is a common disaster event in Malaysia, issues such as information and knowledge integration still have yet to be resolved. Flood management operations seem to be handled in an ad-hoc manner comprising issues such as miscommunication, lack of common understanding during coordination practices, and lack of smooth mutual agreement among flood management agencies. Thus, this paper discusses the flood knowledge integration measures that have been applied by the flood management team for Kemaman District, Terengganu, the first district achieved a Gold Standard award for flood disaster management in Malaysia. This study comprises a qualitative research method using a variety of techniques. These include a case study approach performed by interviewing key informants as well as studying archival documents. In addition, site visits were made to flood location areas in order to better understand the district’s flood management team’s achievement. The result of knowledge integration practice in preliminary, actual and post-flood phases is discussed in this research. This study shows the importance of knowledge integration as a successful factor for the district’s flood management plan.
PERFORMANCE ANALYSIS OF A REAL-TIME ADAPTIVE PREDICTION ALGORITHM FOR TRAFFIC CONGESTION
Authors: Muhamad Nadeem Khodabacchus , Fowdur Tulsi Pawan
Published: August 2020

Traffic congestion is a major factor to consider in the development of a sustainable urban road network. In the past, several mechanisms have been developed to predict congestion, but few have considered an adaptive real-time congestion prediction. This paper proposes two congestion prediction approaches are created. The approaches choose between five different prediction algorithms using the Root Mean Square Error model selection criterion. The implementation consisted of a Global Positioning System based transmitter connected to an Arduino board with a Global System for Mobile/General Packet Radio Service shield that relays the vehicle’s position to a cloud server. A control station then accesses the vehicle’s position in real-time, computes its speed. Based on the calculated speed, it estimates the congestion level and it applies the prediction algorithms to the congestion level to predict the congestion for future time intervals. The performance of the prediction algorithms was analysed, and it was observed that the proposed schemes provide the best prediction results with a lower Mean Square Error than all other prediction algorithms when compared with the actual traffic congestion states.
TRAFFIC FLOW PREDICTION MODEL BASED ON NEIGHBOURING ROADS USING NEURAL NETWORK AND MULTIPLE REGRESSION
Authors: Priambodo Bagus , Ahmad Azlina
Published: August 2020

Monitoring and understanding traffic congestion seems difficult due to its complex nature. This is because the occurrence of traffic congestion is dynamic and interrelated and it depends on many factors. Traffic congestion can also propagate from one road to neighbouring roads. Recent research shows that there is a spatial correlation between neighbouring roads with different traffic flow pattern on weekdays and on weekends. Previously, prediction of traffic flow propagation was based on day and time during weekdays and on weekends. Results obtained from past studies show that further investigation is needed to reduce errors using a more efficient method. We observed from previous research that similarity of traffic condition on weekdays and weekends was not taken into account in predicting traffic flow propagation. Hence, our study is to create and evaluate a new prediction model for traffic flow propagation at neighbouring roads using similarity of traffic flow pattern on weekdays and weekends to achieve more accurate results. We exploit similarity of traffic flow pattern on weekdays and weekends by adding time cluster in our proposed model. Thus, our neural network model proposed high correlation road, time and day clusters as input factors in neural network model prediction. Our initial phase of the methodology involves investigation on correlation between neighbouring roads. This paper discusses the results of experiments we have conducted to determine relationship between roads in a neighbouring area and to determine input factors for our neural network traffic flow prediction model. To choose a particular road as a predicting factor, we calculated the distance between roads in neighbouring area to identify the nearest road. Then, we calculated correlation based on traffic condition (congestion) between roads in neighbouring area. The results were then used as input factors for prediction of traffic flow. We compared the results of the experiment using neural network without cluster parameters and multiple regression methods. We observed that neural network with time cluster parameter produced better results compared to neural network without parameter and multiple regression method in predicting average speed of vehicles on neighbouring roads.
MEASURING EFFICIENCY OF A UNIVERSITY FACULTY USING A HIERARCHICAL NETWORK DATA ENVELOPMENT ANALYSIS MODEL
Authors: Kashim Rosmaini , Mat Kasim Maznah , Abd Rahman Rosshairy
Published: August 2020

An efficiency measurement model of a university faculty is proposed with additional new sub-functions that produce new output variables, based on the network Data Envelopment Analysis (DEA) model for systems with a hierarchical structure.For production systems composed of hierarchical processes, the system efficiency is well represented as the aggregated performance of the components involved in the system. It is identified that the conventional DEA model ignores internal process activities in a university. Therefore, an improved DEA model based on a network structure that accounts for more activities in a university is proposed to measure its overall efficiency. The impact of major functions of a university are taken into account to represent the output variables in assessing the efficiency. Currently, collaboration activities have been given more attention, so, this variable is suggested as a new output for the hierarchical production system. In order to show the practicality of the model, a hypothetical set of data of 14 faculties has been used as a numerical example. The results show that none of the faculties is relatively efficient since its functions were found to be inefficient. The proposed model enables to help the management of university faculties to identify weaknesses of each function and thus to plan for suitable actions on improving the overall performance of the university.
VIBRANT SEARCH MECHANISM FOR NUMERICAL OPTIMIZATION FUNCTIONS
Authors: Yousef Shambour Moh’d Khaled
Published: August 2020

Recently, various variants of evolutionary algorithms have been offered to optimize the exploration and exploitation abilities of the search mechanism. Some of these variants still suffer from slow convergence rates around the optimal solution. In this paper, a novel heuristic technique is introduced to enhance the search capabilities of an algorithm, focusing on certain search spaces during evolution process. Then, employing a heuristic search mechanism that scans an entire space before determining the desired segment of that search space. The proposed method randomly updates the desired segment by monitoring the algorithm search performance levels on different search space divisions. The effectiveness of the proposed technique is assessed through harmony search algorithm (HSA). The performance of this mechanism is examined with several types of benchmark optimization functions, and the results are compared with those of the classic version and two variants of HSA. The experimental results demonstrate that the proposed technique achieves the lowest values (best results) in 80% of the non-shifted functions, whereas only 33.3% of total experimental cases are achieved within the shifted functions in a total of 30 problem dimensions. In 100 problem dimensions, 100% and 25% of the best results are reported for non-shifted and shifted functions, respectively. The results reveal that the proposed technique is able to orient the search mechanism toward desired segments of search space, which therefore significantly improves the overall search performance of HSA, especially for non-shifted optimization functions.
OPTIMIZATION OF ATTRIBUTE SELECTION MODEL USING BIO-INSPIRED ALGORITHMS
Authors: Basir Mohammad Aizat , Yusof Yuhanis , Hussin Mohamed Saifullah
Published: August 2020

Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis. To date, various feature selection algorithms have been introduced, nevertheless they all work independently. Hence, reducing the consistency of the accuracy rate. The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. This is achieved in two stages; 1) create attribute selection models by combining search method and feature selection algorithms, and 2) determine an optimized attribute set by employing bio-inspired algorithms. Classification performance of the produced attribute set is analyzed based on accuracy and number of selected attributes. Experimental results conducted on six (6) public real datasets reveal that the feature selection model with the implementation of bio-inspired search algorithm consistently performs good classification (i.e higher accuracy with fewer numbers of attributes) on the selected data set. Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction.
WRITE-RITE: ENHANCING HANDWRITING PROFICIENCY OF CHILDREN WITH DYSGRAPHIA
Authors: Rahim Norsafinar , Jamaludin Zulikha
Published: August 2020

Many children have limitations that significantly impact their writing ability, such as physical, cognitive, and motor limitations, all of which need to be overcome for a good level of written expression. This study addresses problems and difficulties in mastering the process of writing among dysgraphic children. The most suitable method to overcome these problems is to provide activities and exercises that can help students improve visual-motor integration that is correlated with writing skills. With this aim in mind, a dysgraphic-customised application called Write-Rite has been designed to support children, through activities and exercises, in order to fulfil their unique needs. This study attempted to design and evaluate Write-Rite application that provides a stimulating and interactive experience for dysgraphic children to practise writing at different levels of difficulties, which could facilitate the learning process. This research was conducted in two primary school in Kedah, where five participants (age seven to twelve) were studied and evaluate for five weeks. Data was compiled by using an observation, recorded handwriting performance and a self-generated rubric to track the following: letter formation, slant, size and proportion, alignment, spacing and line quality. The results of a preliminary evaluation and assessment of “Write-Rite” concluded that this application has justified its role in terms of optimisation in writing proficiency among dysgraphic children.
The Syrian Conflict: Regional Dimensions and Implications
Authors: Kirmanj Sherko
Published: August 2020

The Syrian conflict which started in March 2011 is well into its third year and its dimensions and implications are steadily moving beyond Syrian borders and the broader Middle East. Syria’s uprising has developed into a civil war between government forces and the opposition, motivated primarily by internal and external actors’ strategic and at times existential interests. This article examines the implications and dimensions of the Syrian crisis for the major actors in the region, including Turkey, Iraq, Iran, Lebanon, the Gulf States, Israel and the Kurds. It argues that pitting a Shiite Iran-Iraq-Syria-Hezbollah axis against a Sunni Turkey-Gulf states axis is the most significant geo-political regional effect of the Syrian crisis. What is more devastating is not the division of the region along sectarian lines but the proxy war between the Shiite and Sunni factions.
Foreign Aid to Timor-Leste and the Rise of China
Authors: Talesco Cristian
Published: August 2020

Foreign aid forms an important part of a state’s identity within the international system. The established dichotomy saw developed countries giving aid, while developing countries were receiving it. Nevertheless, China’s ‘rise’, along with that of other ‘emerging economies’, changed such a dualist view; or at least undermined the traditional concept of aid giving. China is becoming a world power, it is the second largest economy, yet it is still within the group of developing countries. However, it provides a considerable amount of foreign aid worldwide. This is destabilizing the established understandings of aid regimes, as set by the Development Assistance Committee (DAC) donors since the 1950s. In particular, the rise of China in Timor-Leste as an important aid contributor, but working outside the leading aid regime, is affecting the most prominent donor in the country, Australia. Moreover, the rapidly growing presence of China in Timor-Leste seems well received by the local government, although criticism arose amongst the population. Thus, this paper attempts to analyse the issue from different levels. Firstly, it will analyse how China managed to “break” the monopoly of Australian aid by accessing Timor-Leste. It will then explicate the principles and the practices of Chinese aid, and will attempt to establish whether Chinese aid has produced a positive economic impact on Timor-Leste and its people. Finally, this paper suggests that Chinese aid is not challenging, neither threatening the Australian aid assistance in Timor-Leste; rather Chinese aid offers an alternative way of giving aid, and which can also convey to Australia with the possibilities of establishing mutual benefits and effective partnerships with the recipient countries.
An Appraisal of ASEAN’s Readiness for Community Formation in December 2015
Authors: Singh D. S. Ranjit
Published: August 2020

The ASEAN Community is expected to be formalized on 31 December 2015. The task of seeing the materialization of the much awaited project has fallen on Malaysia which is currently holding the Chair. The Malaysian team led by the Prime Minister, Dato’ Sri Mohd Najib Tun Abdul Razak is not only making the necessary preparations to host the summit, but is also trying to complete the multitude of uncompleted tasks connected with the integration process. This paper outlines the major milestones that ASEAN has achieved since the organization began to toy with the idea of community formation in 2000 to the present time (October 2015). The paper will then examine the major challenges and shortcomings faced by ASEAN as well as some of the measures crafted by the organization to overcome them.
Regional Integration and Development in Africa: Between the Rock and a Hard Place
Authors: Aworawo Friday
Published: August 2020

Since independence in the late 1950s, and in the early 1960s, regional integration in Africa has been identified as an important strategy for the acceleration of development in the continent. The reality of the Post-Cold War international economic world order also stimulates the intensification and fine-tuning of existing regional arrangements leading to the establishment of a supra-national organization and capacity building institutions to address the problems of underdevelopment in Africa. As a consequence, numerous integration groupings have been reorganized and created but their achievements have largely been modest due to inappropriate integration approaches. It is against this background that this article examines the interlocking nexus between regional integration and development in Africa, and maintains that Africans need to adjust their orientation as well as take a major shift towards economic complementarity among member states of integration blocs for the actualization of laudable development. It concludes that inward looking and the involvement of all Africans in the regional integration processes would be the best approach for regional integration to foster development.