Maintenance Responsibilities Research Articles

Cost Estimation for the Operation and Maintenance of Automated Monitoring and Early-Warning Equipment for Geological Hazards

Geological hazards impede regional economy sustainability. To limit their destructive impacts on human life and property, the Chinese government has independently developed automated monitoring and early-warning equipment, which has been deployed in over 250,000 locations nationwide, yielding effective early warnings. The smooth operation of this equipment necessitates substantial human, material, and financial resources for its maintenance. To allocate funds rationally, the Ministry of Finance of China has mandated the urgent establishment of budget standards for the operation and maintenance of automated monitoring and early-warning systems for geological hazards. Addressing the research gap in this area, this study meticulously develops a cost model, subcategorizing operating costs, maintenance costs, and management costs. Addressing the intricate issue of maintenance expenditures, this study ingeniously breaks down routine operations and urgent repairs stipulated in technical standards into personnel, materials, and vehicular needs for each equipment type. Considering the total manpower involved in equipment maintenance, the per-unit maintenance cost is determined. This method allocates costs to individual pieces of equipment, thereby sidestepping the quantification hurdle created by varying types and quantities of monitoring equipment at each monitoring site due to various geological disaster types and magnitudes, and technical personnel’s maintenance responsibility for multiple equipment types in a single operation. Finally, incorporating regional adjustment coefficients, we have formulated theoretical costs for the operation and maintenance of automated monitoring and early-warning equipment for geological hazards. By contrasting theoretical costs with actual project budgets, the error margin is within 2%. Following nationwide consultation, these theoretical costs have been officially endorsed as the budget standard. These standards will lay the groundwork for project budgeting and review, facilitate efficient fund utilization, and ensure the financial sustainability of monitoring and warning systems for geological hazards. Concurrently, this paper bridges the global lack in budget norms for the operation and upkeep of automated geological disaster monitoring systems. The cost calculation model introduced serves as a pivotal reference globally for the evaluation of analogous system’s operations and maintenance expenses.

Assessing the Role and Capacity of Water Management Organizations for Ensuring Delta Food Security in Bangladesh

The coastal zone, consisting of one-third country's area, is the most climate-vulnerable region of Bangladesh. The country has invested significantly in coastal zone through the construction and rehabilitation of polders. Despite vast opportunities, land productivity in the polders is very low due to poor water governance and management. To improve in-polder water management, the responsibility of operation and maintenance of the polder water infrastructure has been transferred to Water Management Organizations (WMOs) since 2001. WMOs are currently voluntary organizations but are very important for micro-level agricultural water management. A study was conducted in 2017 and 2018 in a medium saline polder; with a major focus on organizational behaviour: hierarchy in decision-making, transparency, financial accountability, leadership, internal communication, and motivational incentives of the WMOs. The data were collected through a structured questionnaire from 192 respondents of randomly selected eight Water Management Groups (WMGs – the lowest tier of WMOs), out of 40 WMGs of the polder. The results revealed that the WMGs operations are not fully participatory in principle yet. Even the transparency, financial accountability, leadership, and internal communications within WMGs are not strong enough to take the organizational responsibility to address future challenges in food security of the climate-vulnerable polder communities. Improving drainage through efficient water management showed a yield gain of at least 1.5 t/ha in the wet season only. In addition, improved drainage fosters sustainable year-round cropping with high-yielding, high-value and nutrition-rich crops with 2 to 3 times higher productivity than the traditional cropping system. Therefore, investment in water governance particularly in improving drainage in the polders could be a major game-changer in sustaining the food security of the climate-vulnerable polder communities of Bangladesh. The study identified the knowledge gap as a significant concern that demands the need for capacity building of the WMOs.

The Method of the Probability Analysis of Area with Dissolved Gases in Power Transformer Insulating Oil

Transformer insulating oil plays an extremely important role in power transformers and is used for insulation, arc suppression, cooling and other purposes. However, its other focus is on dissolved gases analysis in the oil to monitor internal operating conditions, which is the responsibility of preventive maintenance. This paper uses the normal distribution theory and the American National Standard Specification (hereinafter referred to as ANSI/IEEE C57.104) to reorganize as a diagnostic tool. The range of each gas from three stages of the specification - normal, caution, and abnormal are incorporated to a stage of abnormal, which divide into equal different values of 1000 as the maternal body of a qualitative normal distribution. Then the benchmark is been calculated from those parameters of a qualitative normal distribution. The data of detection has to pass through "Gas chromatography” to generate dissolved gases. At last, the benchmark value compares with dissolved gases to find the abnormal probability value as a diagnostic tool in maintenance evaluation of equipment. This method was developed using EXCEL application software, and repeatedly tested and verified with examples to confirm its feasibility and high accuracy. In addition, 10 cases accident data were extracted from the literature [11], and compared with the actual maintenance results. The accuracy was 80% for ANSI/IEEE C57.104 and 90% for this probability method. Therefore, this diagnostic method can replace the traditional multi-stage judgment and be represented by a single probability value to show. Based on technology sharing, the development process is specially written into a technical article as reference by scholars and electrical maintenance personnel in the field of power engineering.
 Design Methods: Making a qualitative normal distribution employs EXCEL software and the discriminative rule of ANSI/IEEE C57.104. Design Purpose: As a diagnostic tool with dissolved gases in insulating oil. Design Effectiveness: Probability Method is better than traditional; it has those efficacies - the accuracy and feasibly and compete with tried and tested actual case.

Optimizing maintenance responsibility distribution in real estate management: A complexity-driven approach for sustainable efficiency

Efficient route management is critical for optimizing maintenance activities in real estate management. This study delves into the intricate task of allocating maintenance duties among building surveyors, a pivotal concern for property management firms. The primary goal of route planning is to enhance operational efficiency by minimizing travel time. To achieve this, the study explores three distinct algorithms: Saving, Nearest Neighbor, and an Evolutionary Algorithm (EA) customized with Dual Response Surface Optimization (DRSO). The integration of DRSO and EA enhances adaptability, allowing for dynamic responses to changes and improved allocation of maintenance tasks. Practical limitations, such as time and capacity, are considered through a case study involving a well-established building management organization. Results indicate that the Nearest Neighbor Algorithm generates 16–18 routes, the Saving Algorithm produces 18 routes, and the DRSO-driven EA also yields 18 routes. Significantly, the DRSO-driven EA consistently outperforms traditional methods, achieving a remarkable 17.7% reduction in route distance and an 18.8% reduction in journey time. In specific scenarios with 50 and 80 locations in Northeast and Central Bangkok, the DRSO-driven EA demonstrates practicality and efficacy. The algorithm's ability to address real-world challenges is underscored by these examples, showcasing its potential for broader implementation in real estate management. This study contributes significantly to the optimization of maintenance routes, presenting a clear roadmap for enhancing operational efficiency and customer satisfaction. Furthermore, it addresses the challenges posed by capitalism's growth constraints, offering insights for the adoption of sustainable economic practices in management, economics, and engineering.

A Unified Approach for Resilience and Causal Responsibility with Integer Linear Programming (ILP) and LP Relaxations

What is a minimal set of tuples to delete from a database in order to eliminate all query answers? This problem is called "the resilience of a query" and is one of the key algorithmic problems underlying various forms of reverse data management, such as view maintenance, deletion propagation and causal responsibility. A long-open question is determining the conjunctive queries (CQs) for which resilience can be solved in PTIME. We shed new light on this problem by proposing a unified Integer Linear Programming (ILP) formulation. It is unified in that it can solve both previously studied restrictions (e.g., self-join-free CQs under set semantics that allow a PTIME solution) and new cases (all CQs under set or bag semantics). It is also unified in that all queries and all database instances are treated with the same approach, yet the algorithm is guaranteed to terminate in PTIME for all known PTIME cases. In particular, we prove that for all known easy cases, the optimal solution to our ILP is identical to a simpler Linear Programming (LP) relaxation, which implies that standard ILP solvers return the optimal solution to the original ILP in PTIME. Our approach allows us to explore new variants and obtain new complexity results. 1) It works under bag semantics, for which we give the first dichotomy results in the problem space. 2) We extend our approach to the related problem of causal responsibility and give a more fine-grained analysis of its complexity. 3) We recover easy instances for generally hard queries, including instances with read-once provenance and instances that become easy because of Functional Dependencies in the data. 4) We solve an open conjecture about a unified hardness criterion from PODS 2020 and prove the hardness of several queries of previously unknown complexity. 5) Experiments confirm that our findings accurately predict the asymptotic running times, and that our universal ILP is at times even quicker than a previously proposed dedicated flow algorithm.

Simulating intra-household interactions for in- and out-of-home activity scheduling

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly based on the individual decision-making process, which are limited in their demonstration of behaviour. We simulate multiple intra-household interaction dimensions within the same framework and capture the coordination of the activity scheduling decisions among all household members. Our approach adopts the Optimisation-based Activity Scheduling Integrating Simultaneous choice dimensions (OASIS) framework, which is at the level of isolated individuals and focuses on out-of-home activity schedules. We jointly simulate in- and out-of-home activities and incorporate interactions into the framework. Our framework contributes to the state-of-the-art in activity-based modelling by explicitly capturing multiple interactions within the same model, such as the allocation of the private vehicle to household members, dividing household maintenance responsibilities, escorting, joint activity participation, and sharing rides. We operationalise the model using time-use-survey data from the United Kingdom. The simulation results demonstrate the ability of the framework to capture complex intra-household interactions. We then demonstrate how these interactions can cause individuals to deviate from their schedules planned in isolation. This is a general framework applicable to different household compositions and available resources.

Machine learning approach for predicting bridge components’ condition ratings

Information on bridge condition rating is critical to make decisions regarding rehabilitation or replacement of bridges. Currently, bridge components’ condition ratings are evaluated manually using inspection reports. Markov chain and Petri net models are most commonly used for predicting future values of bridge parameters, however, applicability of these models for a regional or statewide portfolio of bridges may be limited. The existing data based models have low prediction accuracy. Hence, a data and machine learning based approach is presented herein for predicting the future condition values of major components—deck, superstructure and substructure—in a portfolio of bridges with an objective to develop a more accurate approach. National Bridge Inventory (NBI) was used to get information on current and past bridge components’ condition from year 1992–2019 along with other parameters such as ownership, maintenance responsibility and age. After selecting important parameters, this data was used to train three RUSBoost based random forest models for predicting future values of deck, superstructure, and substructure conditions, respectively. The prediction accuracy of the developed models were found above 93%, thereby addressing the limitation of poor prediction accuracy of the existing studies. Additionally, the uncertainties associated with the random forest based predictions were quantified at the regional level and for individual bridges. On-system concrete pre-cast slab units and steel I-beam bridges in Louisiana were selected to demonstrate the proposed approach and predict bridge components condition ratings for years 2020 and 2021.

Implementing Green Roofs in the Private Realm for City-Wide Stormwater Management in Vancouver: Lessons Learned from Toronto and Portland

Green roofs are an innovative stormwater management technology that has numerous environmental benefits. Citywide implementation is critical to maximizing the benefits of green roofs, especially in terms of jurisdictional encouragement and advancing management programs. The City of Vancouver is interested in developing a rainwater management strategy that supports the widespread implementation of green roofs on private property. Performance control for a green roof on private property requires standards on local natural factors that affect performance; development considerations; supporting legal tools; maintenance and operation responsibilities; equity through the different types of private properties; and finally, cost. Research into the rainwater management strategies for the cities of Toronto and Portland for green roof implementation was conducted to provide insight into the best approaches for such an implementation in Vancouver. Portland and Toronto both have independent green roof standards in addition to separate rainwater management strategies. Portland focuses on a post-occupancy inspection program to monitor a green roof’s ongoing performance, while Toronto established the Green Roof Bylaw to encourage the implementation of green roofs. Incentive programs that educate and encourage private owners to take the initiative to construct and effectively operate green roofs are essential to the success of a private green roof program.

Lifestyle and language barriers influence community engagement with green infrastructure.

Few studies have focused on value structures, experiences, and cultural diversity as it relates to bioswale planning and implementation. We used 'Point of Opportunity Interactions' to understand previously undocumented views of the Cantonese-speaking immigrant community regarding bioswale design and use for stormwater management in Portland, Oregon, USA. Approximately half of participants were not aware of bioswale function. Maintenance costs and aesthetics were noted concerns, but parking and safety were not. Lack of outreach materials in the Chinese language(s), evening and weekend work schedules, and lack of clarity about maintenance responsibility were among barriers to public participation. Overall, lack of trust for the city and city officials was apparent, and hindered outreach and engagement. Emphasis on informality and place-based data collection near bioswales as neutral outdoors spaces, andproximate to participant residences, facilitated communication with this 'hard-to-reach' population and revealed information that would have gone unknown using traditional outreach strategies.

The role of transportation in developing the tourism sector at high altitude destination, Kinnaur.

As a supporting factor, transportation is an important element of destination image that provides a base for the successful tourism industry. It is like the blood vessels of an area and is considered a determinant in developing a tourist destination. The article aims to characterize the status or problem of transportation accessibility in Kinnaur. GARMIN hand GPS (Global Positioning System) has been used to identify the damaged roads from their start to endpoints. In addition, a simple random sample technique has been used to register the opinion of 280 tourists about the transport facilities. Study results suggest that the bad condition of National Highway-22 is one of the barriers to tourism development in Kinnaur. There were no significant differences found between the selected destinations. Overall, the district headquarters, Kalpa, has been perceived significantly higher agreements by tourists. The government should ensure that the Border Road Organization, the organization entrusted with the responsibility of construction and maintenance of roads in international border areas, has sufficient resources to invest in transport development and its maintenance.

Decision support systems in irrigation management: Irrigation Facilities Spatial Information System

AbstractAgricultural production and food are strategically important for nutrition, which is the basic requirement of living. Adequate supply of food depends on the sustainability of agricultural activities. Despite the proportional increase in other sectors in water use on a global scale, agriculture is still the largest user. Since Türkiye is located in a semi‐arid climate region, most of the year is dry. Apart from the rainy period, there is not enough water in our streams, especially in periods when irrigation water is needed. For this reason, the water stored in the months when there is a lot of precipitation is used in the months when it is needed for irrigation. The main purpose of irrigation management is to ensure that irrigation water demands within the irrigated area are shared fairly from the spring to the downstream areas in the desired time and amount, in accordance with the current water potential, the capacity of the irrigation system and the actual needs. Although the initial establishment and facility costs of automation and related decision support systems are high, the benefits and added value provided in the medium‐ and long‐term result in the irrigation facilities being preferred more during the operation and maintenance process. Automation applications, especially in closed irrigation systems, can prevent external intervention and water can be supplied to the network according to the real needs. The web‐based application, the Irrigation Facilities Spatial Information System (SUTEM), is designed to monitor, evaluate and report on the operation, maintenance and management activities of the facilities operated by the General Directorate of State Hydraulic Works or whose operation, maintenance and management responsibilities are transferred. The requirements are met through a single application that saves time and labour, facilitates control and supervision, standardizes reports and enables transition to a centralized data security structure.

The Global Peace Mandate of the United Nations Security Council, Conflict Management and the Israeli-Palestinian Question

The United Nations global conflict management strategy is based on certain fundamental assumptions that require serious re-examination in the twenty-first century. This study is focused on the United Nations Security Council, its global peace maintenance responsibility mandated by the United Nations Charter and the protracted Israeli-Palestinian conflict. The doctrinal approach was employed for this study. This is with aim to assess the long-standing violence between Israel and Palestine and a possible way of effective management and possible resolution, which is the sole responsibility of the United Nations Security Council. The study shed more light on the role of the Security Council, its efforts and its challenges that are hampering warring nations from settling their disputes. The study concluded that, although the United Nations Security Council has played vital roles in instituting global peace, which is the fundamental principle of macroeconomic stability, the reforms of the Council is at the top of the most pressing global political issues facing the international community. Therefore, among the recommendations of this study is that, the reformation of the Council to mirror the present globalized world political order is of utmost significance in order to provide room for effective regional or continental representation, just as a representative government is well suited for a federating country. This would enable effective representation via regional or continental powers creating a platform for feasibly effective conflict management and possible resolution of interstate conflicts.

Co-building trust in urban nature: Learning from participatory design and construction of Nature-Based Solutions in informal settlements in East Africa

While the amount of research on NBS is growing rapidly, there is a lack of evidence on community experiences of NBS design and implementation, particularly from low-income and informal settlements of African cities. This article adds new empirical evidence in this space through grounded analysis of NBS “niche” projects co-developed by intermediary organizations and communities in five sites across three settlements in Nairobi and Dar es Salaam. Findings are organized around four established NBS knowledge gaps: (1) NBS-society relations; (2) Design; (3) Implementation; (4) Effectiveness. We find that across the five studied sites, residents' perceptions and valuation of urban nature has changed through processes of co-design and co-implementation, enabling community ownership of projects, and hence playing a crucial role in NBS effectiveness over time. The integration of gray components into green infrastructure to create hybrid systems has proven necessary to meet physical constraints and communities' urgent needs such as flood mitigation. However, maintenance responsibilities and cost burdens are persisting issues that highlight the complex reality of NBS development in informal settlements. The cases highlight key considerations for actors involved in NBS development to support the replication, scaling up and institutionalization of NBS. These include the need to: (i) develop forms of engagement that align with co-production values; (ii) capture communities' own valuation of and motivations with NBS development for integration into design; (iii) elaborate technical guidance for hybrid green-gray infrastructure systems that can be constructed with communities; and (iv) help define and establish structures for maintenance responsibilities (especially governmental vs. civil society) that will enhance the environmental stewardship of public spaces.

Analysing urban trees on verges and slopes along a highway using machine learning methods

In arboricultural research, data analysis is important to the understanding of the characteristics of urban forest. This study attempted to apply machine learning techniques on a relatively small data set. This research aimed at exploring the biodiversity and structure of tree stands on verges and slopes along a highway, and analysing the influences of habitat characteristics on the tree stands with the aid of machine learning techniques. 53 slopes and 52 verges along San Tin Highway, Hong Kong were surveyed. 7209 trees belonging to 23 species were found. Dimension reduction proved successful in the concise characterisation of urban forest by a biodiversity component and an abundance component. The biodiversity component score of the slopes (0.625) was higher than that of the verges (−0.637). However, the abundance component scores of slopes (−0.059) and verges (0.060) showed slight difference, reflecting comparable tree abundance. A 75–25 train/test split was applied on a data subset consisting of slopes registered under a scheme called Systematic Identification of Maintenance Responsibility of Slopes in the Territory for regression analysis. The scores of the two components were regressed on several slope geophysical variables. Slope height and slope area served as significant predictors explaining biodiversity. Boosting improved the explanatory power and predictive accuracy of the regression model on the biodiversity component, as evidenced by an increase in adjusted R2 by 0.23 and a decrease in RMSE by 0.40. This research proved that component scores can serve as inputs for regression models for the explanation of urban forest characteristics by habitat-related variables. In future, small data sets from tree surveys can be analysed using the workflow demonstrated in this study for the generation of more management insights.

Detection of Road Cracks Using Convolutional Neural Networks and Threshold Segmentation

Automatic road crack detection is an important transportation maintenance responsibility for ensuring driving comfort and safety. Manual inspection is considered to be a risky method because it is time consuming, costly, and dangerous for the inspectors. Automated road crack detecting techniques have been extensively researched and developed in order to overcome this issue. Despite the difficulties, most of the proposed methodologies and solutions involve machine vision and machine learning, which have lately acquired traction largely due to the increasingly more affordable processing power. Nonetheless, it remains a difficult task due to the inhomogeneity of crack intensity and the intricacy of the background. In this paper, a convolutional neural network-based method for crack detection is proposed. The method is inspired from recent advancements in applying machine learning to computer vision. The primary goal of this work is to employ convolutional neural networks to detect the road crack. Data in the form of images has been used as input, preprocessing and threshold segmentation is applied to the input data. The processed output is feed to CNN for feature extraction and classification. The training accuracy was found to be 96.20 %, the validation accuracy to be 96.50 %, and the testing accuracy to be 94.5 %.

Aplikasi teorema bayes dalam mendukung aktivitas autonomous maintenance di pabrik gula Kedawoeng

Autonomous Maintenance (AM ) is o ne of the main activities in Total Productive Maintenance (TPM). This article discusses the implementation of AM at the diffuser station at the Kedawoeng Sugar Factory using Bayes' theorem. To maintain the continuity of sugar production, the Kedawoeng Sugar Factory needs to improve the maintenance system. AM improves the maintenance system without depending on the limited maintenance personnel in the factory. The AM concept demands that the production operator be involved in the maintenance process. Increasing the operator's ability to diagnose damage through damage symptoms is necessary. The Bayes theorem successfully helps operators predict machine failure to take quick and effective action to prevent a more significant impact. This study identified 11 m achine malfunction symptoms that can be detected through the five senses that lead to 14 failures. One of the research findings is that if the symptoms are only abnormal sounds, the highest probability of motor-bearing gear failure is 0.762. Suppose a warning accompanies the abnormal sound on the control panel probability of motor-bearing gear failure increases to 0.987. A clear division of machine maintenance responsibilities between operators and maintenance technicians and maintenance training for operators are suggestions for the next steps in implementing TPM.

A STUDY ON THE RESTRICTING MAINTENANCE MANAGEMENT PRACTICES ON PUBLIC INFRASTRUCTURE: EVIDENCE FROM GHAHA

The research aim is to assess the restricting maintenance management practice in Ghana mainly focusing on Kumasi Sports stadium. Specifically, how restricting maintenance practices such as, absence of maintenance policy (AMP); ignoring maintenance responsibility (IMR) and Poor Infrastructure design (PID) affect public facilities in Ghana. A Self-administered questionnaire was used to collect primary data after a pilot test. The data were described using frequency distribution and percentages. The results from multiple regression analysis indicated that there is a positive significant linear relationship between Restricting Maintenance Management Practices and Public Infrastructure in Ghana due to the fact that Restricting Maintenance Practices affects the betterment of the stadia leading it to deteriorate. The study recommends there should be a maintenance policy that compels stakeholders to be accountable for ignoring maintenance responsibility

Innovation outcomes and processes in infrastructure projects – a comparative study of Design-Build and Design-Build-Maintenance contracts

Innovation is often seen as essential for long-term development in the construction industry, but its actual outcomes and processes in construction projects require more attention. Many studies on procurement strategies and delivery systems have focussed on the public transport infrastructure sector, whereas most construction innovation scholars have addressed the innovation phenomenon in construction generally. Thus, the purpose of this study is to compare how two delivery systems, design-build (DB) and design-build-maintenance (DBM), influence project-level innovation. Findings are based on empirical data from a multiple case study of six infrastructure projects, three with DB contracts and three with DBM contracts, in which 12 innovations are identified, described, and compared. The findings show that various kinds of innovations in terms of outcomes and processes are implemented in infrastructure projects, and that the delivery system do effect both dimensions. Long maintenance responsibilities tend to spur contractors to engage in early exploration of sustainable solutions that could be of long-term benefit. The research contributes to procurement literature by exemplifying how delivery systems influence both the outcomes and processes of project-level innovations. It also increases our knowledge about construction innovation as a multi-dimensional phenomenon.

Do Islamic Banking Financial Instruments Achieve Equitable Income and Wealth Distribution?

The study investigates empirically whether the current practices of Sharīʿah-based financing contracts namely, Murabahah, Musharakah, Mudarabah, Istisna, Bai Bithaman Ajil, Ijarah and other contracts in the Malaysian Islamic banking industry achieved equitable income and wealth distribution. To do so, the study applied the bounds test and ARDL model to investigate the relationship between Sharīʿah-based financing contracts and Malaysian GINI coefficient index over the period from 1Q 2014 to 1Q 2019. In analyzing the long- and short-run implications, it was found that the practice of such Sharīʿah-based financing contracts in the Islamic banking industry achieved equitable income and wealth distribution in Malaysia using Murabahah, Mudarabah, Istisna, Bai Bithaman Ajil, and other (i.e., forward Ijarah) financing contracts. On the other hand, the findings indicated that Musharakah and Ijarah-based financing contract practices did not achieve equitable income and wealth distribution in Malaysia. This may be because the current practices of both contracts which seem to be handled as debts instruments and designed to the benefit of the banking sector only. To improve the Islamic banks’ financing practices in Malaysia, the outcomes of the study suggest that bank operators should strengthen the weight of Sharīʿah-based profit and loss sharing financing contracts with small and mid-size enterprises (SMEs) instead of corporations. In other words, Islamic banks are able to achieve fair income and wealth distribution and uphold the concept of justice for all by gradually increasing Musharakah-based financing for SMEs that can potentially grow and create economic value. Further, to solve the problem of Ijarah contract practices, Islamic banks must take steps to enhance the requirements of Ijarah contracts, specifically ownership transformation, maintenance responsibility, default penalty, and the issue of legal treatment as well as bear the costs, risks and rewards related to the leasing asset instead of borne by the clint. The empirical findings of the study will provide valuable input for banks policymakers, particularly central banks, and Islamic bank management to evaluate the current practice of Islamic finance and proactively correct shortcomings to achieve equitable wealth distribution. This study is a pioneering investigation that empirically evaluates whether the current practices of Islamic banking financial instruments achieve the aims of the equitable financial system, and ensure that Islamic banks, as intermediaries, address the issue of inequality and attain equitable wealth distribution worldwide.

Assessment of Residential Buildings Condition In Government Built Housing Estates of Port Harcourt Municipality, Nigeria

A major key indicator for assessing the quality of an urban residential neighborhood is the building condition. A good building condition adds value to a neighborhood in terms of aesthetics, safety, security and comfort. The Rivers State Government has in 1986 - 1998 built 12 residential estates for her staff members in the study area. The responsibility of maintenance of the buildings has been left to the owner occupiers of those houses. What is the state of those houses which has been built for over 30years? It is on this note that this study is poised to ascertain the physical condition of buildings within the public housing estates in Port Harcourt municipality. This study is a quantitative research that belongs to the class called “descriptive research design”. Simple random sampling technique was used to select 108 respondents (household heads) from the six selected housing estates. Questionnaire, physical observation and digital camera were the tools used for data collection. Analysis of findings was presented descriptively in tables, charts and percentages. Among the twelve public housing estates identified within the study area, the simple random sampling method was used to select and study six of the estates which are: 1. Aggrey Housing Estate, 2. Marine Base Govt. Housing Estate, 3. Abuloma housing estate phase, 4. Ndoki Housing Estate, 5. Elekahia housing estate and, 6. Khana Street Housing Estate. The research findings show the physical condition of buildings within the public housing estates, 81.5% of the buildings has good foundation, 92.6% of the windows are in good condition, 95.4% of the buildings have water system. 65% of the respondents considered the overall housing condition of the estates as good (needs no repair) while 35% saw the housing condition as fairly good (needs minor repair).