Supervisory control for conventional unitary air conditioning system

The Supervisory control for conventional unitary air conditioning system is conceptually designed based on Programmable Logic Control (PLC) system. The advantage of PLC system is that it allows online monitoring continually and updates or modification can be performed interactively. This supervisory mode is applied to the conventional unitary air conditioner to avoid the frequent interruption or adjustment of the fan speed or temperature set point by users normal practice which has contributed to the surge of energy consumption due to the frequent on/off of the compressor. Three experiments have been performed at different control methods to simulate user’s daily practice. The first control method is the Variable Set point with high speed fan, the second control method is the Fixed Set point with high speed fan and the third control method is a Supervisory Control; a fixed set point with variable fan speed. The experiments have been conducted for eight (8) hours and the statistic data of accumulated energy consumption based on one unitary air conditioner with capacity of 1 Horse Power are acquired and sampled at the time interval of 30 minutes for the analysis. From these experiments, the supervisory control has consumed 4.2 kWh per day which is 82.35% compared to normal consumption of 5.1 kWh. This result translated into 0.9 kWh or 17.65% of total energy saving per day. The consistency of the air compressor operation in this control method has become a major factor in achieving indoor temperature steadiness whilst improving the energy savings

Learning Hybrid System Models for Supervisory Decoding of Discrete State, with applications to the Parietal Reach Region

Based on Gibbs sampling, a novel method to identify mathematical models of neural activity in response to temporal changes of behavioral or cognitive state is presented. This work is motivated by the developing field of neural prosthetics, where a supervisory controller is required to classify activity of a brain region into suitable discrete modes. Here, neural activity in each discrete mode is modeled with nonstationary point processes, and transitions between modes are modeled as hidden Markov models. The effectiveness of this framework is first demonstrated on a simulated example. The identification algorithm is then applied to extracellular neural activity recorded from multi-electrode arrays in the parietal reach region of a rhesus monkey, and the results demonstrate the ability to decode discrete changes even from small data sets

HUBUNGAN ANTARA KEMAMPUAN PROFESIONAL PENGAWAS DENGAN EFEKTIVITAS PENGENDALIAN INTERN DI KOPERASI PEGAWAI NEGERI JAKARTA TIMUR

ABSTRACT Feby OCTAFIANTY Saputri. Relationship Between Professional Capabilities with Efektivittas Supervisory Employees Cooperative Internal Control in East Jakarta District. Thesis, Jakarta. Economics Education Studies Program, Cooperative Economics Education Concentration, Department of Economics and Administration, Faculty of Economics, University of Jakarta, in December 2014. This study aimed to obtain information and knowledge based on data or facts valid or invalid, correct and trustworthy on the Relationship Between Professional Capabilities with Efektivittas Supervisory Employees Cooperative Internal Control in East Jakarta. This research was conducted at Civil Servants Cooperative in East Jakarta for three months, starting from September 2014 through December 2014. The method used in this study is a survey method with a correlation approach. Survey method with a correlation approach to research conducted on large and small populations studied but the data is the data from samples taken from the population that is found relative events, distribution and relationships between variables. The population in this study were all Employees Cooperative State in East Jakarta. Number of Civil Servants Cooperative located in East Jakarta Office of Government amounted to 56 cooperatives. Of 56 cooperatives only 13 active Cooperative who follow technical guidance structure of internal control. The sampling was superintendent of cooperatives. Each cooperative consists of three supervisors, only three cooperatives which have 2 supervisors. So the whole number of supervisors is 36 supervisors. Because only 13 cooperatives that meet the criteria then all the cooperatives sampled. The resulting regression equation is Y = 56.99 + 0,570X. Test requirements analysis that estimates the error normality test regression of Y on X with the test Liliefors produce Lhitung F table, meaning that the regression equation means, regression linearity test produces Fhitung t table. The coefficient of determination obtained by 42.90%, this means that the variation in the effectiveness of internal control 42.90% is explained by the professional ability and the rest is explained by other factors. The result of the calculation concludes that there is a positive relationship between the ability of the Supervisory Professional Effectiveness of Internal Control in East Jakarta District Cooperative Employees

An improved artificial dendrite cell algorithm for abnormal signal detection

In dendrite cell algorithm (DCA), the abnormality of a data point is determined by comparing the multi-context antigen value (MCAV) with anomaly threshold. The limitation of the existing threshold is that the value needs to be determined before mining based on previous information and the existing MCAV is inefficient when exposed to extreme values. This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. This paper proposed an improved anomaly threshold solution for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability. In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV. From the experiments towards 12 benchmark and two outbreak datasets, the improved DCA is proven to have a better detection result than its previous version in terms of sensitivity, specificity, false detection rate and accuracy

The simulation of action disorganisation in complex activities of daily living

Action selection in everyday goal-directed tasks of moderate complexity is known to be subject to breakdown following extensive frontal brain injury. A model of action selection in such tasks is presented and used to explore three hypotheses concerning the origins of action disorganisation: that it is a consequence of reduced top-down excitation within a hierarchical action schema network coupled with increased bottom-up triggering of schemas from environmental sources, that it is a more general disturbance of schema activation modelled by excessive noise in the schema network, and that it results from a general disturbance of the triggering of schemas by object representations. Results suggest that the action disorganisation syndrome is best accounted for by a general disturbance to schema activation, while altering the balance between top-down and bottom-up activation provides an account of a related disorder - utilisation behaviour. It is further suggested that ideational apraxia (which may result from lesions to left temporoparietal areas and which has similar behavioural consequences to action disorganisation syndrome on tasks of moderate complexity) is a consequence of a generalised disturbance of the triggering of schemas by object representations. Several predictions regarding differences between action disorganisation syndrome and ideational apraxia that follow from this interpretation are detailed

Bypassing the selection rule in choosing controls for a case-control study

Objectives It has been argued that in case–control studies, controls should be drawn from the base population that gives rise to the cases. In designing a study of occupational injury and risks arising from long-term illness and prescribed medication, we lacked data on subjects' occupation, without which employed cases (typically in manual occupations) would be compared with controls from the general population, including the unemployed and a higher proportion of white-collar professions. Collecting the missing data on occupation would be costly. We estimated the potential for bias if the selection rule were ignored. Methods: We obtained published estimates of the frequencies of several exposures of interest (diabetes, mental health problems, asthma, coronary heart disease) in the general population, and of the relative risks of these diseases in unemployed versus employed individuals and in manual versus non-manual occupations. From these we computed the degree of over- or underestimation of exposure frequencies and exposure ORs if controls were selected from the general population. Results: The potential bias in the OR was estimated as likely to fall between an underestimation of 14% and an overestimation of 36.7% (95th centiles). In fewer than 6% of simulations did the error exceed 30%, and in none did it reach 50%. Conclusions: For the purposes of this study, in which we were interested only in substantial increases in risk, the potential for selection bias was judged acceptable. The rule that controls should come from the same base population as cases can justifiably be broken, at least in some circumstances. <br/

Codifying Information Assurance Controls for Department of Defense (DoD) Supervisory Control and Data Acquisition (SCADA) Systems (U)

Protecting DoD critical infrastructure resources and Supervisory Control and Data Acquisition (SCADA) systems from cyber attacks is becoming an increasingly challenging task. DoD Information Assurance controls provide a sound framework to achieve an appropriate level of confidentiality, integrity, and availability. However, these controls have not been updated since 2003 and currently do not adequately address the security of DoD SCADA systems. This research sampled U.S. Air Force Civil Engineering subject matter experts representing eight Major Commands that manage and operate SCADA systems. They ranked 30 IA controls in three categories, and evaluated eight SCADA specific IA controls for inclusion into the DoD IA control framework. Spearman’s Rho ranking results (ρ = .972414) indicate a high preference for encryption, and system and information integrity as key IA Controls to mitigate cyber risk. Equally interesting was the strong agreement among raters on ranking certification and accreditation dead last as an effective IA control. The respondents strongly favored including four new IA controls of the eight considered