Is Reviewing Valuations a Tool for Curtailment of Professional Opinions?: A Perspective of a Reviewer Based on Valuations for Secured Lending Purpose

This paper delves into the pivotal role of valuation reviews in mortgage lending, dispelling misconceptions prevalent among private practice valuers. Drawing on the International Valuation Standards Framework, the study emphasizes the importance of qualified and ethical valuers in producing credible reports. Leveraging the author's extensive experience in the state sector and as a valuation reviewer for leading banks, the paper provides insights into fourfold review techniques—Administrative (Compliance) Review, Desk Review, Field Review, and Technical Review. These techniques ensure the accuracy, appropriateness, and adherence to Generally Accepted Valuation Principles, as per International Valuation Standards. In addition, the paper explores the technical background of mortgage valuations, highlighting nine key principles followed by valuers and examining Sri Lanka Valuation Standard-07. This paper also includes ten compelling case studies, covering diverse scenarios such as legal principles, wasting assets, building limits, accuracy of calculations, and valuation challenges associated with cattle farms and apartment buildings under construction. The paper reinforces the crucial role of valuation reviews in maintaining the integrity of mortgage valuations and the inclusion of ten case studies adds practical insights, covering a spectrum of scenarios and reinforcing the argument for adherence to regulatory standards and client requirements

Exploring Tourist Flow Patterns through Geotagged Social Media Data: A Case Study from Sri Lanka

Tourism studies often rely on conventional methods such as interviews and site-specific surveys to collect data on tourist behaviour, mobility patterns, and preferences. However, these methods can be expensive, time-consuming, and limited in scope. Additionally, accurately tracing tourist travel paths can be challenging due to recall bias. Recently, user generated content on social media platforms have emerged as an alternative data source in tourism studies. In this study, we used geotagged posts on Flickr to understand the dominant paths taken by inbound tourists in Sri Lanka. The methodology consisted of three steps. First, geotagged photographs were collected from the Flickr API spanning a ten-year period, from 2012 to 2022. These photographs included metadata such as user ID, the timestamp of photo capture, and geo coordinates indicating where the photo was taken. Second, a density-based clustering algorithm was utilized to identify tourist hotspots. Finally, the Markov Chain model was employed to calculate transition probabilities among different attractions, revealing dominant travel routes within the country. Study’s findings indicate that Cultural heritage attractions were the most popular, comprising 55% of all attractions identified by the algorithm, and are particularly popular in districts such as Anuradhapura, Polonnaruwa, Matale, Kandy, and Galle. Nature-based attractions, constituting 37% of the total, were mainly located in Nuwara Eliya and Badulla Districts, as well as Yala National Park in Hambantota District. For coastal tourism, Galle and Matara Districts were the top preferences. The analysis confirms dominant travel patterns between North Central, Central, and Southwest coast regions. Notably, Galle, Kandy, Matale, Matara, Nuwara Eliya, and Colombo attract tourists from a more diverse array of regions compared to other districts in the country, showcasing their significance as tourist hubs. The study findings highlight opportunities in Jaffna for cultural-heritage tourism, the Eastern coast for coastal tourism, and the central highlands for tea tourism. It also emphasizes the need to develop the less-visited natural sites to ease pressure on popular National Parks. This research's significance lies in its contribution to informed decision-making and the sustainable management of tourist destinations. By understanding tourist mobility patterns and identifying popular attractions through social media data, policymakers can effectively manipulate visitor flows and mitigate excessive tourist pressure, while preserving the authenticity and allure of these destinations.   Keywords: Sustainable tourism, Geotagged photographs, Social media, Tourist mobility, Flick

Supressão de plantas daninhas por leguminosas anuais em sistema agroecológico na Pré-Amazônia.

Este trabalho teve por objetivos identificar e avaliar a agressividade potencial das plantas daninhas em um agrossistema com leguminosas herbáceas anuais como cobertura de solo. Foram plantadas, nas ruas de um sistema de aléias de sombreiro ( Clitoria fairchildiana) e no final do período agrícola, as leguminosas mucuna-preta, feijão-guandu, feijão-de-porco e calopogônio, em sistema de blocos ao acaso com cinco repetições. Para estudo da dinâmica da composição florística, avaliaram-se a freqüência, densidade, dominância, similaridade, diversidade de espécies e biomassa das plantas daninhas. Foram identificadas 42 espécies de plantas espontâneas, das quais as mais freqüentes e de maior densidade e dominância foram Leptochoa virgata, Panicumlaxum e Sidasp. Não foram detectadas diferenças significativas para densidade, número de espécies, diversidade e biomassa entre as plantas daninhas emergidas nos quatro tratamentos com leguminosas; nem destas em relação ao controle

Incremental frontier generation for improvement of exploration efficiency

Autonomously navigating a single or a multiple set of robots to map a previously unknown environment is known as autonomous exploration and is a fundamental operation in many robotic missions. Given the unknown nature of the environment, planning for the optimal exploratory path for a robot or a group of robots to completely cover the given environment is known to be NP-Hard. Therefore, all autonomous exploration strategies operate by successively selecting the next best sensing location as robot's intermediate target point in a greedy manner, until the environment is completely mapped. Frontier based exploration and its many variants, where the robot's next sensing location is selected from the boundary between the mapped-free and unknown space (i.e. frontier) from the occupancy grid representation of the environment, has emerged as the baseline exploration strategy due to its simplicity and scalability. This dissertation examines the efficient generation and management of frontier information to refresh frontier cell information at a high frequency, and how these frequently available frontier cells can be utilized to further improve the efficiency of exploration missions. Incremental algorithms to extract both safe and reachable area from the occupancy grid map by processing only the locally updated map data and in turn generate only the valid frontier cells in an efficient manner is introduced. The proposed algorithms are validated in real world experimental data and is shown to drastically reduce and bound the execution time throughout exploration missions with very high detection accuracy compared to state of the art incremental frontier extraction methods. The resulting high frequency frontier cell refreshing is utilized to propose an improvement to the traditional frontier based exploration strategy as the next contribution. A probabilistic decision step, based on the most recent frontier cell information is proposed to decide the desirability of the remaining motion of the robot to its current intermediate target and to re-plan when the current motion is undesirable. This reduces redundant exploratory motions of the robot and improves the total efficiency of exploration missions. Experiments carried out in both real and simulated, indoor and outdoor environments corroborate the efficiency of this method and also reveal that the re-planning capability is especially suitable for improving efficiency of indoor exploration missions. This re-planning ability is then utilized to propose a new goal oriented navigation algorithm in unknown environments based on frontier based exploration. This is achieved by directing the exploration towards the goal. A new utility function based on the combined distance estimate to the goal from the robot's position through known and unknown cells is introduced for directing the exploration steps. The distance from frontier cells to the goal which is still in unknown area is estimated using a visibility graph generated through the unknown area thus negating the need to access the entire search space. Experimental results show that the proposed navigation algorithm is an alternative to popular dynamic planning algorithms and that it provides the same travel distance efficiency and a superior re-planning cost efficiency. Finally, the efficiency of exploration missions in unbounded environments is discussed in terms of the compactness of generated maps. Balanced mapping in all possible directions to generate compact maps is captured as balancing the arrival time of the robot to available frontier cells in the robot's neighborhood. The proposed efficient frontier management algorithms are employed to efficiently update the waiting times of individual frontier cells for robot's arrival and a waiting time variance based utility function is derived to guide the robot in a compact exploratory motion. Simulated experiments conducted in multiple environments for both single and multiple robot systems validate the efficiency of the proposed compact exploration strategy in mapping unbounded environments.DOCTOR OF PHILOSOPHY (EEE

A two-level approach for multi-robot coordinated exploration of unstructured environments

The efficiency of Multi-Robot Exploration can be improved by having a balanced distribution of robots in the environment. Exploration strategies for indoor/structured environments can ensure a balanced distribution of robots by explicitly assigning robots to distinct regions in the environment. However, unstructured environments do not support partitioning of environments to distinct regions, thus requires an alternative way of ensuring the balanced distribution of the robots. This paper presents a two level approach to multi-robot coordinated exploration of unstructured environments where a classical coordination method is employed at the lower level to provide a localized coordination while a higher level robot repositioning strategy is used to generate a balanced distribution of the robots in the environment. Simulation results indicate that this new approach provides a balanced distribution of the robots over the environment and improves the exploration efficiency over localized coordination strategies

Hotel Sewage Sludge Derived Biochar as an Adsorbent for Aqueous Cadmium Removal

The hotel industry is considered to be one of the main sources of sewage sludge. Sewage sludge (by-products) of wastewater treatment is considered as water, inorganic and organic materials removed from wastewater. These by-products coming from various sources through physical, chemical, and/or biological treatments. Cadmium is a non-essential heavy metal available in water sources accumulated through both natural phenomena and anthropogenic activities. Direct and indirect accumulation of Cadmium in tissues through food and drinking water causing various diseases and disorders. Thus, developed biochar from hotel sewage sludge Sri Lanka and its applicability to remove aqueous Cadmium ions was studied. In this study, the biochar wassynthesised pyrolsing the sewage sludge in a muffle furnace at 450o C. To maintain an oxygen-free atmosphere during the process, nitrogen was supplied to the system at a 200 mL/min flow rate. The temperature increase rate was set at 17o C/min. The pH, EC, total solid (TS), total fixed solid (TFS), and total volatile solids (TVS) were determined in sewage sludge. Then the synthesised biochar was characterised by X-ray diffraction (XRD), particle size analyser, and scanning electron microscopy (SEM). Furthermore, the Cadmium removal efficiency of synthesised biochar was tested with different concentrations of Cadmium solutions, pH levels, adsorbent dosages, and contact times. Atomic adsorption spectroscopy was used to analyse the Cadmium concentrations in water samples. The results were, pH (5.46), EC (1270 µs/cm), TS (55 mg/mL), TFS (14 mg/mL) and TVS (41 mg/mL). The maximum Cadmium removal percentage of 100% was obtained with 8 pH, 50 mL of 25 mg/L Cadmium solution, and 0.150 g of the synthesised biochar. Adsorption data were fitted with the Langmuir adsorption isotherm model and adsorption kinetics were fitted with a pseudosecond-order model with R2 , 0.9924. The study presents a viable option for removing Cadmiumions in water to desirable levels as a means for controlling Cadmium related health issues while sustainably controlling the sewage sludge.Keywords: Adsorption, Biochar, Heavy metal, Sewage sludg

A new gain function for compact exploration

Trade-off between the information gain and cost has been extensively used as an evaluation criteria for target points in robot exploration strategies where the primary goal is to reduce the mission time. This article introduces a new gain function that has an integrated cost component that can be used in exploration strategies to map the terrain in a balanced way in all directions to generate compact maps. Article also presents an approach to efficiently calculate the gain values. Simulations in both low and high obstacle density environments for single and multi-robot exploration strategies indicate the utility of the new gain function in generating compact maps

Hierarchical probabilistic fusion framework for matching and merging of 3-D occupancy maps

Fusing 3-D maps generated by multiple robots in real/semi-real time distributed mapping systems are addressed in this paper. A 3-D occupancy grid-based approach for mapping is utilized to satisfy the real/semi-real time and distributed operating constraints. This paper proposes a novel hierarchical probabilistic fusion framework, which consists of uncertainty modeling, map matching, transformation evaluation, and map merging. Before the fusion of maps, the map features and their uncertainties are explicitly modeled and integrated. For map matching, a two-level probabilistic map matching (PMM) algorithm is developed to include high-level structural and low-level voxel features. In the PMM, the structural uncertainty is first used to generate a coarse matching between the maps and its result is then used to improve the voxel level map matching, resulting in a more efficient and accurate matching between maps with a larger convergence basin. The relative transformation output from PMM algorithm is then evaluated based on the Mahalanobis distance, and the relative entropy filter is used subsequently to integrate the map dissimilarities more accurately, completing the map fusion process. The proposed approach is evaluated using map data collected from both simulated and real environments, and the results validate the accuracy, efficiency, and the support for larger convergence basin of the proposed 3-D occupancy map fusion framework.Accepted versio