A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.     

Agronomic performance of high oleic,low linolenic soybean in Tennessee

Soybean oil hydrogenation alters the linolenic acid molecule to prevent the oil from becoming rancid, however, health reports have indicated trans-fat caused by hydrogenation, is not generally regarded as safe. Typical soybeans contain approximately 80 g kg⁻¹ to 120 g kg⁻¹ linolenic acid and 240 g kg⁻¹ of oleic acid. In an effort to accommodate the need for high-quality oil, the United Soybean Board introduced an industry standard for a high oleic acid greater than 750 g kg⁻¹ and linolenic acid less than 30 g kg⁻¹ oil. By combing mutations in the soybean plant at four loci, FAD2-1A and FAD2-1B, oleate desaturase genes and FAD3A and FAD3C, linoleate desaturase genes, and seed oil will not require hydrogenation to prevent oxidation and produce high-quality oil. In 2017 and 2018, a study comparing four near-isogenic lines across multiple Tennessee locations was performed to identify agronomic traits associated with mutations in FAD3A and FAD3C loci, while holding FAD2-1A and FAD2-1B constant in the mutant (high oleic) state. Soybean lines were assessed for yield and oil quality based on mutations at FAD2-1 and FAD3 loci. Variations of wild-type and mutant genotypes were compared at FAD3A and FAD3C loci. Analysis using a generalized linear mixed model in SAS 9.4, indicated no yield drag or other negative agronomic traits associated with the high oleic and low linolenic acid genotype. All four mutations of fad2-1A, fad2-1B, fad3A, and fad3C were determined as necessary to produce a soybean with the new industry standard (>750 g kg⁻¹ oleic and <30 g kg⁻¹ linolenic acid) in a maturity group-IV-Late cultivar for Tennessee growers.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Enhanced electrochemical performance of LiNi0.8Co0.1Mn0.1O2 via titanium and boron co-doping

Titanium and boron are simultaneously introduced into LiNi_0.8Co_0.1Mn_0.1O₂ to improve the structural stability and electrochemical performance of the material. X-ray diffraction studies reveal that Ti⁴⁺ ion replaces Li⁺ ion and reduces the cation mixing; B³⁺ ion enters the tetrahedron of the transition metal layers and enlarges the distance of the [LiO₆] layers. The co-doped sample has spherical secondary particles with elongated and enlarged primary particles, in which Ti and B elements distribute uniformly. Electrochemical studies reveal the co-doped sample has improved rate performance (183.1 mAh·g^-1 at 1 C and 155.5 mAh·g^-1 at 10 C) and cycle stability (capacity retention of 94.7% after 100 cycles at 1 C). EIS and CV disclose that Ti and B co-doping reduces charge transfer impedance and suppresses phase change of LiNi_0.8Co_0.1Mn_0.1O_2.     

Description of the thermodynamic properties and fluid-phase behavior of aqueous solutions of linear,branched, and cyclic amines

The SAFT-γ Mie group-contribution equation of state is used to represent the fluid-phase behavior of aqueous solutions of a variety of linear, branched, and cyclic amines. New group interactions are developed in order to model the mixtures of interest, including the like and unlike interactions between alkyl primary, secondary, and tertiary amine groups (NH₂, NH, N), cyclic secondary and tertiary amine groups (cNH, cN), and cyclic methine-amine groups (cCHNH, cCHN) with water (H₂O). The group-interaction parameters are estimated from appropriate experimental thermodynamic data for pure amines and selected mixtures. By taking advantage of the group-contribution nature of the method, one can describe the fluid-phase behavior of mixtures of molecules comprising those groups over broad ranges of temperature, pressure, and composition. A number of aqueous solutions of amines are studied including linear, branched aliphatic, and cyclic amines. Liquid–liquid equilibria (LLE) bounded by lower critical solution temperatures (LCSTs) have been reported experimentally and are reproduced here with the SAFT-γ Mie approach. The main feature of the approach is the ability not only to represent accurately the experimental data employed in the parameter estimation, but also to predict the vapor–liquid, liquid–liquid, and vapor–liquid–liquid equilibria, and LCSTs with the same set of parameters. Pure compound and binary phase diagrams of diverse types of amines and their aqueous solutions are assessed in order to demonstrate the main features of the thermodynamic and fluid-phase behavior.     

The role of microbial electrogenesis in regulating methane and nitrous oxide emissions from constructed wetland-microbial fuel cell

This study assesses a sustainable solution to greenhouse gases (GHGs) mitigation using constructed wetland-microbial fuel cells (CW-MFC). Roots of wetland plant Acorus Calamus L. are placed in biological anode to better enable anode microorganisms to obtain rhizosphere secretion for power improvement. Three selected cathode materials have a large difference in GHG emissions, and among them, carbon fiber felt (CFF) shows the lowest emissions of methane and nitrous oxide, which are 0.77 ± 0.04 mg/(m²·h) and 130.78 ± 13.08 μg/(m²·h), respectively. The CFF CW-MFC achieves the maximum power density of 2.99 W/m³. As the influent pH value is adjusted from acidic to alkaline, the GHGs emissions are reduced. The addition of Ni inhibits GHGs emission but decreases the electricity, the power density is reduced to 1.09 W/m³, and the methane and nitrous oxide emission fluxes decline to 0.20 ± 0.04 mg/(m²·h) and 15.49 ± 1.86 μg/(m²·h), respectively. Low C/N ratio reduces methane emission, while high C/N ratio effectively inhibits nitrous oxide emission. At the influent pH 8 and C/N = 5:1, the methane emission flux is approximately 10.60 ± 0.27 mg/(m²·h), and the nitrous oxide emission flux is only 10.90 ± 1.10 μg/(m²·h). Based on the above experimental results by controlling variable factors, it is proposed that CW-MFC offers an environment-friendly solution to regulate GHG emissions.     

基于TRNSYS的茯砖茶生产工艺能源系统节能环保特性研究

茯砖茶发酵、干燥过程中，烘房内温湿度稳定性和能源系统低能耗是保证茯砖茶品质与成本的重要因素。本文采用TRNSYS仿真与实验研究相结合的方法，对咸阳某茯砖茶厂实际使用的空气源热泵系统进行建模，通过研究各季节典型代表月烘房温湿度的波动情况，确定该空气源热泵系统在全年的运行状态是否满足工艺要求，在此基础上，对比了该系统在全年可运行季节代表月与该生产厂房早期使用的燃气锅炉系统的能耗仿真结果，对空气源热泵系统的节能与环保特性进行研究。结果表明：由于夏季送风质量流量过大且室外空气含湿量较高，7月烘房温湿度不满足工艺要求。热泵系统在1、4、10月的总标煤消耗量的平均值是锅炉系统的44.42%，平均CO2、SO2、NOx排放量分别为锅炉系统的34.13%、44.1%、40.60%。在茯砖茶发酵、干燥的过程中，相比于燃气锅炉系统，空气源热泵系统具有更好的节能与环保特性。