A Review of the Building Blocks of Silicon Photonics: From Fabrication Perspective

Silicon photonics is a disruptive semiconductor technology that taps into the extraordinary properties of light while taking full advantage of the already matured CMOS processes developed in the semiconductor industry. However, just like electronic industry in the 1970s, currently, Silicon Photonics is in its infancy. The fundamental building blocks of silicon photonics such as waveguides, lasers, modulators, etc. are yet to be fully optimized for low-cost-mass-manufacturing. In this paper, the current state-of-the-art related to developing and optimizing these aforementioned key components will be presented. The challenges of process integration regarding Silicon photonics will also be discussed

ACTIVATION SCAVENGING OF AEROSOL : EFFECT OF TURBULENCE AND AEROSOL-COMPOSITION

The interaction of aerosol particles with solar radiation significantly contributes to the global radiation balance. The magnitude of this aerosol-radiation interaction, among other parameters, depends on different aerosol properties, including how readily these particles would act as cloud condensation nuclei (CCN). These properties are governed by the formation and scavenging processes of aerosol. This dissertation explores some of these scavenging processes. Favorable humidity and preexisting aerosol particles acting as CCN are the sine qua non conditions to form cloud droplets in Earth’s atmosphere. Forming cloud droplets (known as activation), meanwhile, acts as a wet scavenging mechanism for those CCN. Given the required humidity, size, and chemical composition of an aerosol particle, determine its probability to activate. Through targeted experiments in a cloudy, turbulent environment in Michigan Tech’s Π chamber, we show that turbulent fluctuation blurs correspondence between activation and a particle’s size and chemical composition. We also show that turbulence enhances the activation efficiency and can mimic the effect of heterogeneity in the size and chemical composition of the aerosol particles. In the absence of clouds, we discuss how turbulence affects the dry scavenging of aerosol particles. Finally, we propose an operational protocol to improve the temporal resolution of an instrument that counts the number of CCN present in an environment as a function of supersaturation (i.e., relative humidity \u3e 100%

Compact Modeling and Rapid Simulation of Silicon Photonic Micro-Disk and Ring Modulators

Microdisk or microring modulators (MDMs or MRMs) realize compact electro-optic modulation in active silicon photonics (SiP) foundry platforms. A key advantage of these resonant modulators is that they readily implement dense wavelength division multiplexing (DWDM) in optical interconnects by tuning and locking the MDMs/MRMs to the DWDM wavelength grid. Compact modeling of static and transient dynamics of these modulators is important for co-simulation with CMOS drivers and wavelength stabilization circuits. This work presents the first compact model for microdisk modulators with a novel approach that uses experimental measurements and allows rapid and accurate simulation. This approach employs coupled real-valued differential equations with analytic signals in Verilog-A, leading to a 7X speed up in transient simulation time over the current art while enhancing accuracy. Since the model is generalized, it can also model microring resonators in addition to MDMs. The model also includes thermo-optic tuning for MDM/MRM with an embedded microheater, which is essential for simulations involving resonant wavelength stabilization

Flexible and Surface Modified ZnSnO3 Nanocubes for Enhanced Piezoelectric Power Generation and Wireless Sensory Application

Piezoelectric systems and their mechanisms are held in high regard, due to their cost-effective structure and mechanical proficiency to harvest renewable energy. In the present article, we propose an aluminum-doped zinc stannate (ZnSnO3) piezoelectric nanogenerator that can be employed for the harvest of energy and sensory applications. In order to ensure and further enrich the piezoelectric mechanics and product outcome in our device, ZnSnO3 was doped with 1 wt% to 5 wt% of aluminum nanoparticles. We reported that 2 wt% of aluminum-doped ZnSnO3 showed the highest electrical output in terms of open circuit voltages and short circuit current. The nanogenerator device achieved an average open-circuit voltage of 80 V to 175 V with a frequency range of 60 BPM to 240 BPM. This presented to be an unprecedented electrical output in comparison to period ZnSnO3-based piezoelectric nanogenerators. With the presented high output-to-size ration taken into consideration, the device was installed into a helmet as an energy harvester and wireless human motion sensor which can harvest energy as well as can detect and transmit signals from mechanical human movement. Thus, transmuting a regular helmet into a smart helmet- indicates a promising future for the field of piezoelectric sensors

Tidal River Siltation and its Impact in the Coastal Parts of Bangladesh

The study area is located in the south-western coastal part of Bangladesh and belongs to the lower deltaic plain of the Ganges delta system, which lies in the Rampal upazila of Bagherhat district. The area is more or less flat with elevation ranges from 1.0 to 2.0 m above mean sea level (MSL) and is blanketed with fluvio-tidal deposits of sandy silt, clayey silt and clay. Right now, water logging is one of the major problems in the area. The present paper is an attempt to expose the causes of water logging as well as its consequences. The satellite images of the last few decades, existing statistical records and simultaneous field checking were employed in this study, which reveals that natural as well as anthropogenic factors are responsible for water logging problem. The rivers and their link channels in the areas are influenced by tidal water regularly. The Water Development Board (WDB) was built embankments along the river courses as well as constructed sluice gates on the head of the tidal creeks to protect the area from regular tidal flooding and sea water intrusion. During monsoon, when rivers carry huge amount of water and sediments due to torrential rain, and these rising waters overtop the natural levees which were artificially modified and raised by coastal embankments. Consequently, the sediments drop down inside the channel and near channel bank rather in the nearby tidal plain. As a result, channels are gradually congested due to siltation, whereas tidal plain areas gradually lower due to subsidence and lack of sedimentation. Moreover, many sluice gates were constructed on the river courses in the coastal areas which also aggravate the situation. Daudkhali river is one of the main rivers in the study area. Image interpretation depicts that in 1977 the width of this river was nearly about 200 m all through its course and the river maintained this width up to 1990. But due to embankments the river starts to squeeze and the width of the river reached about 100 m in 2000. But in 2014, the river was nearly abandoned. A sluice gate was constructed on the course of the river about 30 years ago near Foila Bazar. The sediments carried by the river started to deposit in the mouth of the sluice gate which gradually choked the opening of the gate and now the gate is nearly blocked. During the rainy season,the river cannot carry excess water resulting flooding and water logging for long time. The presence of thick finer sediments in the subsurface as well as climate change further prolongates the situations. Finally, for sustainable development of the area,it is necessary to carry out different development activities with consideration of delta building processes

Effectiveness of Transformer Models on IoT Security Detection in StackOverflow Discussions

The Internet of Things (IoT) is an emerging concept that directly links to the billions of physical items, or "things", that are connected to the Internet and are all gathering and exchanging information between devices and systems. However, IoT devices were not built with security in mind, which might lead to security vulnerabilities in a multi-device system. Traditionally, we investigated IoT issues by polling IoT developers and specialists. This technique, however, is not scalable since surveying all IoT developers is not feasible. Another way to look into IoT issues is to look at IoT developer discussions on major online development forums like Stack Overflow (SO). However, finding discussions that are relevant to IoT issues is challenging since they are frequently not categorized with IoT-related terms. In this paper, we present the "IoT Security Dataset", a domain-specific dataset of 7147 samples focused solely on IoT security discussions. As there are no automated tools to label these samples, we manually labeled them. We further employed multiple transformer models to automatically detect security discussions. Through rigorous investigations, we found that IoT security discussions are different and more complex than traditional security discussions. We demonstrated a considerable performance loss (up to 44%) of transformer models on cross-domain datasets when we transferred knowledge from a general-purpose dataset "Opiner", supporting our claim. Thus, we built a domain-specific IoT security detector with an F1-Score of 0.69. We have made the dataset public in the hope that developers would learn more about the security discussion and vendors would enhance their concerns about product security

Formulation of biofertilizers from oil palm empty fruit bunches and plant growth-promoting microbes: A comprehensive and novel approach towards plant health

Our heavy reliance on chemical fertilizers for agricultural practices has fostered the development of a vast industry that is producing chemicals that are toxic not only for humans but also for the environment. Biofertilizers are microbial formulations containing native plant growth-promoting microorganisms (PGPM) which have the potential to enhance plant growth either directly or indirectly by producing different types of phytohormones, iron-binding metabolites (siderophores), and solubilizing soil nutrients and minerals. The positive impacts on crop growth and development were documented by many researchers while using biofertilizers. Thus, biofertilizers offer enormous promise for sustainable agriculture, particularly in the face of climate change. Despite the growing interest in this technology, its entire potential remains untapped. This review collectively describes the potential use of empty fruit bunches (EFB) biomass as a biofertilizer for sustainable agricultural practices and the roles of plant growth-promoting microbes (PGPM) in plant growth and development. Attempts were also made to give insights into the oil palm industry in Malaysia and the nutrient profile of EFB biomass. We concluded that more research, fund and development activities are needed to improve traits of beneficial microbes that will potentially enhance the biological pathway of different biocompounds production and find solutions for the current issues related to converting EFB biomass into biofertilizers

Effects of Liming on Soil Properties and Its Roles in Increasing the Productivity and Profitability of the Oil Palm Industry in Malaysia

As global demand for edible oil increases, palm oil-producing countries in Southeast Asia are experiencing a rapid expansion of agricultural land for industrial oil palm cultivation by converting existing agricultural lands and some tropical rainforests; however, soil acidity and nutrient depletion are two major constraints in oil palm cultivation in the tropics. Several factors may cause soil acidification, including natural processes, industrial pollutants and extensive agricultural production. Soil acidity increases the leaching of many essential plant nutrient elements and the availability of toxic elements by modifying various geochemical and biological reactions in the soil. Even though acidic soil is less fertile, the productivity of tropical soil is among the highest in the world once the chemical constraints are removed by applying a sufficient quantity of lime and fertilizers. Lime is a widely used alkali to improve soil fertility by retaining nutrients, increasing soil biota, decreasing heavy-metal availability and potentially achieving resistance against Ganoderma disease at oil palm estates. Liming materials are not simple compounds with consistent chemical properties; thus, selecting the appropriate lime must be based on soil type and price compared to the products neutralizing value, composition, and fineness. Since the primary aim of liming is to improve soil pH, numerous reviews have been reported on the impacts of soil acidification, nutrient deficiencies and heavy-metal toxicity; however, no extensive review has been published that discusses the effects of liming on oil palm growth and yield. It is not enough to emphasize just soil impacts alone, and a thorough assessment must also be given on crops (oil palm) and soil biodiversity. This review synthesizes current understanding and introduces a holistic approach to provide insights into the far-reaching effects liming has on the biogeochemical properties of tropical soil and oil palm crops

Bengali Fake Review Detection using Semi-supervised Generative Adversarial Networks

This paper investigates the potential of semi-supervised Generative Adversarial Networks (GANs) to fine-tune pretrained language models in order to classify Bengali fake reviews from real reviews with a few annotated data. With the rise of social media and e-commerce, the ability to detect fake or deceptive reviews is becoming increasingly important in order to protect consumers from being misled by false information. Any machine learning model will have trouble identifying a fake review, especially for a low resource language like Bengali. We have demonstrated that the proposed semi-supervised GAN-LM architecture (generative adversarial network on top of a pretrained language model) is a viable solution in classifying Bengali fake reviews as the experimental results suggest that even with only 1024 annotated samples, BanglaBERT with semi-supervised GAN (SSGAN) achieved an accuracy of 83.59% and a f1-score of 84.89% outperforming other pretrained language models - BanglaBERT generator, Bangla BERT Base and Bangla-Electra by almost 3%, 4% and 10% respectively in terms of accuracy. The experiments were conducted on a manually labeled food review dataset consisting of total 6014 real and fake reviews collected from various social media groups. Researchers that are experiencing difficulty recognizing not just fake reviews but other classification issues owing to a lack of labeled data may find a solution in our proposed methodology