Preface

Welcome to The 2020 International Conference on Science in Engineering and Technology (ICoSiET), online held 21-22 October, 2020. The 2020 International Conference on Science in Engineering and Technology (ICoSiET) is an international conference which covers Science and applied engineering and technology. ICoSiET 2020 will be held on October 21-22, 2020 in Palu, Indonesia. This conference hosted by Universias Tadulako and is jointly organized with Association for Scientific Computing Electronics and Engineering (ASCEE), Universitas Islam Alauddin Makassar, Universitas Negeri Malang, Universitas Mulawarman, Universitas Muslim Indonesia, and Universitas Lambung Mangkurat. This conference is IOP conference so that papers accepted and presented will be forwarding for consideration to be published in the IOP Material Science and Engineering. Thanks are due to Keynote Speakers, Prof. Dr. Zhen-jiang Shen (Faculty of Geosciences and civil Engineering, Institute of Science and Engineering Kanazawa University, Japan), Prof. Dr. Richard Sliuzas (Department of Urban and Regional Planning and Geo-Information Management Twente University, Netherland), Prof. Yandi Andri Yatmo., Ph.D (Department of Architecture Faculty of Engineering Universitas Indonesia, Indonesia). Prof. Amar Akbar Ali (Department of Architecture Universitas Tadulako, Indonesia), and Dr. Diana Contrias Mojica, New Castle University, UK) This year, the ICOSIET conference received 110 papers submissions from 106 countries such as, Bangladesh, China, Colombia, Germany, Hong Kong, India, Indonesia, Iraq, Japan, Jorda, Peru, Philippines, Russia, Saudi Arabia, Thailand, United Kingdom, United States and Viet Nam. But only 68 papers were accepted for presentations for online sessions (the acceptance ratio is 65%). We are very grateful for the extensive efforts of many individuals who worked diligently to ensure a successful and high quality conference. We would like to thank to IPO, ASCEE, TPC Committee and Faculty of Engineering Tadulako University for supporting this event. Once again we would like to say Welcome to ICOSIET 2020. Congratulations for your papers have been accepted. We invite all participants to actively participate in the conference activities to learn from one another. Thank you for choosing ICOSIET as your conference reference. We hope to have your pleasant supports and participations in the next year 2021 7th ICOSIET. List of ICoSIET 2020 Committee, ICoSIET 2020 Editors are available in this pdf.

Acceptance Ratio Analysis in Grid-Connected Photovoltaic System: Is There Any Difference Between DC and AC?

The performance status of a grid-connected photovoltaic (GCPV) system is denoted by performance indices, namely performance ratio, capacity factor, and even through power acceptance ratio (AR), as documented in Malaysia Standard (MS) procedures for acceptance test of GCPV testing and commissioning (TNC). Even though AR analysis can be either on the DC or AC side, the MS TNC procedures implemented analysis on the AC side. Therefore, the question arises whether there is any significant difference when using AC AR analysis compared to DC AR analysis in evaluating the system performance. Thus, this paper evaluates the differences between applying DC AR analysis and AC AR analysis in accessing the performance of the ten kWp GCPV system in Malaysia. The AR analytical analysis employed the 2019 one-year historical data of solar irradiance, module temperature, DC power, and AC power. The results demonstrated that the monthly AC AR were consistently lower than DC AR with a percentage difference of approximately 3%. The percentage discrepancy was due to the variation of actual inverter efficiencies compared to the declared constant value by the manufacturer used in the AR prediction model. These findings have verified a significant difference between DC AR analysis and AC AR analysis. Most importantly, this study has highlighted the significance of AC AR analysis compared to DC AR analysis as a tool to evaluate GCPV system performance because AC AR has taken an additional factor into consideration, which is the inverter efficiency variation.

Guaranteeing Timely Response to Changes of Monitored Objects by Assigning Deadlines and Periods to Tasks

Timely response to changes of monitored objects is the key to ensuring the safety and reliability of cyber-physical systems (CPSs). There are two kinds of tasks in CPSs: update tasks and control tasks. Update tasks are responsible for updating the data in the system based on the state of the objects they monitor. Control tasks are responsible for making decisions based on the data in the system. The response time of the system to the change of a monitored object consists of two parts: the time taken by update tasks to reflect the change to the system, and the time taken by control tasks to make decisions according to the data in the system. Deadlines and periods of update tasks and control tasks directly affect the response time. Reasonable deadline and period assignment is the key to ensuring timely response to the changes of monitored objects. In this paper, we study the deadline and period assignment in CPSs. To the best of our knowledge, all existing work only focuses on the deadline and period assignment for update tasks with the goal of ensuring the freshness of the data in CPSs, and this is the first study focusing on the deadline and period assignment for both update tasks and control tasks with the goal of ensuring timely response to the changes of monitored objects. A new problem about response time control and system workload control is defined in this paper. Two deadline and period assignment methods are proposed to solve the defined problem. All the proposed methods can be used in the CPSs adopting the earliest deadline first (EDF) scheduling method. Experiments with randomly generated tasks are conducted to evaluate the performance of the proposed methods in terms of acceptance ratio and execution efficiency.

Solvation Free Energy of Protonated Lysine: Molecular Dynamics Study

In the present work, we have used an alchemical approach for calculating solvation free energy of protonated lysine in water from molecular dynamics simulations. These approaches use a non-physical pathway between two end states in order to compute free energy difference from the set of simulations. The solute is modeled using bonded and non-bonded interactions described by OPLS-AA potential, while four different water models: TIP3P, SPC, SPC/E and TIP4P are used. The free energy of solvation of protonated lysine in water has been estimated using thermodynamic integration, free energy perturbation, and Bennett acceptance ratio methods at 310 K temperature. The contributions to the free energy due to van der Waals and electrostatics parameters are also separately computed. The estimated values of free energy of solvation using different methods are in well agreement with previously reported experimental value within 14 %.

Improved two factor fuzzy commitment scheme for securing IoT device

Purpose Generally, Internet-of-Things (IoT) is quite small sized with limited resource and low cost that may be vulnerable for physical and cloned attacking. All kind of authentication protocols designed to IoT devices are robust despite which it is prone to attack by hackers. In order to resolve this issue, there are various researches that have introduced the best method for obscuring the cryptographic key. However, the studies have majorly aimed to generate the key dynamically from noise data by Fuzzy Extractor (FE) or Fuzzy Commitment (FC). Hence, these methods have utilized this kind of data with noisy source namely Physical Unclonable Function (PUF) or biometric data. There are several IoT devices that get operated over undermined environment in which biometric data is not available but the technique utilized with biometric data can't be used to undermined IoT devices. Even though, the PUF technique is implemented for the undermined IoT devices this is quite vulnerable over physical attacks inclusive of accidental move and theft. Design/methodology/approach This paper has proposed an advanced scheme in fuzzy commitment over IoT devices which is said to be Improved Two Factor Fuzzy Commitment Scheme (ITFFCS) and this proposed ITFFCS has used two kind of noisy factors present inside and outside the IoT devices. Though, an intruder has accomplished the IoT devices with an access to the internal noisy source, the intruder can't select an exact key from the available data which have been compared using comparable module as an interest. Findings Moreover, the proposed ITFFC method results are compared with existing Static Random Accessible Memory (SRAM) PUF in enterprises application which illustrated the proposed ITFFC method with PUF has accomplished better results in parameters such as energy consumption, area utilization, False Acceptance Ratio (FAR) and Failure Rejection Ratio (FRR). Originality/value Thus, the proposed ITFFCS-PUF is comparatively better than existing method in both FAR and FRR with an average of 0.18% and 0.28%.

Energy-Efficient Task Offloading Under E2E Latency Constraints

<b>Abstract:</b><br>In this paper, we propose a novel resource management scheme that jointly allocates the transmit power and computational resources in a centralized radio access network architecture. The network comprises a set of computing nodes to which the requested tasks of different users are offloaded. The optimization problem minimizes the energy consumption of task offloading while takes the end-to-end-latency, i.e., the transmission, execution, and propagation latencies of each task, into account. We aim to allocate the transmit power and computational resources such that the maximum acceptable latency of each task is satisfied. Since the optimization problem is non-convex, we divide it into two sub-problems, one for transmit power allocation and another for task placement and computational resource allocation. Transmit power is allocated via the convex-concave procedure. In addition, a heuristic algorithm is proposed to jointly manage computational resources and task placement. We also propose a feasibility analysis that finds a feasible subset of tasks. Furthermore, a disjoint method that separately allocates the transmit power and the computational resources is proposed as the baseline of comparison. A lower bound on the optimal solution of the optimization problem is also derived based on exhaustive search over task placement decisions and utilizing Karush–Kuhn–Tucker conditions. Simulation results show that the joint method outperforms the disjoint method in terms of acceptance ratio. Simulations also show that the optimality gap of the joint method is less than 5%.<br>

Energy-Efficient Task Offloading Under E2E Latency Constraints

<b>Abstract:</b><br>In this paper, we propose a novel resource management scheme that jointly allocates the transmit power and computational resources in a centralized radio access network architecture. The network comprises a set of computing nodes to which the requested tasks of different users are offloaded. The optimization problem minimizes the energy consumption of task offloading while takes the end-to-end-latency, i.e., the transmission, execution, and propagation latencies of each task, into account. We aim to allocate the transmit power and computational resources such that the maximum acceptable latency of each task is satisfied. Since the optimization problem is non-convex, we divide it into two sub-problems, one for transmit power allocation and another for task placement and computational resource allocation. Transmit power is allocated via the convex-concave procedure. In addition, a heuristic algorithm is proposed to jointly manage computational resources and task placement. We also propose a feasibility analysis that finds a feasible subset of tasks. Furthermore, a disjoint method that separately allocates the transmit power and the computational resources is proposed as the baseline of comparison. A lower bound on the optimal solution of the optimization problem is also derived based on exhaustive search over task placement decisions and utilizing Karush–Kuhn–Tucker conditions. Simulation results show that the joint method outperforms the disjoint method in terms of acceptance ratio. Simulations also show that the optimality gap of the joint method is less than 5%.<br>

Assessment of Concentrated Liquid Coffee Acceptance during Storage: Sensory and Physicochemical Perspective

Concentrated liquid coffees (CLCs) refer to stored extracts stable at environmental temperature, used as ingredients in the retail market. Their low chemical stability affects the sensory profile. This study was performed in two CLCs, one without additives (BIB) and another with a mix of sodium benzoate and potassium sorbate additives (SD), stored at 25 °C for one year. Quantitative-Descriptive (QDA) and discriminant analyses permitted identifying the critical sensory attributes and their evolution over time. The concentrate without additives presented an acceptance limit of 196 days (evaluated at a 50% acceptance ratio), while the additives increased the shelf life up to 226 days (38.9% improvement). The rejection was related to a decreased aroma, increased acidity, and reduced bitterness. A bootstrapped feature selection version of Partial Least Square analysis further demonstrated that reactions of 5-caffeoylquinic acid (5CQA) and 3,5-dicaffeoylquinic acid (3,5diCQA) could cause changes in the aroma at the first degradation stage. In the following stages, changes in fructose and stearic acid contents, a key indicator of acceptance for both extracts possibly related to non-enzymatic reactions involving fructose and other compounds, might affect the bitterness and acidity. These results provided valuable information to understand flavor degradation in CLCs.