Integrated Sensor Fusion Device with an Optimized Mathematical Model to Monitor Civil Engineering Structures

Integrated sensor fusion is a new technique in which multiple sensors intelligently combine data to support application or system performance improvement software. With this method, many sensors combine data for accurate position and orientation information to overcome the inadequacy of each sensor. Data consolidation can be described as measuring the state of an entity as a mixture of data or information. This multidisciplinary field has several advantages, including increased confidence, reliability, and reduced ambiguity when measuring company conditions in engineered systems. This paper discusses the various applications of data fusion in civil engineering in recent years, and puts forward some potential advantages of data fusion in civil engineering. Mathematical modeling (MM) is the skill to transform challenges from application to tractable mathematical formulations that provide insight, answers, and instructions in the theoretical and numerical analysis of the original application. This article presented an integer linear programming mathematical model to divide building activities in a project to solve building planning problems. MMCE (Mathematical Modeling Conceptual Evaluation) introduced it to complete an accurate and quick estimation of civil systems such as traffic networks, structural systems, and building projects, becoming more and more achievable through omnipresent sensor networks and communications systems. By assessing the condition of the system, it can make better decisions more rapidly and better. This has enormous value and a variety of impacts. Fusion data is an essential element of system status assessment. Applications and needs for research are underlined for the future

Methodological challenges for collaborative learning research

Research on collaborative learning, both face-to-face and computer-supported, has thrived in the past 10 years. The studies range from outcome-oriented (individual and group learning) to process-oriented (impact of interaction on learning processes, motivation and organisation of collaboration) to mixed studies. Collaborative learning research is multi-disciplinary. This introduces a multitude of theoretical accounts for collaborative learning, accompanied by a broad spectrum of methods to study processes and outcomes of collaboration. This special issue will provide an overview of methods that are at the core of current research effort, but also identifies opportunities and problems to sensibly combine methods into mixed method approaches

Developing integrated data fusion algorithms for a portable cargo screening detection system

Towards having a one size fits all solution to cocaine detection at borders; this thesis proposes a systematic cocaine detection methodology that can use raw data output from a fibre optic sensor to produce a set of unique features whose decisions can be combined to lead to reliable output. This multidisciplinary research makes use of real data sourced from cocaine analyte detecting fibre optic sensor developed by one of the collaborators - City University, London. This research advocates a two-step approach: For the first step, the raw sensor data are collected and stored. Level one fusion i.e. analyses, pre-processing and feature extraction is performed at this stage. In step two, using experimentally pre-determined thresholds, each feature decides on detection of cocaine or otherwise with a corresponding posterior probability. High level sensor fusion is then performed on this output locally to combine these decisions and their probabilities at time intervals. Output from every time interval is stored in the database and used as prior data for the next time interval. The final output is a decision on detection of cocaine. The key contributions of this thesis includes investigating the use of data fusion techniques as a solution for overcoming challenges in the real time detection of cocaine using fibre optic sensor technology together with an innovative user interface design. A generalizable sensor fusion architecture is suggested and implemented using the Bayesian and Dempster-Shafer techniques. The results from implemented experiments show great promise with this architecture especially in overcoming sensor limitations. A 5-fold cross validation system using a 12 13 - 1 Neural Network was used in validating the feature selection process. This validation step yielded 89.5% and 10.5% true positive and false alarm rates with 0.8 correlation coefficient. Using the Bayesian Technique, it is possible to achieve 100% detection whilst the Dempster Shafer technique achieves a 95% detection using the same features as inputs to the DF system

Performance of composite sand cement brick containing recycled concrete aggregate and waste polyethylene terepthalate

The reuse and recycling of waste materials from construction and demolition waste is one of the new concepts for brick manufacturing production. Construction and demolition debris refers to waste materials that result from the construction, renovation and demolition of buildings. Bricks are an important material for developing areas where manufacturers find it difficult to locate adequate sources due to the shortage of natural aggregate supply. Construction waste can be recycled to replace naturals resource or other competitive materials. This study aims to establish the sustainable properties for composite bricks using Recycle Concrete Aggregate (RCA) and Polyethylene Terephthalate (PET) waste bottles as sand aggregate replacement. RCA was obtained from crushed laboratory concrete cubes while PET bottles were collected around UTHM and Parit Raja areas. The objectives of this study are to determine the optimum cement-sand ratio (1:5, 1:6 and 1:7) for composite brick through density, compressive strength and water absorption tests, to investigate the mechanical properties and durability of composite sand cement bricks through shrinkage and carbonation tests, and to identify the optimum percentages of RCA and PET as sand aggregate replacement in composite bricks. For this study, the brick specimens were prepared using 25%, 50% and 75% of RCA and 1.0%, 1.5%, 2.0% and 2.5% of PET by volume of natural sand with a water-cement ratio of 0.6. The size of the RCA used measured less than 5 mm. Moreover, the size of the sieved waste PET granules was between 0.1 to 5 mm which made it physically similar to the size of fine aggregates. The bricks were cast in moulds measuring 215 mm in length, 103 mm in width, and 65 mm in depth. Three types of sand-cement ratios were used, namely 1:5, 1:6 and 1:7. The first stage of the study was the determination of the best sand-cement ratio through density, water absorption and compressive strength tests. The next stage was the determination of the optimum percentages of RCA and PET according to the shrinkage and carbonation tests. The overall results revealed that the best cement-sand ratio was 1:6. The density test indicates that the average density of composite bricks is lower compared to that of control bricks. The cement-sand ratio of 1:6 was the optimum value for all sample bricks. In addition, the percentage of water absorption for composite bricks was found to be satisfactory. It can be concluded that the optimal replacement of RCA and PET was R25P1 with a cement-sand ratio of 1:6 as it achieved the lowest values during the drying shrinkage and carbonation tests

Occipital nerve stimulation for headache disorders

Occipital nerve stimulation (ONS) was originally described in the treatment of occipital neuralgia. However, the spectrum of possible indications has expanded in recent years to include primary headache disorders, such as migraine and cluster headaches. Retrospective and some prospective studies have yielded encouraging results, and evidence from controlled clinical trials is emerging, offering hope for refractory headache patients. In this article we discuss the scientific rationale to use ONS to treat headache disorders, with emphasis on the trigeminocervical complex. ONS is far from a standardized technique at the moment and the recent literature on the topic is reviewed, both with respect to the procedure and its possible complications. An important way to move forward in the scientific evaluation of ONS to treat refractory headache is the clinical phenotyping of patients to identify patients groups with the highest likelihood to respond to this modality of treatment. This requires multidisciplinary assessment of patients. The development of ONS as a new treatment for refractory headache offers an exciting prospect to treat our most disabled headache patients. Data from ongoing controlled trials will undoubtedly shed new light on some of the unresolved questions

Degeneration of the intervertebral disc with new approaches for treating low back pain.

This review paper discusses the process of disc degeneration and the current understanding of cellular degradation in patients who present with low back pain. The role of surgical treatment for low back pain is analysed with emphasis on the proven value of spinal fusion. The interesting and novel developments of stem cell research in the treatment of low back pain are presented with special emphasis on the importance of the cartilaginous end plate and the role of IL-1 in future treatment modalities