Improving the indoor air quality (IAQ) through application of the air cleaning technologies for offices building simulated in environmental chamber

Indoor air quality (IAQ) is very important issue in residential and commercial buildings, because human spend almost 90% of their life indoor. IAQ problems effect on the health of the occupants, and lead to reduction of the efficiency and output in workplaces. The main objective of this study is to improving the (IAQ) and to reduce energy consumption in offices building, through experimental and simulation investigation. The method used in this study was by using environmental chamber to represent the real office. The results of the experimental were validated the simulation. The chamber was modified by installing two mechanical filters with low pressure drop; minimum efficiency reporting value rate 13 (MERV 13) and activated carbon filter (ACF) on the air handling unit. The IAQ parameters which include temperature, relative humidity, air velocity, air flow rate, pressure drop, CO2 concentration and particle matters PM 10 and PM 2.5 concentration for upstream and downstream were considered in this study. These variables were measured inside the chamber using IAQ devices and these data were used as an input data for simulation by using ANSYS 16.1 software. The simulation generated the air distribution via air velocity, temperature, CO2 concentration and the particle distribution in the room. The results from experiment showed good agreement for combining filters efficiency value from 86.20% to 84.60% and from 86% to 82.35% for PM 10 and PM 2.5 particle removal respectively during occupied period. The CO2 concentration decreased during the measurement period from 816 ppm to 700 ppm and the distribution was in the acceptable range compare with ASHRAE standard 55-2004 and Malaysian industry code of practice on IAQ. Also, the validation with simulation showed below 10% error ratio compare with experiment results. The significance of study is to balance between enhancing thermal comfort inside workplace and (IAQ) for occupants, leading to reduction of energy consumption

Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings

Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort by combining predictive control with demand controlled ventilation (DCV). First, we show that the problem of maintaining IAQ, thermal comfort and optimal energy is a multi-objective optimization problem with competing objectives, and a predictive control approach is required to smartly control the system. This leads to many implementation challenges which are addressed by designing a hybrid ventilation scheme supported by predictive control and soft-sensors. The main idea of the hybrid ventilation system is to achieve thermal comfort by varying the ON/OFF times of the air conditioners to maintain the temperature within user-defined bands using a predictive control and IAQ is maintained using Healthbox 3.0, a DCV device. Furthermore, this study also designs soft-sensors by combining the Internet of Things (IoT)-based sensors with deep-learning tools. The hardware realization of the control and IoT prototype is also discussed. The proposed novel hybrid ventilation system and the soft-sensors are demonstrated in a real research laboratory, i.e., Center for Research in Automatic Control Engineering (C-RACE) located at Kalasalingam University, India. Our results show the perceived benefits of hybrid ventilation, predictive control, and soft-sensors

Indoor air quality in California homes with code-required mechanical ventilation.

Data were collected in 70 detached houses built in 2011-2017 in compliance with the mechanical ventilation requirements of California's building energy efficiency standards. Each home was monitored for a 1-week period with windows closed and the central mechanical ventilation system operating. Pollutant measurements included time-resolved fine particulate matter (PM2.5 ) indoors and outdoors and formaldehyde and carbon dioxide (CO2 ) indoors. Time-integrated measurements were made for formaldehyde, NO2 , and nitrogen oxides (NOX ) indoors and outdoors. Operation of the cooktop, range hood, and other exhaust fans was continuously recorded during the monitoring period. Onetime diagnostic measurements included mechanical airflows and envelope and duct system air leakage. All homes met or were very close to meeting the ventilation requirements. On average, the dwelling unit ventilation fan moved 50% more airflow than the minimum requirement. Pollutant concentrations were similar to or lower than those reported in a 2006-2007 study of California new homes built in 2002-2005. Mean and median indoor concentrations were lower by 44% and 38% for formaldehyde and 44% and 54% for PM2.5 . Ventilation fans were operating in only 26% of homes when first visited, and the control switches in many homes did not have informative labels as required by building standards

Linkage between knowledge management practices towards library user’s satisfaction at Malaysian University Libraries

Academic library services have begun to apply various knowledge management (KM) practices in the provision of library services. KM has been developed to enhance the use of organizational knowledge through practices and organizational learning. KM practices include the creation, capture and/or acquisition of knowledge, its retention and organization, its dissemination and re-use, and general responsiveness to the new knowledge. The focus of this research is the assessment of KM practices, particularly creation, acquisition, capture, sharing, recording and preservation, and their effects on Library User’s Satisfaction (LUS) in Malaysian university libraries. The objective of this research is the development of a model to enhance KM processes (i.e. Creation, acquisition, capturing, sharing, recording, and preserving) and to improve library users’ satisfaction. A quantitative approach in research methodology is employed (e.g. Questionnaire) for the purpose of generating new knowledge and understanding of library concerns. The findings of this research show that the overall KM practice at six Malaysian university libraries is at a high level. The findings from the structural model indicated that two KM processes, namely knowledge creation and acquisition, are not supported in terms of KM practices at Malaysian university libraries. Other KM processes, namely capturing, sharing, recording, and preserving are fully supported towards KM practices in the library. Hence, the major contribution of this research is a model, namely KM Practice-Library User’s Satisfaction (KMP-LUS) highlighting six KM processes based on strong Structural Equation Modeling (SEM) fit indices

Clitics in Sasak, eastern Indonesia

This paper is a discussion of the distribution of clitics in Sasak, an Austronesian(Western Malayo-Polynesian) language spoken by approximately two million people on the island of Lombok, eastern Indonesia. It outlines the types of clitics found Sasak and shows that there are interesting interactions between clitic placement and focus constructions that result in the violation of a number of canonical word orders in Sasak. The author argues that these violations can be seen as arising from competition for linear positions within the sentence; this can be accounted for within an optimality-theoretic syntax framework (Bresnan, 2000, Grimshaw, 1999) which describes sentence structures in terms of violable ranked constraints, the interaction of which accounts for observed structures as being the most optimal result of constraint competition

Key schedule algorithm based on coordinate geometry of a three-dimensional hybrid cube

Cryptographic algorithms play an important role in information security where it ensures the security of data across the network or storage. A key schedule algorithm is the mechanism that generates and schedules all session-keys for the encryption process. The 2-dimensional hybrid cube is generated based on permutation and combination of integer numbers that are utilized in the construction of encryption and decryption key in the non-binary block cipher. The generation of key space by using the 2-dimensional hybrid cubes are not sufficient to resist attacks and could easily be exploited. Therefore, the large key space is more desirable to resist any attack on the secret key. This research proposed a new Key Schedule Algorithm based on the coordinate geometry of a Hybrid Cube (KSAHC) for the non-binary block cipher. By using the three-dimensional hybrid cube in KSAHC transformation, encryption keys are represented as n × n × n matrix of integer numbers and used in the development of the permutation and substitution of order 4 square matrix. Triangular Coordinate Extraction (TCE) technique has also been introduced to extract the coordinates during the rotation of Hybrid Cube surface (HCs) and plays an important role in the development of KSAHC algorithm. The Hybrid Cube Encryption Algorithm (HiSea) has been implemented to validate the encryption keys that are generated from the proposed algorithm. The strength of the keys and ciphertext are compared with the Advanced Encryption Standard (AES), HiSea, and Dynamic Key Schedule Algorithm (DKSA). The proposed KSAHC algorithm has been validated using the randomness test proposed and recommended by NIST, the average result of avalanche test is 93%, entropy is 0.9968, correlation assessment test is -0.000601 and having large key space 2.70 × 1067 keys that makes the Brute Force attack difficult and time-consuming. Therefore, it can be concluded that the strength and validity of KSAHC algorithm have been enhanced as compared to other algorithms and can serve as the alternative algorithm in designing security systems

Performance of a demand controlled mechanical extract ventilation system for dwellings

The main aim of ventilation is to guarantee a good indoor air quality, related to the energy consumed for heating and fan(s). Active or passive heat recovery systems seem to focus on the reduction of heating consumption at the expense of fan electricity consumption and maintenance. In this study, demandcontrolled mechanical extract ventilation systems of Renson (DCV1 and DCV2), based on natural supply in the habitable rooms and mechanical extraction in the wet rooms (or even the bedrooms), was analysed for one year by means of multi-zone Contam simulations on a reference detached house and compared with standard MEV and mechanical extract ventilation systems with heat recovery (MVHR). To this end, IAQ, total energy consumption, CO2 emissions and total cost of the systems are determined. The results show that DCV systems with increased supply air flow rates or direct mechanical extract from bedrooms can significantly improve IAQ, while reducing total energy consumption compared to MEV. Applying DCV reduces primary heating energy consumption and yearly fan electricity consumption at most by 65% to 50% compared to MEV. Total operational energy costs and CO2 emissions of DCV are similar when compared to MVHR. Total costs of DCV systems over 15 years are smaller when compared to MVHR due to lower investment and maintenance costs