Predicting with sparse data

It is well known that effective prediction of project cost related factors is an important aspect of software engineering. Unfortunately, despite extensive research over more than 30 years, this remains a significant problem for many practitioners. A major obstacle is the absence of reliable and systematic historic data, yet this is a sine qua non for almost all proposed methods: statistical, machine learning or calibration of existing models. In this paper we describe our sparse data method (SDM) based upon a pairwise comparison technique and Saaty's Analytic Hierarchy Process (AHP). Our minimum data requirement is a single known point. The technique is supported by a software tool known as DataSalvage. We show, for data from two companies, how our approach — based upon expert judgement — adds value to expert judgement by producing significantly more accurate and less biased results. A sensitivity analysis shows that our approach is robust to pairwise comparison errors. We then describe the results of a small usability trial with a practising project manager. From this empirical work we conclude that the technique is promising and may help overcome some of the present barriers to effective project prediction

Highway sustainability construction: reducing carbon emissions using process management.

Carbon emission is a critical issue in infrastructure development, including the highway construction industry. Previous studies suggest that continuous carbon emission across highway projects is due to the use of different types of construction equipment and their inherent activities. Several research studies focused on arbitrary evaluation in order to reduce carbon emission using simulation, life-cycle analysis and multi-criteria optimisation. However, the general lack of methodological rigour brings into question the effectiveness of these carbon reduction methods. In addition, some of these studies do not show suitable improvement in carbon reduction and some of the findings are restricted in their usability. The present study aims to develop an integrated technique and a better understanding for the use of process management in reducing carbon emissions from highway construction projects. The study uses the literature review as the basis for its enquiry, enabling the use of secondary information as inputs to the analytical hierarchy process. The result shows that 'Strategy' has the highest weight score. The pattern of results indicates that a new paradigm shift is required in the use of strategic process management approaches in highway carbon reduction. Two contributions are made: firstly, the recommendation for early decision-making in order to include carbon reduction strategy during the highway feasibility study and tender phases. Secondly, the recommendation to use the proposed strategic process management framework in determining realistic carbon reduction strategies across the highway construction sector

Meja kopi modular untuk rumah minimalis moden

Peningkatan populasi di seluruh dunia adalah sangat tinggi. Di Malaysia, kadar pertumbuhan populasi rakyat Malaysia meningkat kepada 1.1% iaitu sebanyak 32.4 bilion (2018) berbanding 31.1 bilion (2015) (Mahidin, 2019). Peningkatan populasi ini meningkatkan permintaan dan bekalan terhadap keperluan asasi seperti makanan, pakaian, peluang pekerjaan dan juga ruang kediaman. Ini turut mempengaruhi reka bentuk dan saiz kediaman bagi menempatkan kesemua rakyat Malaysia dan juga pekerja asing yang berkerja di negara ini. Menurut Harian Metro Online, tanah yang semakin berkurangan menyebabkan unit kediaman sekarang banyak dibina dengan keluasan yang terhad antara 650 hingga 800 kaki persegi (Satibi, 2018). Justeru, pemilihan perabot memainkan peranan penting dalam usaha untuk menampakkan kediaman lebih luas dan selesa (Ismail, 2020)

Evaluating and benchmarking non-governmental training programs: an analytic hierarchy approach

This study uses Analytic Hierarchy Process (AHP) as a multi-criteria decision making technique for evaluating training programs. Critical factors characterizing successful training programs are first identified using interviews with experts along with questionnaires. Once the factors were identified, the hierarchy was constructed and the factors were ranked according to their importance with respect to achieving the overall goal set for training. Results show that, of these critical factors, content and trainer rank the highest, while logistics came last. Then, two existing non-governmental training programs are selected, evaluated, and compared. Moreover, and as requested by one of the administrations of one of the evaluated programs, a benchmarking alternative is derived based on the results of the two training programs. Finally, recommendations are given to each of these programs in particular and training programs in general, for possible areas of improvements based on the strengths and weaknesses of each program as compared to the benchmark

Intelligent multimedia transmission for back pain treatment

Copyright @ 2002 EUNITERemote, multimedia-based, collaboration in back pain treatment is an option which only recently has come to the attention of clinicians and IT providers. The take up of such applications will inevitably depend on their ability to produce an acceptable level of service over congested and unreliable public networks However, although the problem of multimedia application-level performance is closely linked to both the user perspective of the experience as well as to the service provided by the underlying network, it is rarely studied from an integrated viewpoint. To alleviate this problem in the context of a multimedia application, a method is proposed in this paper for obtaining a priority order of low-level Quality of Service parameters, which would ensure that user-level Quality of Perception is maintained at an optimum level. Thus we present an approach that integrates technical concerns with user perceptual considerations for intelligent decision-making in the construction of tailor-made multimedia communication protocols. The proposed approach, based on multicriteria decision making, incorporates not only classical networking considerations, but, indeed, user preferences as well. Moreover, our approach also opens the possibility for such protocols to dynamically adapt based on a changing operating environment and user preferences

A fuzzy ANP application for prioritizing the productivity factors based on university employees' counterproductive behaviors

Measuring the relative efficiency of employee plays essential role on the success of any organization including universities. In this paper, we present a survey to detect and to prioritize important factors influencing on the productivity of employees who work for one of Iranian universities located in city of Tehran, Iran. The study also uses analytical network process to prioritize the factors. Based on the results of our survey, we have categorized effective productivity factors into three groups of research, educational and administration groups. In our survey, coherence and unity with no dispersion of the employee's duties, systematic job rotation and correct design communication job are among the most important factors influencing on employees’ productivity

A Framework for BPM Software Selection in Relation to Digital Transformation Drivers

Business process management (BPM) is nowadays almost a traditional paradigm of assuring operational excellence. Within emerging approaches for boosting organizational readiness and maturity to cope with digital challenges, BPM transforms as well. In order to investigate the role of BPM and BPM software (BPMS) in relation to these approaches we explore drivers of digital transformation (DT). Based on the mapping of BPMS dimensions and drivers of DT, we propose a framework for self-assessment which allows evaluation of the significance of BPMS dimension in relation to DT. The framework was tested on multiple case-studies to analyse what their BPMS priorities are and how these priorities influence their digital transformation. AHP analysis was performed by prioritizing BPM\u27s dimensions mapped with DT drivers and it served as a basis for assessing the level of digital maturity of the observed companies. This article therefore deals with the following: (1) it briefly discusses BPM and DT as concepts, (2) it demonstrates how AHP can serve for selecting BPM software and (3) it shows that BPM dimensions can be linked to Digital Transformation