ANALISIS KONSEP ARSITEKTUR PERILAKU PADA DESAIN STUDY CAFE DAN CO-WORKING SPACE DI KOTA SEMARANG

Seiring  perkembangan  zaman, masyarakat ikut mengalami perkembangan gaya pola bekerja dan belajar mereka, saat ini masyarakat lebih menyukai ruang publik yang lebih fleksibel dan nyaman seperti café, dikarenakan rumah maupun kosmemiliki ruang dan fasilitas terbatas dan situasiyang kurang kondusif. Di Semarang khususnya di Kecamatan Ngaliyan masih terbilang kurang akan fasilitas study space maupun work space. Sehingga banyak pelajar, mahasiswa, maupun freelancer yang mencari alternatif tempat untuk mengerjakan tugas maupun pekerjaan mereka, dengan memanfaatkan restaurant fast food yang bukan sebuah sarana untuk memfasilitasi kegiatan tersebut, sehingga perencanaan study café dan co-working space merupakan solusi inovatif untuk mewadahi aktivitas belajar maupun bekerja mahasiswa, pelajar, maupun freelanacer. Dengan menggunakan pendekatan arsitektur perilaku, untuk memaksimalkan fungsi serta guna bangunan agar tepat perencanaan, sehat, aman, nyaman, ramah pengguna khususnya bagi wanita maupun penyandang disabilitas selama 24 jam. dengan memperhatikan kebutuhan, kebiasaan, dan tingkat kenyamanan pengguna

Shifting Home Energy Consumption Through a Holistic Understanding of the Home System of Practice

This chapter describes the concept of the home system of practice, which can be used to provide a deeper understanding of the social system of the home and inform long-term solutions for enabling domestic energy reduction. More traditional methods have attempted to persuade occupants to change behaviour through the use of information campaigns and feedback technology. However, these interventions are usually short lived as they ignore the underlying reasons for practices to occur. A more effective solution is through practice-oriented design, which co-creates innovative technology with the user. In addition, the emergence and use of automated technology enables practices to act independently of the user. Yet, the success of automation is also reliant on an understanding of the home system of practice, occupant needs and skills

Case-based reasoning using expert systems to determine electricity reduction in residential buildings

Case-based reasoning enables solving new problems using past experience, by reusing solutions for past problems. The simplicity of this technique has made it very popular in several domains. However, the use of this type of approach to support decisions in the power and energy domain is still rather unexplored, especially regarding the flexibility of consumption in buildings in response to recent environmental concerns and consequent governmental policies that envisage the increase of energy efficiency. In order to determine the amount of consumption reduction that should be applied in a building, this article proposes a methodology that adapts the past results of similar cases in order to achieve a decision for the new case. A clustering methodology is used to identify the most similar previous cases, and an expert system is developed to refine the final solution after the combination of the similar cases results. The proposed CBR methodology is evaluated using a set of real data from a residential building. Results prove the advantages of the proposed methodology, demonstrating its applicability to enhance house energy management systems by determining the amount of reduction that should be applied in each moment, thus allowing such systems to carry out the reduction through the different loads of the building.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and a grant agreement No 703689 (project ADAPT); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013info:eu-repo/semantics/publishedVersio

Suggestions for improving the effectiveness of environmental education in the maritime sector

Research shows that many barriers to pro-environmental behaviour in the maritime industry exist despite significant efforts of various stakeholders, and there is a need to put additional efforts to improve the sustainability of shipping. Education has an important role because a lack of environmental knowledge is almost always identified as a barrier to environmental concern and behaviour. However, eliminating knowledge gaps and raising concern does not necessarily translate to behaviour change, because behaviour depends on numerous factors, which moderate and mediate one another. Effectiveness of education activities may be improved if potential barriers are identified and targeted. This paper reviews determinants of pro-environmental behaviour and provides some suggestions for educators to plan and execute educational activities to increase the willingness of seafarers and shore-based personnel to adopt environmentally-friendly practices

Starting a New Midcareer Librarian Position During COVID-19: Lessons to take into the future

This article chronicles the experience of two midcareer librarians who were new hires at the University of South Florida one month before the entire campus was sent to work from home due to the COVID-19 pandemic. They recount the obstacles encountered and how they overcame them. They include lessons learned and ways to improve a transition to remote working. Specific areas that are discussed: technology, training, communication, self-advocacy, relationship building, and mentorship

Hybrid data driven/thermal simulation model for comfort assessment

Machine learning models improve the speed and quality of physical models. However, they require a large amount of data, which is often difficult and costly to acquire. Predicting thermal comfort, for example, requires a controlled environment, with participants presenting various characteristics (age, gender, ...). This paper proposes a method for hybridizing real data with simulated data for thermal comfort prediction. The simulations are performed using Modelica Language. A benchmarking study is realized to compare different machine learning methods. Obtained results look promising with an F1 score of 0.999 obtained using the random forest model