International Journal of Engineering
Volume:32 Issue: 8, Aug 2019

Propolis was used as medicine, cosmetic and beverage additives since past decades. The most important active compounds in the propolis are phenolic and flavonoids, which are in the resin category. The purpose of this study was to measure the total amount of flavonoids and quercetin in propolis of northern Iran and compare obtain data with different extraction methods. The soxhlet, maceration and microwave-ultrasound-assisted extraction (MUAE) were conducted for comparison of the extraction efficiency. Total amount of flavonoids measured by Spectrophotometry and the amount of quercetin were determined by using high performance liquid chromatography (HPLC). Here in this work, the best extraction yield for the total flavonoids was obtained 70.88 % and for quercetin was 44.53% at 300 W, 1.5 min for microwave and ultrasound 10 min and 40 °C. Also extraction yield of quercetin for soxhlet (as reference method) was determined 67.85% and for maceration was 13.9%. UV-vis, HPLC and FTIR analyses were used to determine the extraction yield and chemical structure of the active compounds. Then antioxidant and antibacterial effects of propolis extract were evaluated and the obtained results were compared with the related literature.

Aromatic plants have subscribed to the belief that they can be used in food, perfumery, pharmaceutical and cosmetic products due to their nutritional and biological properties. The present study was designed to examine the chemical composition and antibacterial and analgesic properties of Lavandula stoechas flowers originating Amol, north of Iran for the first time. The essential oil of Lavandula stoechas flowers was obtained by hydrodistillation. Gas chromatography-mass spectrometry examination was used for its analysis. Staphylococcus aureus, Escherichia coli, Salmonella enteritidis and Bacillus subtilis were utilized to evaluate the antibacterial activity of essential oil using agar disk diffusion and microdilution assayes. GC-MS analysis revealed Linalol (35.69%) Borneol (14.99%) and 1,8-Cineole (11.45%) as the main compounds of the oil. Antibacterial assayes of various dilutions of essential oil revealed its remarkable antibacterial activity against gram-positive Staphylococcus aureus. Furthermore, the water and ethanolic extracts inhibited the pain resulting from hot-plate test. The results proposed lavandula stoechas from Amol as an alternative natural bioactive compound which posses antibacterial and analgesic effects to use in pharmaceutical industries.

In this project, the degradation of synthetic wastewater comprising p-nitro toluene (PNT) is investigated using UV/TiO2 process. PNT as a pollutant has a very harmful effect on the environment and human hormones. TiO2 is one of the best metal oxides it has photo catalyst role. The full factorial design (FFD) of experiment is employed to investigate the effect of working variables including pH, initial dosage of PNT and catalyst concentration. The Analysis of variance (ANOVA) presented a high determination coefficient value (R2 = 0.9876, R2pred = 0.8585, R2adj = 0.9596) for degradation of PNT and acceptable prediction of second-order regression model. The graphical counter plots were used to control the optimum conditions. The operative variables are optimized at [TiO2] = 0.2g/L , pH value of 4, and  [PNT] = 50mg/L. These findings suggest that the percentages of degradation and mineralization of PNT at the forecasted optimum conditions after 120 min of reaction were 64 and 55%, respectively.

To understand the seismic damage characteristics of bottom frame-wall buildings and to study their seismic performance, the seismic damage outcomes of  bottom frame-wall structures in Du jiang weir by the Wen chuan earthquake on May 12,2008, China were field observed and studied. The assesment of the seismic damage to the bottom frame-wall masonry in Du jiang weir urban showed that the damage to the type of structure system was serious and including damage to the bottom frame, the bottom storey, the transition storey, the bottom node and the rear longitudinal wall, combining with the failure characteristics, the failure reasons and mechanism were analyzed and the corresponding treatment measurements are given. However, a substantial number of bottom frame seismic wall masonry structures (BFSWMSs) after 2000 are basically undamaged. The field inspections team sampled 2178 buildings of the urban ensemble observation. A considerable number of buildings seismic fortified have shown excellent seismic performance in Wenchuan earthquake, which sufficient illustrates the significant role of seismic fortification factors in structural design. Through, the investigation and analysis of its empirical seismic damage, the main measures to improve its seismic performance of construction structure. The above analysis results can provide a reference for seismic design and the revision of seismic intensity scales.

Cycle time optimization could be one of the great challenges in business process management. Although there is much research on this subject, task similarities have been paid little attention. In this paper, a new approach is proposed to optimize cycle time by minimizing entropy of work lists in resource allocation while keeping workloads balanced. The idea of the entropy of work lists comes from the fact that the time it takes for a resource to do similar tasks in a rather consecutive order is less than the time it takes to do the same tasks separately. To this end, an entropy measurement is defined, which represents task similarities on some given work lists. Furthermore, workload balancing is also regarded as an objective because not only is cycle time optimization important, but also workload fairness should also be met. Experimental results on a real-life event log of BPI challenge 2012 showed that the proposed method leads to 32% reduction in cycle time, compared with a reinforcement learning resource allocation without involving the entropy.

In social networking/microblogging environments, #tag is often used for categorizing messages and marking their key points. Also, since some social networks such as twitter apply restrictions on the number of characters in messages, #tags can serve as a useful tool for helping users express their messages. In this paper, a new knowledge-intensive content-based #tag recommendation system is introduced. The proposed system works by integrating structured knowledge in every core component. First, the relevant features, semantic structures and information-content are extracted from messages. Since little information can often be placed in a message, a content enrichment module is introduced to identify information structures that can improve the representation of message. The extracted features are represented by semantic network. Then, a hybrid and multi-layered similarity module identifies the commonalities and differences of the features, semantics and information-content in messages. At the end, #tags are recommended to users based on #tags in contextually similar messages. The system is evaluated on Tweets2011 dataset. The results suggests that the proposed method can recommend suitable #tags in negligible operational time and when little content is available.

Internet of things (IoTs) is the newfound information architecture based on the internet that develops interactions between objects and services in a secure and reliable environment. As the availability of many smart devices rises, secure and scalable mass storage systems for aggregate data is required in IoTs applications. In this paper, we propose a new method for storing aggregate data in IoTs by the use of -threshold secret sharing scheme in the cloud storage. In this method, original data is divided into blocks ‎that ‎each ‎block ‎is ‎considered ‎as a ‎share. The edge server does not send these shares (blocks) directly (through the secure channel) to cloud service providers ( s). Rather, the edge server hides the shares (blocks) with XORing two secret values and publishes the result. Indeed, with this method, none of s has an amount of block information.‎This scheme is also verifiable, i.e., in the verification phase, each  can verify its quasi-share. Moreover, before data retrieval, the edge server checks the correctness of provided quasi-share from s of an authorized group. Also, the proposed scheme is scalable, since new data can be inserted or part of the original data can be deleted, without changing shares. It is worth noting that the proposed scheme is more efficient compared with the other scheme since heavy and complex computation is not required.

This paper proposes a pulsed power generator which consists of two types of switched-capacitor booster modules. A doubling mode module employed to elevate the input voltage to a specified level and, constant mode module is used to increase the elevated voltage into the finally intended bipolar output voltage. Also, the proposed modular structure does not utilize any switches across the load. Other advantage of the proposed structure is its lower current stress on source and every circuit component near it. In comparison with Marx Generator (MG) based topologies, the number of circuit components has been significantly reduced, which led to cost-saving and prevention of circuit control complexity. Calculation of the capacitors is presented. Experimental tests and simulations are performed on a five-module system which confirms the high performance of the proposed topology.

Traditionally, conventional generation unit was used to provide ancillary services e.g. reactive power support, and spinning reserve. Nonetheless, with the emergence of highly penetrated distributed energy resources (DERs) systems and considering how beneficial they can be; it appears reasonable to use them as reactive power providers. Therefore, this paper introduces a new procedure for DERs to participate in the reactive power market. To do that, an algorithm is proposed to calculate the deliverable reactive power capability of DERs from distribution networks to transmission systems. Furthermore, a reactive power procurement model is introduced to consider DERs participation in the reactive power market. Finally, to show the effectiveness, and validity of this method many case studies are carried out on 33-bus distribution and CIGRE 32-bus transmission test systems

This work proposes a direct sequence spread spectrum transmitter with high transmission range and efficiency for audio signals. It is shown that by choosing high process gain for spread spectrum signal the data could reach a range of 55km in the 2.4GHz ISM band. By employing a light modulation scheme, we have a relaxed SNR requirement for having a low bit error rate (BER) which translates to relaxed error vector magnitude (EVM) condition. Therefore a switching power amplfier (PA) is used in this work which improves the transmitter’s efficiency while by taking PAs nonidealities into account we extracted the new equations to find the conditions to improve the efficiency compared to conventional zero current and zero current switching conditions. The PA efficiency is equal to 79.5% while having 30dBm output power. The mixer alongside power amplifier used in this work provide a conversion gain of 9 dB while having 16 dBm output compression point. The  employed tunable quadrature oscillator has the ability to cancel phase and amplitude errors without comprimising the oscillator phase noise. The transmitter reaches an efficiency of 73.4% and an EVM of -32.75 dB.

With respect to the dramatic increasing use of electronically communicators and wireless modems, concerns have been raised about the possible effects of emitted electromagnetic radiation on human brain. In this paper, the effects of high-frequency wireless modem waves on the brain signal are investigated. To this end, the Electroencephalograph (EEG) recording of 15 volunteers is examined in four different bands. The experiments are designed to cover in four steps. Average power statistical analysis in different frequency bands and magnitude-squared coherence function shows significant changes in some bands.

In this paper, new topology of phase shifter is proposed that uses advantage of metamaterial and MEMS technology. The phase shifter is switched between two states of RH- and LH-TL having frequency passband unlike other proposed metamaterials which create the maximum phase shift from one unitcell. Analysis and design approach of the phase shifter is presented and the structure is simulated using 3D simulator. The phase shifter creates 180 degree phase shift with return loss and insertion loss that are better than 15 dB and 0.25 dB in both states at frequency ranges of 1.4-4.4 GHz. Therefore, low loss, high bandwidth and high phase shift are the advantages of the new proposed phase shifter.

A Digital Microfluidic Biochip (DMFB) offers a promising platform for medical diagnostics, DNA sequencing, Polymerase Chain Reaction (PCR), and drug discovery and development. Conventional Drug discovery procedures require timely and costly manned experiments with a high degree of human errors with no guarantee of success. On the other hand, DMFB can be a great solution for miniaturization, integration, automation, and cost reduction of drug discovery. DMFB can improve the parallelism of drug discovery procedures; since most procedures in drug discovery are concurrent and parallel, DMB can reduce the execution time of these bioassays. Therefore, there is a critical need to develop DMFBs to speed up the drug discovery applications and improve cost and error of these reactions. In this paper, a new architecture is used for drug discovery applications. The architecture is evaluated and compared with FPPC architecture. The experimental results prove that the new architecture is faster and cheaper than FPPC; it reduces all the important parameters such as total execution time, number of controlling pins, CAD algorithm execution time, and the area usage and its costs. There is an urgent need for collaboration between experts of drug discovery, microfluidic platform architecture and also machine learning to design a data-driven microfluidic architecture which improves the CAD algorithms by learning from prior knowledge.

Partial shading reduces the power output of solar modules, generates several peak points in P-V and I-V curves and shortens the expected life cycle of inverters and solar panels. Electrical array reconfiguration of PV arrays that is based on changing the electrical connections with switching devices, can be used as a practical solution to prevent such problems. Valuable studies have been performed to justify the electrical array reconfiguration efficiency. However, there are some problems such as algorithms complexity, simulations runtime and the inability of objective functions to detect the best array. In this paper, the photovoltaic (PV) array reconfiguration problem is solved by using a parallelized Particle Swarm Optimization (PSO) algorithm, which searches for reducing the rows current difference. The proposed algorithm is implemented in MATLAB/Simulink and is numerically compared with some related works. Results show the simplicity and higher power outputs of the proposed algorithm compared to published papers while ensuring less simulation runtime. Depending on the shading pattern, the power enhancement is different. The maximum power increase is 26.5 percent of the total array output power.

Nowadays, there is much attention for planning of container terminals in the global trade centers. The high cost of quay cranes motivates both scholars and industrial practitioners especially in the last decade to develop novel optimization models to address this dilemma. This study proposes a coordinated optimization model to cover both Quay Crane Scheduling Problem (QCSP) and Quay Crane Assignment Problem (QCAP) as among the first attempts in this area. Another main contribution of this paper is to apply a recent nature-inspired algorithm called Red Deer Algorithm (RDA). The RDA revealed its performance for a variety of combinatorial optimization problems in different real-world applications. This is the first attempt in the literature to employ this recent metaheuristic to solve the proposed Coordinated Quay Crane Scheduling and Assignment Problem (CQCSAP). Finally, an extensive comparison discussion is considered to reveal the main benefits of the proposed optimization model and solution algorithm.

This paper integrates competitive pricing and network design problems for the short life cycle products. The pricing problem determines selling prices of the products for different life cycle phases in a competitive market, as well as acquisition management of returned products. Besides, the selling and acquisition prices are related to the distance between distribution centers and customers. The network design problem aims to determine network flow and fleet assignment in each route. The proposed model is solved by various methods including exact and meta-heuristic approaches. The model and solving approaches have been validated and verified by several simulated examples and sensitivity analyses. Considering life cycle phases, competitive pricing, and transshipment problems as an integrated model, provides a new approach for the optimum solutions, which makes it more practical for application of real cases of short life cycle products. The results showed how the competition and fleet assignment influenced the optimum solution.

Isothermal redox kinetics of as-received Co3O4 (AC), 1 h ball milled Co3O4 (BC), and 1 h ball milled Co3O4-15wt.% Fe2O3 (BCF) was investigated at various temperatures (1130, 1100, 1070, and 1040 °C for reduction and 830, 860, and 890°C for re-oxidation) by thermogravimetric method. It was found that mechanical activation with and without Fe2O3 addition decreases the rate of reduction in all isothermal reduction temperatures, while it improves the rate of re-oxidation in lower re-oxidation temperatures. Mechanical activation with and without Fe2O3 addition preserves and decreases the rate of re-oxidation at higher re-oxidation temperatures, respectively. In addition, according to the results, the re-oxidation kinetics was slower than reduction kinetics. A model-free method was used to calculate the redox activation energies. It was found that mechanical activation individually increases the reduction activation energy, while mechanical activation along with Fe2O3 addition decreases the reduction activation energy in comparison with as-received Co3O4. The results showed that reduction activation energies of AC, BC, and BCF samples varies depending on the reacted fraction (α) and are in the range of  140.6 – 166.6 kJ/mol, 175.5 – 213.7 kJ/mol and 111.5 – 121.3 kJ/mol, respectively. The results also showed that although both mechanical activations with and without Fe2O3 addition decreases the re-oxidation activation energy in comparison with as-received cobalt oxide, but the impact of mechanical activation without Fe2O3 addition on activation energy decline, is higher. Moreover, it was found that activation energies for the re-oxidation of AC, BC, and BCF samples are negative, variations depending on the reacted fraction (α), and are in the range of  -76.8 to -133.5 kJ/mol, -440.2  to -471.9 kJ/mol, and -190.8 to -196.05 kJ/mol, respectively.

Temperature control during the cutting process with different parameters such as cutting velocity and applying water cooling is essential to decrease the cutting force, increase the life of the cutting tool and decrease the machined surface temperature of work-piece. In this research, the temperature of machined surface and the chip-tool interface in orthogonal cutting process of Ti-6Al-4V were investigated using smooth particle hydrodynamics (SPH) method. The effects of cooling with different speeds and temperatures of water flow on the temperature of these surfaces were studied. The non-cooling model is validated using experimental results. According to the results, a water flow with speed of 0.25 m/s at 20°C temperature causes a significant decreasing in the cutting force and the temperature on machined surface and chip-tool interface.

There are some large scale orebodies that extend from surface to the extreme depths of the ground. Such orebodies should be extracted by a combination of surface and underground mining methods. Economically, it is highly important to know the limit of upper and lower mining activities. This concern leads the mine designers to the transition problem, which is one of the most complicated problems in mining industry. The transition problem is categorized as a strategic one and is formulated in the form of long-term production scheduling problems. This implies that the transition problem is highly affected by the uncertainties that are rooted in the quantity and quality of an explored orebody. The current study aims to evaluate the effects of geological uncertainty on transition depth. To this aim, an integer programming (IP) model was executed on different simulations of an orebody. The results indicate that the net present value (NPV) of the deterministic solution is greater than that of the basic alternative. However, the uncertainty-based solutions show that the NPV of the whole mining operation is lower than the basic and deterministic solutions mostly (more than 72% of the simulations). Nevertheless, there are some rare cases in which the NPV of the operation may increase ideally up to 2.5 % due to development of the pit bottom downward. Finally, because of a negligible difference between the average NPV of the simulations and that of basic alternative, it is expected that the primitive pit bottom would play the role of transition depth.