15 research outputs found

    Law and Modern Technology: Lack of Tech Knowledge in Legal Profession May Cause Injustice

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    There is no such field where technology hasn’t reached. It will be a dream to think something without technology. In today’s world every field requires tech knowledge. The courtroom and law offices have changed with the evolution of technology. Most courts don’t accept paper files anymore. Law offices use virtual file to store client information. However, due to old age or other reason a significant number of attorneys and judges are not competent in technology. This paper will examine the use of technology in our legal system and what problem arises due to lack of proper tech knowledge. Increasing use of computer and internet in the courtroom and law office, trial presentation, keeping client’s confidential data secure, legal researching, e-filing document with the court require tech knowledge. This paper will discuss the necessity of tech knowledge, ethical obligation, expert’s opinions and case laws to demonstrate that to practice laws nowadays requires tech knowledge. After examining all relevant materials, this paper has revealed that to comply with the digital world all legal professionals should have enough tech knowledge for better litigation and avoid errors in the litigation

    Forensic Science: Complex Admissibility Standard for Scientific Evidence and Expert Witness\u27s Testimony

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    Modern science forces the world to accept new theories and invention. Science has invented several tools, which are used in the legal system to dispute criminal cases. Scientific evidence and expert witness testimony have weight in the courtroom because those are scientifically proved to be true. Even though there are few case laws and Federal rule of evidence 1975, still the admissibility standard is complex which may lead injustice. This article examines the Federal rule of evidence, case laws and scholars’ opinion to address the complexity of the admissibility standard of scientific evidence and expert testimony. The first legal question raised relating the admissibility standard was Frye v. United States (1923) where the court ruled that any scientific method or practice must be generally accepted by the scientific community at large. The First Federal rule of evidence was adopted in 1975. In 1980`s scientific scholars began to questioning the authenticity of the admitted scientific evidence saying the kind of expertise regularly accepted as admissible by courts was, frankly, \u27junk\u27 of scandalous lack of dependability. \u27 To address the problem of junk science in the courtroom, the United States Supreme Court decided Daubert v. Merrell Dow Pharma, Inc. (1993) In this case the Court addressed a new standard for determining the admissibility of scientific evidence in the federal courts of the U.S. After examining the case laws and statues, it revealed US has legal system has complex admissibility standard for scientific evidence and expert witness interpreted by the judges and may serve injustice to innocent people

    Manifesting a mobile application on safety which ascertains women salus in Bangladesh

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    This paper reflects on the indemnity of women in our society. The proposed model ensures the embodiment of a mobile application. The algorithm, we developed for this model focuses the safety issues which is applicable to both inside as well as outside of the house for the women in Bangladesh. The solution of this problems can be done through some interrelated features such as i) SOS button pressing which ensures automatic calling, instant location tracking system through GPS of the phone and sending tracked location to all trusted numbers, automatically secrete video recording system ii) voice command detection which assures exact same features as SOS button pressing iii) phone shaking features serve user instant immunity by calling a trusted number. This research also assures experimented data analysis at Dhaka city based on respond time, the time it takes to arrive the SMS and Phone call and current location of the victim. Also do a short comparison among the most popular safety related mobile applications

    Characterization of Biochar from Different Feedstocks under Low and High Temperature and Their Effects on Greenhouse Gas Emission and Ammonia Volatilazation from Soil Incubation

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    Biochar is a potential soil amendment that likely to reduce GHG emissions from land application to soil, but their properties depend on biomass types and pyrolysis temperature. In this study, biochars were produced from different biomasses (wet distiller grains (WDG), dry distiller grains (DDG), and corn stover (CS)) at two temperatures (low & high). Biochars were analyzed for pH, electrical conductivity, proximate and ultimate analysis, elemental analysis, and morphological structure. Also, biochar's efficacy on GHGs and ammonia (NH3) emission were measured from soil and manure incubated at 25? for 76 days. DDG and CS derived biochar properties outperformed other biochars. Manure treated with high-temperature DDG biochar emitted the lowest amount of N2O (0.09 mg N2O-N kg?1), and CH4 (0.04 mg CH4-C kg?1). Biochar application also reduced CO2 emission from 11 to 59%, but resulted in higher cumulative NH3 volatilization. Overall, biochars reduced GHG emissions when applied with N treatments

    Study on Influence of Macro-trauma Injuries on the Psychology of a Sportsman

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    This study presents the influence of macro trauma also known as a large-scale injury on the psychology of a sportsman, which may have been happening over some time going before the certified affirmation that injury is obvious. By macro trauma sports injury, individual, and social qualities, may compellingly affect the harmed sportsmen. Wounds, while ideally rare, are regularly an unavoidable piece of game support. While most macro-trauma injury wounds can be dealt with practically zero disturbance in-game support and different exercises of everyday living, some force a significant physical and mental weight. An idiopathic etiology where the purpose behind brokenness is dark may extend vibes of disappointment, shock, and distress, especially if the hurt contender cannot promptly the point of convergence of recuperation, besides, set conspicuous destinations. For the study of the cases, convenience sampling is applied for selecting focus-group participants and for interviews 40 were approached and asked for their participation according to their availability. The findings of the study stated that, for the sportspersons, the mental reaction to a macro trauma injury could trigger or expose genuine psychological wellness issues like melancholy, uneasiness, confused eating, and substance use or misuse. At the point when a sportsman is harmed, a typical passionate response incorporates preparing the clinical data about the injury given by the clinical group, just as adapting sincerely to the macro trauma injury

    Impact of land use change on ecosystem services of southwest coastal Bangladesh

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    This study assessed impact of land use change on ecosystem services (ES) of the southwest coastal Bangladesh, by combining Landsat data and published value coefficients of different ecosystems. Land use categories were estimated using satellite images from 1980–2016. Changes in the value of ES delivered by each of the land use categories were estimated from respective value coefficients. Results revealed that agriculture land decreased by 253,928\ua0ha and aquaculture land increased by 272,032\ua0ha within 1980–2016. Meanwhile, the total value of ES decreased from US90.45to88.22billion.Declineofagriculturewasthelargestcontributor(US 90.45 to 88.22 billion. Decline of agriculture was the largest contributor (US 1.41 billion) to the loss of ES, followed by deforestation (US$ 0.94 billion). Forest is the major contributor to the ES of this region and could largely impact on the ES value. Future land use policy could be targeted to promote sustainable agriculture and conservation of forest

    WaterHyacinth: A comprehensive image dataset of various Water hyacinth species from different regions of Bangladesh

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    The “WaterHyacinth” dataset, a recently gathered collection of images featuring four distinct species of Water hyacinth from different regions of Bangladesh, is presented in this article. There are four different classifications: Lemna minor, Eichhornia crassipes, Monochoria korsakowii, and Pistia stratiotes. The collection consists of 1790 original images and in addition 4050 augmented photos of Water hyacinth species. Every original picture was captured with the appropriate background and in sufficient natural light. Every image was correctly placed in its corresponding subfolder, providing optimal use of the pictures by various machine learning and deep learning models. Researchers could make major progress in agriculture, environmental monitoring, aquatic science, and remote sensing domains by utilizing this enormous dataset and various machine learning and deep learning approaches. In addition to opening opportunities for significant developments in these domains, it offers an essential asset for further study

    Species classification of brassica napus based on flowers, leaves, and packets using deep neural networks

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    Deep learning (DL) has gradually taken the lead as the most effective approach in the agricultural fields due to the early identification and classification of plant species and diseases for improving the quality of crop production because of recent technological breakthroughs, which have had a significant impact on agriculture. Plenty of complicated problems in farming, including species classification, plant disorder identification, yield approximation, and weather and soil moisture prediction, are made simple using deep neural networks. Thus, this proposed study aims to classify Brassica Napus (B. Napus) rapeseed species based on their most significant features, like flowers, leaves, and packets. The study has adopted two types of rapeseed such as B. Rapa and B. Alba. Five contemporary deep learning-based Convolutional Neural Network (CNN) models have also been assessed for distinguishing rapeseed species. These models are DenseNet201, VGG19, InceptionV3, Xception, and ResNet50. Initially, the researchers collected data from the agricultural field, and then image pre-processing is performed to create our dataset. After that, CNN models were applied to this dataset and enumerated the experimental data accordingly. Our DenseNet201 model successfully classified both species with the highest accuracy of 100% for flowers and 97% for both packets and leaves. A comprehensive analysis with companion studies confirmed the efficacy of our preferred paradigm for the near future. Nevertheless, future studies will compare these methodologies to data from a separate metabolomics dataset from comparable crops
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