The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is suitable for multi-objective optimisation based on cooperative multi-agent systems (CMAS). The framework of DCLTML is used greedy iterative training to get an optimal set of weights and tabulated as a layer for each clustering structure. Such layers can deal with the challenges of large space and its massive data. Then the layer weights of each cluster are tuned by the Quasi-Newton (QN) algorithm to make the action sequence of CMAS optimal. Such a policy of CMAS effectively manipulates the inputs of the AHU, where the agents of the AHU activate the natural ventilation and set chillers into an idle state when the outdoor temperature crosses the recommended value. So, it is reasonable to assess the impact potential of thermal mass and hybrid ventilation strategy in reducing cooling energy; accordingly, the assigning results of the proposed DCLTML show that its main cooling coil saves >40% compared to the conventional benchmarks. Besides significant energy savings and improving environmental comfort, the DCLTML exhibits superior high-speed response and robustness performance and eliminates fatigue and wear due to shuttering valves. The results show that the DCLTML algorithm is a promising new approach for controlling HVAC systems. It is more robust to environmental variations than traditional controllers, and it can learn to control the HVAC system in a way that minimises energy consumption. The DCLTML algorithm is still under development, but it can potentially revolutionise how HVAC systems are controlled.
Background:Open reduction and internal fixation (ORIF) of using miniplates and screws is the treatment of choice of mandibular fractures. It is important to know both: the region where the bone providesafirm anchorage, andthe topography of the dental apices and inferior alveolar nerve to avoiddamaging them when inserting the screw. The aim of this study is to determine the thickness of buccal cortical plate and that of buccal bone at the parasymphysis and mandibular body, thereby determining the area that provide afirm anchorage and the maximum length of mono-cortical screws that can be safely placed in these regions without injuring the tooth roots or mandibular nerve. Materials and Methods:The sample of the present study was 110 Iraqi sub
... Show MoreThis paper investigates the interaction between fiscal and monetary policy in Iraq after 2003 using the prisoner’s dilemma.The paper aims to determine the best form of coordination between these policies to achieve their goals; payoff matrix for both policies was constructed. To achieve the purpose, the quantitative approach was applied using several methods, including regression, building payoff matrices and decision analysis using a number of software.The results of the monetary policy payment function show that inflation rate has an inverse relationship with the auctions of selling foreign currency and a positive relationship with the government’s activity, while the fiscal policy function shows that real growth is positively
... Show MoreThis study aims to preparation a standards code for sustainability requirements to contribute in a better understanding to the concept of sustainability assessment systems in the dimensions of Iraqi projects in general and in the high-rise building. Iraq is one of the developing countries that faced significant challenges in sustainability aspects environmental, economic and social, it became necessary to develop an effective sustainability building assessment system in respect of the local context in Iraq. This study presented a proposal for a system of assessing the sustainability requirements of Iraqi high rise buildings (ISHTAR), which has been developed through several integrated
The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr
... Show MoreThis paper attempts to shed light on the most influential factors in the importance of religious buildings were destroyed because of the recent war due to the control of terrorist gangs of ISIS over the city of Mosul, and to prioritize their reconstruction and their role in reviving the historical center of Mosul.
The research’s problem emerged in the lack of knowledge about the identifying the most influential factors in the importance of religious buildings and utilizing them to prioritize their reconstruction. This study aims to analyze the factors influencing the importance of religious buildings using the Expert Choice software through the Analytic Hierarchy Process (AHP) to reach an analysis of their weights and propose p
... Show MoreIn this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a
... Show MoreImproved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval