Stabilisation of clay subgrade soils using ground granulated blastfurnace slag

Roads constructed on expansive clays may be adversely affected by the behaviour of the clay. Expansive clays suffer volume change due to changes in moisture content which causes heaving, cracking and the break up of the road pavement. Stabilisation of these types of soil is necessary to suppress swelling and increase the strength of the soil and thus partially decrease the thickness of road pavement layers. The use of by-product materials for stabilisation has environmental and economic benefits. Ground granulated blastfurnace slag (GGBS), a by-product material in Egypt, and lime are used in the current work to stabilise samples of a clay soil similar to a typical Egyptian clay soil. This test soil comprises 80% River Aire soil and 20% calcium montmorillonite. The main objectives of this research were to investigate the effect of GGBS, with and without lime, on the engineering behaviour (plasticity characteristics, compaction, unconfined compressive strength (UCS) and swelling potential) of the test soil and to identify the reaction products of the stabilised materials to determine the mechanisms by which changes in engineering properties are obtained. In order to achieve these objectives, extensive laboratory investigations were carried out. Various mixes (up to 10% GGBS by dry weight of the test soil and up to 30% replacement by hydrated lime) were prepared and cured under two representative conditions {20°C with 90-100% relative humidity (CCI) and 35° C with 50-60% relative humidity (CC2)} for up to 12 months. Compaction and plasticity were measured soon after mixing, the swelling potential and UCS were measured after longer curing periods. Four analytical techniques {X ray diffraction, scanning electron microscopy, differential thermal analysis and nuclear magnetic resonance (NMR)} were used to identify the reaction products of the clay fraction of the test soil mixed with various amount of GGBS and lime. This pure clay test soil was used to ease identification of the reaction products. The investigations showed that generally the engineering properties (UCS, swelling, plasticity) improved with the addition of GGBS and with increasing curing period and temperature. The addition of lime resulted in a dramatic improvement within the test ranges covered in the programme. The maximum dry density, MDD, decreased and the optimum moisture content, OMC, increased with increasing GGBS and lime content. The major changes in the UCS and swelling behaviour are due to the formation of new cementitious materials. The analytical investigation confirmed two major reactions when GGBS and lime were added to the pure clay soil, hydration of GGBS activated by lime to produce calcium aluminosilicate hydrate gel (C-A-S-H) and hydrotalcite type phase, and the clay-lime reaction to produce calcium silicate hydrate (C-S-H), (C-A-H) and (C-A-S-H). The NMR test results revealed that the aluminosilicate chain length (EL), the aluminium: silicate (Al/Si) ratio and the amount of Si in the formed C-S-H significantly increased with an increase in the curing temperature and period, which indicates a more stable and well crystalline C-S-H. The results indicate that the use of GGBS alone, or preferably with lime, could have a significant effect on the behaviour of potentially swelling clays. Recommendations for further studies include a study of the effect of cyclic loading on the test soil. Also, site trials should be carried out to assess the suitability of using these materials in the field

Generating design-sensitive occupant-related schedules for building performance simulations

Despite the benefits of occupant behavior (OB) models in simulating the effect of design factors on OB, there are challenges associated with their use in the building simulation industry due to extensive time and computational requirements. To this end, we present a novel method to incorporate these models in building performance simulations (BPS) as design-sensitive schedules. Over 2,900 design alternatives of an office were generated by varying orientation, window to wall ratio (WWR), the optical characteristics of windows and blinds, as well as indoor surfaces’ reflectance. By using daylight simulations and stochastic OB modeling, unique light use schedules were generated for each design alternative. A decision tree was then developed to be used by building designers to select light use schedules based on design parameters. These findings are relevant for building energy codes as they provide an approach to incorporate design-sensitive operational schedules for use as BPS inputs by practitioners. These design-sensitive schedules are expected to be superior to default ones currently specified in codes and standards, which ignore the effect of design factors on OB, and ultimately on energy consumption

Anti-cancer, Anti-inflammatory, Cytotoxic and Biochemical Activities of a Novel Phosphonotripeptide Synthesized from Formyl Pyrazolofuran using TUBU as Condensing Agent

A novel and mild protocol for the synthesis of phosphonotripeptide 16 were achieved from novel formylpyrazolofuran 3, benzyl carbamate 5, triphenyl phosphite 6 by Birum-Oleksyszyn reaction using copper (II) trifliate as Lewis acid catalyst in dry dichloromethane at room temperature which synthesis of novel N-benzyloxy-α-aminophosphonate 7 . A mechanism for this condensation reaction is proposed. Cleavage of the N-benzyloxy carbonyl group under acid hydrolysis afford the free α-aminophosphonate 9 in quantitative yield. This in turn, by reaction with N-phthaloylglycine 12 via TUBU to phthalimido group 13.Cleavage of phthalimido group under hydrazinedihydrochloride afford free peptide 14 .the result phosphonotripeptide 16 obtained by the reaction of free peptide with bioactive cyclic moiety-COCl 15. The structures of all new compounds were established by IR,1HNMR and mass spectral data. Also anti-cancer, anti-inflammatory  and biochemical activities of all these compounds were reported

Usability and comfort in Canadian offices: Interview of 170 university employees

Increasing building automation to improve energy efficiency introduces a risk of reducing occupants' perceived control and overall comfort. To this end, this paper presents a field study that used contextual techniques to explore the relationship between occupants' perceived control and comfort, as well as their preferences for building automation. A total of 170 occupants in 23 Canadian university campus buildings were interviewed in their offices using semi-structured interviews. All interviews entailed verbally administering a survey while photographs were systematically used to identify the context of occupants' interactions with building controls. Findings revealed that occupants' perception of comfort was moderately correlated to their perception of control over their indoor environment. Occupants also showed an overwhelming preference for more control opportunities in their offices (e.g. operable windows and dimmable lighting controls). Conducting interviews in offices yielded many interesting anecdotes and enabled the researcher to identify contextual issues related to building controls' accessibility, which may have been unnoticed otherwise. The findings of this research contribute to a broader debate within the research community about the appropriate level of building automation to optimize energy efficiency and occupant comfort

Key Performance Indicators Detection Based Data Mining

One of the most prosperous domains that Data mining accomplished a great progress is Food Security and safety. Some of Data mining techniques studies applied several machine learning algorithms to enhance and traceability of food supply chain safety procedures and some of them applying machine learning methodologies with several feature selection methods for detecting and predicting the most significant key performance indicators affect food safety. In this research we proposed an adaptive data mining model applying nine machine learning algorithms (Naive Bayes, Bayes Net Key -Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), J48, Hoeffding tree, Logistic Model Tree) with feature selection wrapper methods (forward and backward techniques) for detecting food deterioration’s key performance indicators. In conclusion the proposed model applied effectively and successfully detected the most significant indicators for meat safety and quality with the aim of helping farmers and suppliers for being sure of delivering safety meat for consumer and diminishing the cost of monitoring meat safety

Risk Assessment Approaches in Banking Sector –A Survey

Prediction analysis is a method that makes predictions based on the data currently available. Bank loans come with a lot of risks to both the bank and the borrowers. One of the most exciting and important areas of research is data mining, which aims to extract information from vast amounts of accumulated data sets. The loan process is one of the key processes for the banking industry, and this paper examines various prior studies that used data mining techniques to extract all served entities and attributes necessary for analytical purposes, categorize these attributes, and forecast the future of their business using historical data, using a model, banks\u27 business, and strategic goals

Credit Card Fraud Detection Using Machine Learning Techniques

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today\u27s banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary losses, not just for financial institutions but also for individuals. as technology and usage patterns evolve, making credit card fraud detection a particularly difficult task. Traditional statistical approaches for identifying credit card fraud take much more time, and the result accuracy cannot be guaranteed. Machine learning algorithms have been widely employed in the detection of credit card fraud. The main goal of this review intends to present the previous research studies accomplished on Credit Card Fraud Detection (CCFD), and how they dealt with this problem by using different machine learning techniques

Eyes on the Goal! Exploring Interactive Artistic Real-Time Energy Interfaces for Target-Specific Actions in the Built Environment

Current research is focused on sensing and modeling occupant behavior to predict it and automate building controls. Another line of research recommends influencing the behavior of occupants through feedback mechanisms and engagement. Yet, most of the work has focused on pushing occupants to reduce energy consumption over a long time and does not explore the potential to guide users to take specific actions promptly. The study examines a new interface mechanism that aims to solicit immediate and predefined actions from occupants. Building on seminal research in the field, the study uses art visualization to reinterpret social feedback. We test this approach in an immersive interaction space where participants react to artistic visuals to attain predefined settings for three indoor devices. In the 197 interactions recorded, participants’ overall actions conformed with the predefined goals. The participants were able to reach all or some of the targets in more than 80%, within an average of less than 30 seconds. We also see that complementing the visuals with textual hints improved the interaction in terms of engagement and accuracy. We conclude that ambient, abstract, and artistic real-time goal-driven feedback is effective in influencing immediate actions. We recommend that guiding occupants didactically has a strong potential for advancing building controls

Designing a Program using Augmented Reality Technologies and some Interactive Educational Aids to Simplify Science of Remote sensing for Elementary School Students

The present research aims to develop innovative methods that simplify science. The author adopts the descriptive analytical approach by designing an electronic educational system that involve some electronic games that contribute to spreading awareness and culture of sensing and space in the Egyptian society. Teaching methods have been devised to motivate children and develop their skills, mix science with imagination and use interactive education based on Augmented Reality (AR) to search for minerals and rocks with satellite images. Thus, there is an interactive educational method based on augmented reality with cartoons and interaction to simplify sensor and space sciences. Augmented reality (AR) has gained increased recognition in various fields; learning via augmented reality technology will help learners comprehend learning content in a more creative frame of mind than ever before. It is substantial to understand the dynamics of augmented reality adoption to encourage students to employ this highly innovative and impactful type of technology in learning process

Eco-Nudging: Interactive Digital Design to Solicit Immediate Energy Actions in The Built Space

In the built space, building occupants, their behaviours and control actions are research areas that have gained a lot of attention. This is well justified since energy behaviours can result in differences of up to 25% in building energy consumption. Previous research recommends exploring ways to influence occupants' energy behaviour – through eco-feedback and by directly engaging occupants with building controls. Very little attention has been given to the role digital art and design can play in soliciting and changing human energy-related actions and behaviours in the built space. This paper proposes a new process that combines eco-feedback, gamification, and ecological digital art to trigger occupants to take immediate and precise control actions in the built space. We design, deploy and test this by creating an immersive human-building-interaction apparatus, which we place in a month-long exhibition. This experimental interface was informed by a novel vision for engagement-based human-building interactions deeply rooted in aesthetics, digital art and design. It also uses digital art to mediate between the occupants and energy-performance of spaces by redefining their relationship with and perception of energy – moving from metrics and quantities understanding to one that is art and emotion-based. The analysis reveals that this new type of human-engagement-based interactive building-control mechanism can add a significant layer of influence on energy-related actions – without revoking the individuals' ability to control their environment. It also highlights digital design and art's power in guiding actions and interactions with the built space