A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network

Recent high-throughput experiments have generated protein-protein interaction data on a genomic scale, yielding the complete protein-protein interaction network for several organisms. Various graph clustering algorithms have been applied to protein interaction networks for detecting protein functional modules. Although the previous algorithms are scalable and robust, their accuracy is still limited because of the complex connectivity found in protein interaction networks. The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. The adapted ACO (ACO-PFMDA) has obtained feasible solution but not as magnificent as those reported in the literature. Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. Experiments on one popular benchmark dataset namely "Saccharomyces cerevisiae" which taken from two popular databases DIP and MIPS has been performed. The experimental result have proved that ACO-PFMDM have improved the overall performance of protein functional module detection. The search process of ACO-PFMDM has converged effectively compared to some state-of-art algorithms. Moreover, the proposed dynamic update of the heuristic parameters based on entropy has generated high quality tours and it can guide ants toward the effective solutions space in the initial search stages

Implementing white hat search engine technique in e-business website

In today’s worldwide of e-business marketing, there are demanded searching engine. Hence, Search Engine Marketing (SEM) with paid and non-paid searching. Data or information about an unknown subject is usually searched for the first page of search engines. The purpose of the research is to analyze, design and develop a domain website using White Hat SEO techniques. The collected data include the website URL, some keywords or keyword groups that define the content of the web site, the code structure that forms the web page and also links provided on the web site. It is important to move a web page to top lists of search engines in order to increase visibility thus getting t h e highest number of visitors. The website published using a chosen platform verified by Google Search Console and tested in Google Search engine. The website achieving high ranking results in Google Search which is in the top three of the first page in Google search. The result obtained shows that the White Hat SEO technique was correctly implemented

Determining of knowledge sharing

Knowledge sharing is the process of transform individual knowledge to organizational knowledge which can helps the organization to get maximum outcomes from the employees.The purpose of conducting this study was to identify the determinants of knowledge sharing in Universiti Sains Malaysia (USM) Penang.132 out of 351 respondents in USM participated in this study. Data has been analyzed by using SPSS software and the results found that three variables i.e. rewards, self-efficacy and shared goals have significant relationship with knowledge sharing. To conclude, emphasizing on the right determinants of knowledge sharing will motivate the employees to share the relevant knowledge with superiors, colleagues and subordinates.Introduction - Recently, knowledge sharing has become the subject that attracts researchers to explore.Knowledge is recognized as useful information to gain competitive advantage and sustainability in organization.Thus, the organization must ensure that knowledge sharing is occurred actively and become a culture which foster on mutual giving and receiving knowledge.The latter of sharing knowledge will be beneficial to the employees and organization in terms of productivity improvement and cost efficiency (Blair, 2002). Knowledge sharing or the contributions by individuals to the collective knowledge of an organization (Cabrera & Cabrera, 2002), is increasingly acknowledged as an important research topic. According to Lu, Leung and Koch (2006), knowledge is often shared among the employees in the organization in various forms and the main objective of sharing knowledge is to transform individual knowledge into organizational knowledge. Knowledge sharing is crucial whereby it is a fundamental root of the organization establishment.There were many research conducted to determine the factors of knowledge sharing in private sectors.However, knowledge sharing interventions in public sectors are lacking of attention (Cong & Pandya, 2003). Furthermore, in public sectors, rewarding employees are subject to government allocation controlled by the federal government.Previous research has discovered many factors that have relationship with knowledge sharing.Gray (2001); Jeon, Kim and Koh (2011); and Kankanhalli, Bernard, and Wei (2005); found that perceived consequences, social factors, facilitating conditions, perceived reputation enhancement,perceived enjoyment in helping others, trust, perceived loss of knowledge power and shared goals lead to the culture of knowledge sharing.Despite variables tested by the mentioned scholars, the researcher came across with other variables to be tested i.e. culture, reciprocal relationship, reward, self-efficacy and shared goals

Comparison of Statistic Prediction Results in Weka Explorer Interface and Experimenter Environment Interface on Dataset

With the increased interest into data mining as an important tool for data processing and analysis, the researchers are concerned into data mining for real decision making, data mining helps in the organizational decision making, inaccurate information can mislead decisionmakers and cause costly errors. With more data collected for analytical purposes. Techniques data mining through Weka Explorer interface and experimental environment interface into determining the prediction and accuracy using different algorithm ratings to know the performance of best. Study confirm is to categorize data and help users mining useful data and easily identify an appropriate algorithm for an accurate predictive model, to access the best-performing algorithms, minimize errors and minimum time to build models through the Explorer interface and Experimental Environment Interface to get accurate

Determinants of knowledge sharing / Roslina Abd Hamid

Knowledge sharing is the process of transform individual knowledge to organizational knowledge (Nonaka, 1994; Foss et al., 2010) which can help the organization to get maximum outcomes from the employees. The study was conducted at Universiti Sains Malaysia (USM) Pulau Pinang. The questionnaires were distributed to 351 respondents from various departments which are Jabatan Pendaftar, Jabatan Bendahari, Jabatan Sains Kaji Hayat each and 51 online surveys were sent to Pusat lnovasi dan Pentadbiran Awam. The complete answered and usable questionnaires were 132. After all the questionnaires was collected, a computer software which was called Statistical Package of Social Science (SPSS) version 22 had been used in order to analyze the data and checked the possible relationships between culture, reciprocal relationship, reward, self-efficacy and shared goals with knowledge sharing among the administration employees. The objective of this study was to study the predictors of knowledge sharing. From the finding, reward, self-efficacy and shared goals have a significant relationship towards knowledge sharing. The administration employees in USM Pulau Pinang feel that reward, self-efficacy and shared goals are the factors that encourage them to share knowledge among them. In conclusion, the organization should focus on rewards, self-efficacy and shared goals to ensure that the employees always motivated to share the knowledge among themselves

Adaptation of Aura Colour Interface Content Presentation based on Learners Emotion in Personal eLearning Environment using Production Rules

Personalization is a suitable approach to adapt the learner to its learning environment.Adaptation for personalization is based on modality and affective aspects of the learner. Most research into adaptation is focusing on modality aspect, thus adaptation in affective aspect is crucial to be explored. This innovative prototype namely, EmoAPeL was developed to adapt the aura colour interface content presentation based on learner’s emotion in Personal e-Learning Environment using an intelligent production rule. EmoAPeL has been tested to 30 Universiti Malaysia Pahang students. The mean results show 88.5% of the students agreed that EmoAPeL motivates their inclusive learning environment. EmoAPeL development concept can be embedded to any eLearning systems

A Novel Approach to Explore Edhi Foundation Knowledge for Ontology Construction

The worth of the Edhi Foundation (EF) system depends on how well its structural knowledge can be extracted by EF users and staff to perform daily activities. Ontology has emerged as a semantic tool to represent the knowledge of a particular domain and thus is a good choice for the semantic organization of EF data. However, building an ontology that suits the needs of EF users is a challenging task. This study presents a novel approach that uses the UML class diagram (UCD) to construct an ontology for the EF system. We propose UCD-to-ontology transformation rules, that is, the ontology model that is used for eliciting OWL ontology. We test our approach for the successful interpretation of UCD features to OWL ontology elements and find that the system performs well with an average precision of 97.80%

Learning Space Quality Monitoring: Sensing the Unseen Factor

Providing the best infrastructure for learning in university is the most important job. Administrator tends to look after the physical infrastructure rather than unseen matters. Recently, no device or scheme available to detect and prevent with monitoring the learning space quality. 150 students from multiple courses had participated in the learning investigations. The sites for investigations are the lecture hall, computer laboratory, and library. In the same investigations, we activate the HeDoo devices which detecting air particles which theoretically affect the quality of learning. Even though the site looks cozy and breathable, it showed students have a problem, especially in knowledge understanding, memorizing, and focusing. The three unseen major factors influencing the learning quality are humidity (95%), temperature (93%), and carbon dioxide (92%). This finding is beneficial to educational infrastructure planning and may provide a good outcome on students’ performance. Further analysis will be run especially on minor factors

Increasing Data Anonymity using AES and Privacy Technique

Data security and data preserve privacy had been an important area to a huge in recent years. However, rapid developments in collecting, analyzing, and using personal data had made privacy a very important issue. This thesis had addressed the problem the protect user data in the dataset from attacks internal and attacks external by using combination techniques between security technique, and privacy techniqueand data mining technique. The research objectives were to determine the privacy and security technique in suitable the dataset, and to implement the combination property with chosen and security technique in order to protect user data in the dataset and to validate by comparing result before and after apply privacy techniques in dataset using chosen data mining tool. The research methodology consists of three phases. the analysis phase, combination techniques phase, and results evaluating phase and for every phase has research objective