{"title":"An insight on survey questionnaire design for Green SCM: Using cognitive interviewing method","authors":"K. Savita, P. Dominic, Thurasamy Ramayah","doi":"10.1109/ICCOINS.2016.7783296","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783296","url":null,"abstract":"This paper features cognitive interviewing method adopted in the pre-test study along with operational definition of the research variables adapted in the study. The findings from cognitive interviews contributed as part of the psychometric testing in improving the survey questionnaire design and content. The cognitive interviews were conducted with five managers from ISO 14001 manufacturing firms in Malaysia. These firms are selected based on purposive sampling method since the ISO 14001 certified firms are in the best position to provide the required information since the adoption and implementation of green practices in their operations are expected. The evidences showed that some participants face difficulty the grasping certain terminology and phase, therefore the interpretation of the questions may vary. Whilst, others face difficulty to comprehend, retrieve and response to the items since the coverage of the content are broad in nature as it focuses on supply chains, information technologies and systems as well as performance. In addition, the participants provide value feedback on the content, format of questionnaire, language, instructions, length as well as response options and scale. The identified issues were clarified and revised in producing the enhanced survey questionnaire for actual data gathering among ISO14001 Manufacturing firms in Malaysia.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128409077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Droopy Mouth Detection Model in stroke warning","authors":"O. Foong, K. Hong, S. Yong","doi":"10.1109/ICCOINS.2016.7783286","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783286","url":null,"abstract":"This paper presents a Droopy Mouth Detection Model in stroke warning. The objective of this paper is to take up the challenge to provide early detection of stroke through mouth drooping detection in mobile Android platform. To achieve that, a specialized library, Google Mobile Vision is utilized to detect facial landmark such as mouth corners and obtain the coordinates of the landmarks or key points for further processing. The inputs for the proposed droopy mouth detection model were taken from the Google Web Images and National Cheng Kung University (NCKU) Robotics Face datasets. The system prototype was evaluated using metrics such as Precision, Recall and F-Score to determine its recognition rate. Experimental results show that the proposed droopy mouth detection model has achieved satisfactory recognition rate.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132082289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigating requirement engineering techniques in the context of small and medium software enterprises","authors":"Souhaib Besrour, Lukman Bin Ab Rahim, P. Dominic","doi":"10.1109/ICCOINS.2016.7783269","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783269","url":null,"abstract":"Numerous requirement techniques have been proposed in the last decade in order to reduce requirement engineering challenges. However, Large number of requirement engineering techniques causes confusion while technique selection process. Thus, there is a need to investigate requirement techniques. To address this objective, techniques have been studied in the last two decade between the years 1995 and 2016 using systematic literature review (SLR) to explore other studies findings and results. A total of 15 techniques has been specified in the context of requirement engineering. Additionally, identified techniques have been further investigated using quantitative study through small and medium software enterprises. Where a total of 250 surveys have been collected, after eliminating incomplete surveys 217 completed surveys used for data analysis. Concluding results show that out of 15 techniques, 12 techniques have been rated as supported. Lastly identified techniques aim to benefit software enterprises particularly new enterprises to have a better understanding about techniques support level in the context of requirement engineering.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115254122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimization of sensor deployment in data center","authors":"L. T. Jung, O. Foong, Pramita Winata","doi":"10.1109/ICCOINS.2016.7783291","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783291","url":null,"abstract":"The demand for data center (DC) has been increasing significantly due to the rapid growth in ICT technology. This brings along the “green” issues in data center such as energy consumption, heat generation and cooling requirements. These issues can be addressed by “Green of/by IT” approach in the context of operating costs as well as the environmental impacts. To install temperature monitoring system in every corner of data center is certainly cost inefficient. Optimizing the number of sensors deployed in DC is thus important for reducing the monitoring cost. This project aims to create a wireless temperature monitoring system with an optimizing technique to optimize the number of temperature sensors deployed in a DC. The real-time temperature data collected by this system can also be used to predict the next state of the temperature in DC to detect potential anomaly in heat generation. Quick preventive response can thus be invoked to manage this potential hot spots in DC. This could be a promising green by IT approach.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122467693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vala Ali Rohani, Shahid Shayaa, Ghazaleh Babanejaddehaki
{"title":"Topic modeling for social media content: A practical approach","authors":"Vala Ali Rohani, Shahid Shayaa, Ghazaleh Babanejaddehaki","doi":"10.1109/ICCOINS.2016.7783248","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783248","url":null,"abstract":"Perceiving the discussed topic in social media brings a great amount of value to different fields, such as marketing, security, education, and management. Topic modeling provides a powerful method for projecting text documents into topic space. In this paper, we explore an unsupervised topic modeling approach that incorporates LDA algorithm toward discovering the topics in social media content. Empirical experiments on social media datasets with 90,527 records reveal that this approach is quite effective for detecting the topic facets and extracting their dynamics over time. By analyzing the studied dataset, five main topics were discovered accurately by the presented algorithm according to the domain experts' comments. The presented model is quite general and can be applied in a wide variety of domains to automatically mining topics from the social media channels.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132819728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Big data: Performance profiling of Meteorological and Oceanographic data on Hive","authors":"A. Abdullahi, R. Ahmad, Nordin Zakaria","doi":"10.1109/ICCOINS.2016.7783215","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783215","url":null,"abstract":"The emergence and development of big data tools, techniques and systems motivate industries and organizations to embrace and explore research in big data. This is to circumvent the challenges of the traditional database systems. However, the available benchmarks and workloads are for some specific aspect of Information Technology industries, which has differences in nature and complexities with the data obtained from other sources. Hence there is need for using data from other domains in order to evaluate the performance and maturity of the big data technologies. In this paper the performance profiling of Meteorological and Oceanographic data on Hive is conducted. Hive being the commonly used data warehouse analytical platform for big data is chosen with the view to exposing the intricacies that are involved in the formating and loading of the data. The response time for indexed and non-indexed retrievals using three set of queries frequently used in the area is found. The query types are Type 1 SELECT with WHERE clause, Type 2 SELECT with JOIN clause. And Type 3 SELECT with GROUP BY clause. The experimental results show that a good response time for both indexed and Non-indexed tables are achieved. The indexed retrieval shows a significant decrease in the response time for Type 1 query for all data sizes and for Type 3 query for 100GB data size and less . It also shows additional overhead for Type 2 query for all data sizes and Type 3 query for 500GB and more data sizes. The Meteorological and Oceanographic data if properly formated it's analytics with Hive proved to be efficient compared to the traditional database systems. The results of this study has the potentials of attracting the oil and gas companies to adopt big data technologies for the handling of their exploration dataset.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"344 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132233958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A comparison of deep learning and hand crafted features in medical image modality classification","authors":"S. Khan, S. Yong","doi":"10.1109/ICCOINS.2016.7783289","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783289","url":null,"abstract":"Modality corresponding to medical images is a vital filter in medical image retrieval systems, as radiologists or physicians are interested in only one of radiology images e.g CT scan, MRI, X-ray. Various handcrafted feature schemes have been proposed for medical image modality classification. On the other hand not enough attempts have been made for deep learned feature extraction. A comparative evaluation of both handcrafted and deep learned features for medical image modality classification is presented in this paper. The experiments are performed on IMAGECLEF 2012 data. After carrying out the experiments it is shown that the handcrafted features outperforms the deep learned features and shows the potential of handcrafted feature extraction models in the medical image field.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115774530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An efficient distributed mobility management scheme for network mobility","authors":"A. Wagan, L. T. Jung","doi":"10.1109/ICCOINS.2016.7783226","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783226","url":null,"abstract":"Network Mobility (NEMO) is a technology that enables internet services in the public transportation and personal network. To facilitate the internet service in an ongoing vehicle a mobility management protocol shall play a key role. Mobility management is basically responsible for two tasks; node location update of node and service delivery. Present mobility management protocols are incurred with two key issues. First is centralized entity, the central entity provides all intelligence and is responsible for handover process. Therefore, if this entity is fails due to over burden traffic; the whole network is going to suffer. The second issue is related to mobile router; which is frequently moving from one point to another (router visited foreign network). Due to frequently changes in its point of attachment all the running applications will be terminated (session breakup). Therefore; this research work has two objectives. The first objective is to present distributed mobility management architecture to mitigate the central entity issue and the second is to design a handover communication scheme to reduce the long interval, when router changes its point of attachment. Furthermore, an analytical model is developed to analyze the performance of the proposed communication scheme.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134542821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. E. Nyamasvisva, H. Hasbullah, N. Yahya, Yunus Nayan, A. Rostami, Muhammad Rauf
{"title":"Computer algorithm for airwave prediction in marine controlled source electromagnetics data","authors":"T. E. Nyamasvisva, H. Hasbullah, N. Yahya, Yunus Nayan, A. Rostami, Muhammad Rauf","doi":"10.1109/ICCOINS.2016.7783246","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783246","url":null,"abstract":"This paper presents a methodology for quantifying airwaves as a noise component in Sea Bed Logging environment. Sea bed logging is an application of marine controlled source electromagnetic sounding applied for mainly offshore hydrocarbon detection in the subsurface. The basis of the approach is the difference in resistivity values of matter which comprise the subsurface and the overlying layers. A mobile electric dipole emits a low frequency electromagnetic signal both into the overlying water column and downwards into the seabed. An array of sea floor receivers measures both the amplitude and the phase of the received signal that depend on the resistivity structure beneath the seabed. A survey consisting of many transmitter and receiver locations can be used to determine a multidimensional model of subsea floor resistivity. The received signal is a composition of many signal which are multiplexed to form a complex signal. This signal consists of wanted and unwanted data of which the technique described in here separates the unwanted air waves from the wanted. A mathematical model to quantify the amount of airwave at any given sea water depth from a defined offset is proposed. The method described here has managed to eliminate more than 99.5 percent of the airwave noise from shallow water deep target environment data. Data used was collected from a simulated model of offset 50Km, and cross sectional depth of 10km of which 6km makes the subsurface.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133425360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Managing knowledge over social messaging application: The case of an event management project group","authors":"S. Ismail, N. Jamaludin","doi":"10.1109/ICCOINS.2016.7783184","DOIUrl":"https://doi.org/10.1109/ICCOINS.2016.7783184","url":null,"abstract":"Recent research looks into how social messaging (SM) is used to manage the knowledge among managers, and how this leads to decision making in management team. Despite the numerous articles found on SM, which mostly referred to instant messaging (IM), only a few covered the usage of SM for managing knowledge at workplace. The current observation on the changing technology usage trend in managing tasks and knowledge has found that SM applications (i.e. over mobile phones) are heavily used to make important decisions on-the-go. This results to the addiction of creating new SM groups every time a new team or special task force is formed, to ensure constant communication among the team members and to solve issues immediately. Since the concept of knowledge management (KM) is deem relevant to the process of making decisions regarding official work, it is believed that there is a need to investigate the communication patterns in the SM group environment and identify the KM patterns that emerge from these. This paper uses the GUSC Model, established under the concept of personal knowledge management (PKM), as a tool to analyse these patterns, focusing on a sample group of a special task force formed for an important event. It further proves the existence of KM patterns among members of a social messaging group.","PeriodicalId":224429,"journal":{"name":"2016 3rd International Conference on Computer and Information Sciences (ICCOINS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115503725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}