Search results for: pose normalization

Authors: David Yartel

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Drawing on the current state of software engineering and information technology in Ghana, the study documents its significant contribution to the development of Ghanaian industries. The study focuses on the application of modern trends in technology and the barriers faced in the area of software engineering and information technology. A thorough analysis of a dozen of interviews with stakeholders in software engineering and information technology via interviews reveals how modern trends in software engineering pose challenges to the industry in Ghana. Results show that to meet the expectation of modern software engineering and information technology trends, stakeholders must have skilled professionals, adequate infrastructure, and enhanced support for technology startups. Again, individuals should be encouraged to pursue a career in software engineering and information technology, as it has the propensity to increase the efficiency and effectiveness of work-related activities. This study recommends that stakeholders in software engineering and technology industries should invest enough in training more professionals by collaborating with international institutions well-versed in the area by organizing frequent training and seminars. The government should also provide funding opportunities for small businesses in the technology sector to drive creativity and development in order to bring about growth and development.

Keywords: software engineering, information technology, Ghana, development

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Authors: Yuqing Sun

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Chinese has been regarded as one of the most difficult languages in learning due to its complex spelling structure, difficult pronunciation, as well as its varying forms. Since vocabulary acquisition is the basic process to acquire a language, to express yourself, to compose a sentence, and to conduct a communication, so learning the vocabulary is of great importance. However, the vocabulary contains pronunciation, spelling, recognition and application which may seem as a huge work. This may pose a question for the language teachers (language teachers in China who teach Chinese to the foreign students): How to teach them in an effective way? Traditionally, teachers have no choice but teach it all by themselves, then with the development of technology, they can use computer as a tool to help them (Computer Assisted Language Learning or CALL). Now, they move into the Mobile Assisted Language Learning (MALL) method to guide their teaching, upon which the appraisal is convincing. It diversifies the learning material and the way of output, which can activate learners’ curiosity and accelerate their understanding. This paper will focus on actual case studies occurring in the universities in China of teaching the foreign students to learn Chinese, and the analysis of the utilization of WeChat channel as an example of MALL model to explore the active role of MALL to enhance the effectiveness of Chinese vocabulary acquisition.

Keywords: Chinese, vocabulary acquisition, MALL, case

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Authors: M. R. Ahmad, I. Musirin, M. M. Othman, N. A. Rahmat

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Plug-in Hybrid-Electric Vehicle (PHEV) has gained immense popularity in recent years. PHEV offers numerous advantages compared to the conventional internal-combustion engine (ICE) vehicle. Millions of PHEVs are estimated to be on the road in the USA by 2020. Uncoordinated PHEV charging is believed to cause severe impacts to the power grid; i.e. feeders, lines and transformers overload and voltage drop. Nevertheless, improper PHEV data model used in such studies may cause the findings of their works is in appropriated. Although smart charging is more attractive to researchers in recent years, its implementation is not yet attainable on the street due to its requirement for physical infrastructure readiness and technology advancement. As the first step, it is finest to study the impact of charging PHEV based on real vehicle travel data from National Household Travel Survey (NHTS) and at present charging rate. Due to the lack of charging station on the street at the moment, charging PHEV at home is the best option and has been considered in this work. This paper proposed a technique that comprehensively presents the impact of charging PHEV on power system networks considering huge numbers of PHEV samples with its traveling data pattern. Vehicles Charging Load Profile (VCLP) is developed and implemented in IEEE 30-bus test system that represents a portion of American Electric Power System (Midwestern US). Normalization technique is used to correspond to real time loads at all buses. Results from the study indicated that charging PHEV using opportunity charging will have significant impacts on power system networks, especially whereas bigger battery capacity (kWh) is used as well as for higher penetration level.

Keywords: plug-in hybrid electric vehicle, transportation electrification, impact of charging PHEV, electricity demand profile, load profile

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Authors: Peri Harish Kumar, Rafique Umer Harvitkar

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Background: The emergency department mandates maximum efficacy in the utilization of the available resources. Non-urgent patient visits pose a serious concern to the treatment, patient triage, and resources available. Aims and Objectives: We conducted a retrospective case-control study of the emergency department patient list from October 2019 to November 2022. A total of 839 patients formed part of the study. Somatic complaints, vital signs, diagnostic test results, admission to the hospital, etc., were some of the criteria used for the categorization of patients. Results: The proportion of non-urgent visits varied from 7.2% to 43%, with a median of 21%. Somatic complaints were the least associated with further hospital admissions (n=28%), while diagnostic test results were the most significant indicator of further hospital admissions (n=74%). Effective triage helped minimize emergency department admissions by 36%. Conclusion: Our study shows that effective triaging, patient counselling, and round-the-clock consumable monitoring helped in the effective management of patients admitted and also significantly helped provide treatment to the patients most in need.

Keywords: urgent visits, non-urgent visits, traiging, emergency department admissions

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Authors: Philip Tachin

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Despite the positive contributions that religion has impacted human society, religious discrimination and violence also have been growing globally with extreme negative effects on human life and social relationships. Believers in religious extremism are motivated by a sense of exhibiting true religious piety in which case they do not only withhold their practical benevolence from those who do not belong to their faith but they even seek the elimination of other adherents from human existence. This phenomenon has a very high magnitude in Nigeria over the years, which deserves more research for the purpose of finding sustainable solutions to the problem. Calvin believed that true religious piety must, among other things, be categorized in personal and corporate positive social actions that esteem human needs irrespective of ethnic, ideological and belief differences. It is therefore appropriate to pose the following questions: Should true religious piety be seen in terms of how the actions of adherents positively impact human society? Could Calvin’s idea on this issue be very significant and helpful in the context of the Nigerian situation? In answering these questions, this research will limit its investigation to Calvin’s Institutes and some of his Commentaries. The goal of this research is to offer an instructive orientation to the readers that will help in building a more tolerable, peaceful, and a free and virtuous society.

Keywords: Calvin, human good, religious piety, virtuous society

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Hong Beom Hur

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Politics in America is polarized. The best illustration of this is the 2016 presidential election result map. States with megacities like California, New York, Illinois, Virginia, and others are marked blue to signify the color of the Democratic party. States located in inland and south like Texas, Florida, Tennesse, Kansas and others are marked red to signify the color of the Republican party. Such a stark difference between two colors, red and blue, combined with geolocations of each state with their borderline remarks one central message; America is divided into two colors between urban Democrats and rural Republicans. This paper seeks to defy the visualization by pointing out its limitations and search for alternative ways to visualize the 2016 election result. One such limitation is that geolocations of each state and state borderlines limit the visualization of population density. As a result, the election result map does not convey the fact that Clinton won the popular vote and only accentuates the voting patterns of urban and rural states. The paper seeks whether an alternative narrative can be observed by factoring in the population number into the size of each state and manipulating the state borderline according to the normalization. Yet another alternative narrative may be reached by factoring the size of each state by the number of the electoral college of each state by voting and visualize the number. Other alternatives will be discussed but are not implemented in visualization. Such methods include dividing the land of America into about 120 million cubes each representing a voter or by the number of whole population 300 million cubes. By exploring these alternative methods to visualize the politics of the 2016 election map, the public may be able to question whether it is possible to be free from the narrative of the divide-conquer when interpreting the election map and to look at both parties as a story of the United States of America.

Keywords: 2016 U.S. presidential election, data visualization, population scale, geo-political

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Authors: Sajjad Shojaeidoust, Mohsen Ghanbarzadeh, Abdolhamid Habibi

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Exercise-induced bronchospasm (EIB) is a transitory condition of airflow obstruction that is associated with physical activities. It is noted that high ventilation can lead to an increase in the heat and reduce in the moisture in airways resistance of trachea. Also causes of pathophysiological mechanism are EIB. Accordingly, studying some parameters of pulmonary function (FVC, FEV1) among active people seems quintessential. The aim of this study was to analyze bronchospasm following the implementation of a program of maximum aerobic exercise in active men at Chamran University of Ahwaz. Method: In this quasi-experimental study, the population consisted of all students at Chamran University. Among from 55 participants, of which, 15 were randomly selected as the experimental group. In this study, the size of the maximum oxygen consumption was initially measured, and then, based on the maximum oxygen consumed, the active individuals were identified. After five minutes’ warm-up, Strand treadmill exercise test was taken (one session) and pulmonary parameters were measured at both pre- and post-tests (spirometer). After data normalization using KS and non-normality of the data, the Wilcoxon test was used to analyze the data. The significance level for all statistical surveys was considered p≤0/05. Results: The results showed that the ventilation factors and bronchospasm (FVC, FEV1) in the pre-test and post-test resulted in no significant difference among the active people (p≥0/05). Discussion and conclusion: Based on the results observed in this study, it appears that pulmonary indices in active individuals increased after aerobic test. The increase in this indicator in active people is due to increased volume and elasticity of the lungs as well. In other words, pulmonary index is affected by rib muscles. It is considered that progress over respiratory muscle strength and endurance has raised FEV1 in the active cases.

Keywords: aerobic active maximum, bronchospasm, pulmonary function, spirometer

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Ayobami P. Olatunji, Saadat Ibiyeye, Abdulaziz Ibiyeye, Tahir M. Khan

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Digital evidence has become a cornerstone in criminal investigations due to the vast amount of information available in digital form. Despite its prevalence, this evidence is often met with skepticism in court proceedings because of its inherently volatile nature. Traditional forensic processes, defined predominantly by technology experts, emphasize technical details in evidence collection while often neglecting legal procedures. This gap can pose significant challenges for legal practitioners in understanding and applying digital forensics. As digital evidence increasingly influences future cases, a cohesive framework integrating both technical and legal perspectives is essential. We propose a comprehensive techno-legal framework designed to bridge this gap. Our framework integrates key aspects of collection, preservation, examination, and documentation with legal components such as case building, certificate of compliance, cross-examination, and authorization. This balanced approach aims not to replace existing evidence presentation principles but to enhance the seamless integration of digital evidence into legal proceedings, addressing the common issues that lead to its dismissal.

Keywords: evidence presentation, warrant, digital-forensic, certificate of compliance, legal procedures, computer crime, violation, investigation cybercrime

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Authors: Emmanuel Adu-Ofori, Richard Amfo-Otu, Isaac O. A. Hodgson

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The study was conducted to determine the treatment performance of waste stabilization ponds in Akosombo. A total of 15 samples were taken for four consecutive months from the inlet, facultative pond and outlet of maturation pond. The samples were preserved and transported to Water Research Institute for laboratory analysis. The wastewater quality parameters analysed to assess the treatment performance were total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia and phosphate. The results of the laboratory analysis showed that the ponds achieved TSS, BOD and COD removals of about 30, 82 and 75 per cent respectively. Statistically, the BOD (t = 10.27, p = 6.68 x 10-6) and COD (t = 4.23, p = 0.0029) of the raw sewage were significantly different from the total effluent at 95% confidence interval. The ammonia and phosphate removal was as high as 92% and 84% respectively. The quality parameters analysed for the final effluent from the Waste Stabilisation Pond was within the EPA guideline values. The general treatment performances were very good with respect to the parameters studied and does not pose threat to the receiving water body. A further study to examine the bacteriological treatment performance was recommended.

Keywords: waste stabilization pond, wast water, treatment performance, nutrient, Ghana

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Authors: Vincent Kheswa

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X-rays are ionizing electromagnetic radiation that is used in various industries such as computed tomography scans, dental X-rays, and screening freight trains. However, they pose health risks to humans if they are not shielded properly. In recent years, many researchers around the globe have been searching for nontoxic best possible glass materials for shielding X-rays. In this work, the x-ray shielding properties of 45Na₂O + 10 Bi₂O₃ + (5 - x)TiO₂+ (x) Nb₂O₅ + 40 P₂O₅, were x = 0, 1, 3, 5 mol%, glass materials were studied. The results revealed that the glass sample with the highest TiO2 content has the highest mass and linear attenuation coefficients and lowest half-value thickness, tenth-value thickness and mean-free path in the 20 to 80 keV energy region. The sample with 3 mol% of Nb₂O₅ has the highest mass and linear attenuation coefficients and the lowest half-value thickness, tenth-value thickness, and mean-free path at 15 keV and photon energies between 80 to 300 keV. It was, therefore, concluded that 45Na₂O + 10 Bi₂O₃ + 5 TiO₂ + 40 P₂O₅ glass is best for shielding x-rays of energies between 20 and 80 keV, while 45Na₂O + 10 Bi₂O₃ + 2 TiO₂ + 3 Nb₂O₅ + 40 P₂O₅ is best for shielding 15 keV x-rays and x-rays of energies between 80 keV and 300 keV.

Keywords: bismuth-titanium-phosphate glass, x-ray shielding, LAC, MAC, radiation shielding

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Authors: O. O. Olawusi-Peters, K. I. Adejugbagbe

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The concentration of heavy metal (Cd, Pb, Fe, Zn, Cu) in Clarias gariepinus collected from fish markets; Fanibi (Station I) and Fiwasaye (Station II) in Akure metropolis, Ondo state, Nigeria were investigated to ascertain the safety for the consumers. 60 samples were collected from the two markets in three batches (I, II, III) for a period of six months and analyzed for heavy metals in the gills and muscles of the fish. Also, the Health Risk Index (HRI) was used to determine the health risk of these metals to the consumer. The results showed that the investigated metal concentration was higher in station I than station II, except Pb having higher concentration in station II than station I. In both stations, the highest concentration of Fe was recorded in the gills (12.60 ± 1.51; 6.94 ± 1.38) and muscles (3.72 ± 0.09; 3.86 ± 0.33) of samples in batch I. Also, the HRI revealed that consumption of Clarias gariepinus from these study areas did not pose any health risk (HRI < 1). In addition, concentrations of the heavy metals were all below the permissible limits recommended by FAO/WHO.

Keywords: health risk index, heavy metals, clarias gariepinus, akure metropolis, fish monger

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Authors: D. Subedi, S. Pradhan

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Current transformers are an integral part of power system because it provides a proportional safe amount of current for protection and measurement applications. However when the power system experiences an abnormal situation leading to huge current flow, then this huge current is proportionally injected to the protection and metering circuit. Since the protection and metering equipment’s are designed to withstand only certain amount of current with respect to time, these high currents pose a risk to man and equipment. Therefore during such instances, the CT saturation characteristics have a huge influence on the safety of both man and equipment and also on the reliability of the protection and metering system. This paper shows the effect of burden on the Accuracy Limiting factor/ Instrument security factor of current transformers and also the change in saturation characteristics of the CT’s. The response of the CT to varying levels of overcurrent at different connected burden will be captured using the data acquisition software LabVIEW. Analysis is done on the real time data gathered using LabVIEW. Variation of current transformer saturation characteristics with changes in burden will be discussed.

Keywords: accuracy limiting factor, burden, current transformer, instrument security factor, saturation characteristics

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Authors: Muhammad Waqar Ashraf

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Selected heavy metals, namely Cu, Zn, Fe, Mn, Cd, Pb, and As, in seven popular varieties of edible vegetable oils collected from Saudi Arabia, were determined by graphite furnace atomic absorption spectrometry (GF-AAS) using microwave digestion. The accuracy of procedure was confirmed by certified reference materials (NIST 1577b). The concentrations for copper, zinc, iron, manganese, lead and arsenic were observed in the range of 0.035 - 0.286, 0.955 - 3.10, 17.3 - 57.8, 0.178 - 0.586, 0.011 - 0.017 and 0.011 - 0.018 µg/g, respectively. Cadmium was found to be in the range of 2.36 - 6.34 ng/g. The results are compared internationally and with standards laid down by world health agencies. A risk assessment study has been carried out to assess exposure to these metals via consumption of vegetable oils. A comparison has been made with safety intake levels for these heavy metals recommended by Institute of Medicine of the National Academies (IOM), US Environmental Protection Agency (US EPA) and Joint FAO/WHO Expert Committee on Food Additives (JECFA). The results indicated that the dietary intakes of the selected heavy metals from daily consumption of 25 g of edible vegetable oils for a 70 kg individual should pose no significant health risk to local population.

Keywords: vegetable oils, heavy metals, contamination, health risk assessment

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Authors: Nurul Noraziemah Mohd Pauzi, Muhammad Fauzi Mohd Zain

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The rapid advance in the electronic industry has led to the increase amount of the waste cathode ray tube (CRT) devices. The management of CRT waste upon disposal haves become a major issue of environmental concern as it contains toxic elements (i.e. lead, barium, zinc, etc.) which has a risk of leaching if it is not managed appropriately. Past studies have reported regarding the possible use of CRT glass as a part of aggregate in concrete production. However, incorporating waste CRT glass may present an environmental risk via leachability of toxic elements. Accordingly, the preventive measures for reducing the risk was proposed. The current work presented the experimental results regarding potential leaching of toxic elements from four types of concrete mixed, each compromising waste CRT glass as coarse aggregate with different shape and properties. Concentrations of detected elements are measure in the leachates by using atomic absorption spectrometry (AAS). Results indicate that the concentration of detected elements were found to be below applicable risk, despite the higher content of toxic elements in CRT glass. Therefore, the used of waste CRT glass as coarse aggregate in hardened concrete does not pose any risk of leachate of heavy metals to the environment.

Keywords: recycled CRT glass, coarse aggregate, physical properties, leaching, toxic elements

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Authors: Ghoul Rachid Brahim

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Introduction: Tuberculous spondylodiscitis is an infection of the spine by Mycobacterium tuberculosis. Tuberculous spondylodiscitis still remains a topical disease in developing countries and continues to pose a public health problem in endemic countries. Materials and methods: Clinical case: This is a 12-year-old child followed in pediatrics for weight loss and progressively worsening low back pain. The neurological examination found an irritative pyramidal syndrome in both lower limbs with a severe lumbar spinal syndrome. The radiological assessment: (Rx of the spine supplemented by CT and MRI) shows L1L2 spondylodiscitis. Treatment: The child is put on anti-tuberculosis treatment, and the spine is restrained with a corset. Control MRI shows a worsening of the dorsal kyphosis with a backward movement of the posterior wall and spinal cord compression. The child is operated on via the posterior approach (the operative procedure consists of an L1 laminectomy and D11 L3 osteosynthesis). Results: Spinal cord décompression and stabilization of the spine. Conclusion: Tuberculous spondylodiscitis in children remains a rare, aggressive, and progressive condition. The prognosis depends on the diagnosis's precocity and the therapeutic management quality.

Keywords: tuberculous spondylodiscitis, mycobacterium tuberculosis, laminectomy, MRI

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Authors: Isa Muhammad Zumo

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The African Great Green Wall (GGW) is a significant initiative in northern Nigeria because it promotes land restoration and conservation utilizing both commercial and species of forest trees while also helping to mitigate desertification and hazards from the sand dunes and shifting Sahara deserts. Conflicts and weather, however, pose a significant danger to the achievement of these goals. The scientific method for monitoring the vegetation dynamics since inception has not received the required attention, despite the African Development Bank (ADB)'s help in funding the project and its integration into the state's development plans for GGW initiatives. This study will monitor the changes in the vegetation cover of the great green wall within Yobe State Nigeria from 2014 to 2023. The vegetation dynamics will be monitored using Landsat 8 Operational Land Imager (OLI) for 6 years at 2 years intervals. The result will show the fluctuations in the vegetation cover density within the period of study. This will guide the design and implementation of policies of the GGW in achieving its objectives. The result can also contribute to the realization of Sustainable Development Goal (SDG) Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

Keywords: monitoring, green wall, Landsat 8, Nigeria

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Authors: Elijah Acquah-Andoh

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The UK has had its fair share of the shale gas revolutionary waves blowing across the global oil and gas industry at present. Although, its exploitation is widely agreed to have been delayed, shale gas was looked upon favorably by the UK Parliament when they recognized it as genuine energy source and granted licenses to industry to search and extract the resource. This, although a significant progress by industry, there yet remains another test the UK fracking resource must pass in order to render shale gas extraction feasible – it must be economically extractible and sustainably so. Developing unconventional resources is much more expensive and risky, and for shale gas wells, producing in commercial volumes is conditional upon drilling horizontal wells and hydraulic fracturing, techniques which increase CAPEX. Meanwhile, investment in shale gas development projects is sensitive to gas price and technical and geological risks. Using a Two-Factor Model, the economics of the Bowland shale wells were analyzed and the operational conditions under which fracking is profitable in the UK was characterized. We find that there is a great degree of flexibility about Opex spending; hence Opex does not pose much threat to the fracking industry in the UK. However, we discover Bowland shale gas wells fail to add value at gas price of $8/ Mmbtu. A minimum gas price of $12/Mmbtu at Opex of no more than $2/ Mcf and no more than $14.95M Capex are required to create value within the present petroleum tax regime, in the UK fracking industry.

Keywords: capex, economical, investment, profitability, shale gas development, sustainable

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Authors: Helen Sanders, Joshua Cousins

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The purpose of this study is to ascertain whether riparian buffer strips could be used to reduce Escherichia Coli (E. coli) runoff into streams in Central New York. Mainstream methods currently utilized to reduce E. coli runoff include fencing and staggered fertilizing plans for agriculture. These methods still do not significantly limit E. coli and thus, pose a serious health risk to individuals who swim in contaminated waters or consume contaminated produce. One additional method still in research development involves the planting of vegetated riparian buffers along waterways. Currently, riparian buffer strips are primarily used for filtration of nitrate and phosphate runoff to slow erosion, regulate pH and, improve biodiversity within waterways. For my research, four different stream sites were selected for the study, in which rainwater runoff was collected at both the riparian buffer and the E. coli sourced runoff upstream. Preliminary results indicate that there is an average 70% decrease in E. coli content in streams at the riparian buffer strips compared to upstream runoff. This research could be utilized to include vegetated buffer planting as a method to decrease manure runoff into essential waterways.

Keywords: Escherichia coli, riparian buffer strips, vegetated riparian buffers, runoff, filtration

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Authors: Akshada Amit Koparde, Candrakant S. Magdum

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Objective: To investigate the anti-arthritic activity of chloroform extract and Isolate 1 of Eulophia ochreata Lindl and dichloromethane extract and Isolate 2 of Zingiber cassumunar Roxb in adjuvant arthritic (AA) rat model induced by Freund’s complete adjuvant (FCA). Methods: Forty two healthy albino rats were selected and randomly divided into six groups. Freund’s complete adjuvant (FCA) was used to induce arthritis and then treated with chloroform extract, isolate 1 and dichloromethane extract, isolate 2 for 28 days. The various parameters like paw volume, haematological parameters (RBC, WBC, Hb and ESR), were studied. Structural elucidation of active constituents isolate 1 and isolate 2 from Eulophia ochreata Lindl and Zingiber cassumunar Roxb will be done using GCMS and H1NMR. Results: In FCA induced arthritic rats, there was significant increase in rat paw volume whereas chloroform extract and Isolate 1 of Eulophia ochreata Lindl and dichloromethane extract and Isolate 2 of Zingiber cassumunar Roxb treated groups showed strong significant reduction in paw volume. The altered haematological parameters in the arthritic rats were significantly recovered to near normal by the treatment with extracts at the dose of 200 mg/kg. Further histopathological studies revealed the anti-arthritic activity of Eulophia ochreata Lindl and Zingiber cassumunar Roxb by preventing cartilage and bone destruction of the arthritic joints of AA rats. Conclusion: Extracts and isolates of Eulophia ochreata Lindl and Zingiber cassumunar Roxb have shown anti-arthritic activity. Decrease in paw volume and normalization of haematological abnormalities in adjuvant induced arthritic rats is significantly seen in the experiment. Further histopathological studies confirmed the anti-arthritic activity of Eulophia ochreata Lindl and Zingiber cassumunar Roxb.

Keywords: arthritis, Eulophia ochreata Lindl, Freund's complete adjuvant, paw volume, Zingiber cassumunar Roxb

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

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High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

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Authors: Mohammad Qasim Mohammadi, Mohammad Arif Rohman

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Although socially sustainable building is becoming increasingly popular worldwide, past studies indicate that when policymakers support sustainable building development, the social dimension is often given insufficient attention or entirely disregarded. There are not many studies that focus on the problems of socially sustainable buildings in Afghanistan. This research investigates the factors that may hinder social sustainability implementation in residential building construction. The study will gather data from construction professionals by purposive sampling and employ Exploratory Factor Analysis (EFA) and Varimax for analysis. The results will undergo rigorous examination and thorough discussion. The expected results in this research will analyze the underlying barrier structure (factors) that hinder social sustainability, and each of these factors will represent a set of observed variables. In addition, the factor loadings show which barriers pose the greatest challenges. The primary goal of this study is to provide valuable insights into the impediment factors of social sustainability within the residential building environment, aiming to inform decision-making in the industry and encourage the adoption of more socially sustainable construction practices.

Keywords: social sustainability, residential building, barriers, drivers, afghanistan, factor analysis

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Authors: Tingke Wu, Yaping Huang

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Many cities in China have been experiencing serious urban sprawl since the 1980s, which pose great challenges to a country with scare cultivated land and huge population. Because of different social and economic context and development stage, driving forces of urban sprawl in China are quite different from developed countries. Therefore, it is of great importance to probe into urban sprawl driving mechanism in Chinese context. By a comparison study of the background and features of urban sprawl between China and developed countries, this research establishes an analytical framework for sprawl dynamic mechanism in China. By literature review and analyzing data from national statistical yearbook, it then probes into the driving mechanism and the primary cause of urban sprawl. The results suggest that population increase, economic growth, traffic and information technology development lead to rapid expansion of urban space; defects of land institution and lack of effective guidance give rise to low efficiency of urban land use. Moreover, urban sprawl is ultimately attributed to imperfections of policy and institution. On this basis, this research puts forward several sprawl control strategies in Chinese context.

Keywords: China, driving forces, driving mechanism, land institution, urban expansion, urban sprawl

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Eugene Muambeh Muntoh

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Corruption has a destructive effect on State institutions and on the capacity of States to respect, protect and fulfil human rights, particularly of those persons and groups in situation of vulnerability and marginalization. In Cameroon, corruption pose a major challenge as it divert public revenues and cripple public budgets that should provide healthcare, housing, education, and other essential services. Corruption has undermined the States’ ability to meet the minimum core obligations and pre-existing legal obligations to maximize all available resources to respect, protect and fulfil Economic, Social and Cultural Rights. This study therefore makes use of the qualitative research design, ranging from interviews, observations and content analysis of vital documents to provide evidence and associations between corruption and human rights concerns in Cameroon. The study made use of research material from both primary and secondary sources. Findings from the study reveals that the impact of corruption in Cameroon is especially pronounced regarding economic, social and cultural rights. In most cases, the right to be treated equally is violated, for example, when someone is requested to pay a bribe to obtain a public service. There is an urgent need for sustainable measures to counter corruption in order to protect and promote human rights.

Keywords: corruption, governance, human rights, law

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Brizita Djordjevic, Bojana Vidovic, Milica Zrnic, Uros Cakar, Ivan Stankovic, Davor Korcok, Sladjana Sobajic

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Histamine is a biogenic amine, which is formed by enzymatic decarboxylation from the amino acid histidine. It can be found in foods such as fish and fish products, meat and fermented meat products, cheese, wine and beer. The presence of histamine in these foods can indicate microbiological spoilage or poor manufacturing processes. The consumption of food containing large amounts of histamine can have toxicological consequences. In 62 food products (31 canned fish products, 19 wines and 12 cheeses) from the market of Serbia the content of histamine was determined using enzyme-linked immunosorbent assay (ELISA) test kit according to the manufacturer's instructions (Immunolab GmbH, Kassel, Germany). The detection limits of this assay were 20 µg/kg for fish and cheese and 4 µg/L for wine. The concentration of histamine varied between 0.16-207 mg/kg in canned fish products, 0.03-1.47 mg/kg in cheeses and 0.01- 0.18 mg/L in wines. In all analyzed canned fish products the results obtained for the histamine were below the limits set by European and national legislation, so they can be considered acceptable and safe for the health consumers. The levels of histamine in analyzed cheeses and wines were very low and did not pose safety concerns.

Keywords: cheese, enzyme-linked immunosorbent assay, histamine, fish products, wine

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