Search results for: legal recognition

Authors: Bin Liu

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Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

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Authors: Zsofia Patyi

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While empirical studies under socialism in Hungary focused on the lawyer society as a whole, current research deals with law students in specific. The change of regime and the mutation of legal education have influenced the motivation, efficiency, social background and self-concept of law students. This shift needs to be acknowledged, and the education system improved for students and together with students. A new law student society requires a different legal education system, different legal studies, or, at the minimum, a different approach to teaching law. This is to ensure that competitive lawyers be trained who understand the constantly changing nature of the law and, as a result, can potentially transform or create legislation themselves. A number of developments can affect law students’ awareness of legal relations in a democratic state. In today’s Hungary, these decisive factors are primarily the new regulation of the financing of law students, and secondly, the new Hungarian constitution (henceforth: Alaptörvény), which has modified the base of the Hungarian legal system. These circumstances necessitate a new, comprehensive, and empirical, investigation of law students. To this end, our research team (comprising a professor, a Ph.D. student, and two law students), is conducting a new type of study in February 2017. The first stage of the research project uses the desktop method to open up the research antecedents. Afterward, a structured questionnaire draft will be designed and sent to the Head of Department of Sociology and the Associate Professor of the Department of Constitutional Law at the University of Szeged to have the draft checked and amended. Next, an open workshop for students and teachers will be organized with the aim to discuss the draft and create the final questionnaire. The research team will then contact each Hungarian university with a Faculty of Law to reach all 1st- and 4th-year law students. 1st-year students have not yet studied the Alaptörvény, while 4th-year students have. All students will be asked to fill in the questionnaire (in February). Results are expected to be in at the end of February. In March, the research team will report the results and present the conclusions. In addition, the results will be compared to previous researches. The outcome will help us answer the following research question: How should legal studies and legal education in Hungary be reformed in accordance with law students and the future lawyer society? The aim of the research is to (1) help create a new student- and career-centered teaching method of legal studies, (2) offer a new perspective on legal education, and (3) create a helpful and useful de lege ferenda proposal for the attorney general as regards legal education as part of higher education.

Keywords: change, constitution, investigation, law students, lawyer society, legal education, legal studies, motivation, reform

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Authors: Mandeep Saini

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The rapid advancement of Artificial Intelligence (AI) is transforming various fields, including intellectual property law. This paper explores the emerging role of AI in interpreting patent claims, a critical and highly specialized area within intellectual property rights. Patent claims define the scope of legal protection granted to an invention, and their precise interpretation is crucial in determining the boundaries of the patent holder's rights. Traditionally, this interpretation has relied heavily on the expertise of patent examiners, legal professionals, and judges. However, the increasing complexity of modern inventions, especially in fields like biotechnology, software, and electronics, poses significant challenges to human interpretation. Introducing AI into patent claim interpretation raises several legal and ethical concerns. This paper addresses critical issues such as the reliability of AI-driven interpretations, the potential for algorithmic bias, and the lack of transparency in AI decision-making processes. It considers the legal implications of relying on AI, particularly regarding accountability for errors and the potential challenges to AI interpretations in court. The paper includes a comparative study of AI-driven patent claim interpretations versus human interpretations across different jurisdictions to provide a comprehensive analysis. This comparison highlights the variations in legal standards and practices, offering insights into how AI could impact the harmonization of international patent laws. The paper proposes policy recommendations for the responsible use of AI in patent law. It suggests legal frameworks that ensure AI tools complement, rather than replace, human expertise in patent claim interpretation. These recommendations aim to balance the benefits of AI with the need for maintaining trust, transparency, and fairness in the legal process. By addressing these critical issues, this research contributes to the ongoing discourse on integrating AI into the legal field, specifically within intellectual property rights. It provides a forward-looking perspective on how AI could reshape patent law, offering both opportunities for innovation and challenges that must be carefully managed to protect the integrity of the legal system.

Keywords: artificial intelligence (ai), patent claim interpretation, intellectual property rights, algorithmic bias, natural language processing, patent law harmonization, legal ethics

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Authors: M. Dabirinezhad, M. Bayat Pour, A. Dabirinejad

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Recognition of the color spectrum of the teeth plays a significant role in the dental laboratories to produce dentures. Since there are various types and colours of teeth for each patient, there is a need to specify the exact and the most suitable colour to produce a denture. Usually, dentists utilize pallets to identify the color that suits a patient based on the color of the adjacent teeth. Consistent with this, there can be human errors by dentists to recognize the optimum colour for the patient, and it can be annoying for the patient. According to the statistics, there are some claims from the patients that they are not satisfied by the colour of their dentures after the installation of the denture in their mouths. This problem emanates from the lack of sufficient accuracy during the colour recognition process of denture production. The colour recognition pen (CRP) is a technology to distinguish the colour spectrum of the intended teeth with the highest accuracy. CRP is equipped with a sensor that is capable to read and analyse a wide range of spectrums. It is also connected to a database that contains all the spectrum ranges, which exist in the market. The database is editable and updatable based on market requirements. Another advantage of this invention can be mentioned as saving time for the patients since there is no need to redo the denture production in case of failure on the first try.

Keywords: colour recognition pen, colour spectrum, dental laboratory, denture

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Authors: Gianni Izzo

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The relation of Islam to its legal precepts, reflected in the various jurisprudential 'schools of thought' (madhahib), is one expressed in a version of 'positivism' (fiqh) providing the primary theory for deducing Qurʾan rulings and those from the narrations (hadith) of the Prophet Muhammad. Scholars of Islam, including Patricia Crone (2004) and others chronicled by Anver Emon (2005), deny the influence of natural law theories as extra-scriptural indices of revelation’s content. This paper seeks to dispute these claims by reference to historical and canonical examples within Shiʿa legal thought that emphasize the salient roles of ‘aql (reason), fitrah (primordial human nature), and lutf (divine grace). These three holistic features, congenital to every human, and theophanically reflected in nature make up a mode of moral intelligibility antecedent to prophetic revelation. The debate between the 'traditionalist' Akhbaris and 'rationalist' Usulis over the nature of deriving legal edicts in Islam is well-covered academic ground. Instead, an attempt is made to define and detail the built-in assumptions of natural law revealed in the jurisprudential summa of Imami Shiʿism, whether of either dominant school, that undergird its legal prescriptions and methods of deduction.

Keywords: Islam, fiqh, natural law, legal positivism, aql

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

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A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Ahmad Alwosheel, Ahmed Alqaraawi

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This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.

Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Pratyusha Das

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A paradigm shift has been noticed in the interpretation of DNA evidence for determining paternity. Sometimes DNA evidence has been accepted while sometimes it was rejected by the Indian Courts. Courts have forwarded various justifications for acceptance and rejection of such evidence through legal and scientific means. Laws have also been changed to accommodate the necessities of society. Balances between both the legal and scientific approaches are required, to make the best possible use of DNA evidence for the well-being of the society. Specifications are to be framed as to when such evidence can be used in the future by pointing out the pros and cons. Judicial trend is to be formulated to find out the present situation. The study of cases of superior courts of India using an analytical and theoretical approach is driving the questions regarding the shared identity of the legal and scientific approaches. To assimilate the differences between the two approaches, the basic differences between them have to be formulated. Revelations are required to access the favorable decisions using the DNA evidence. Reasons are to be forwarded for the unfavorable decisions and the approach preferred in such cases. The outcome of the two methods has to be assessed in relation to the parties to the dispute, the society at large, the researcher and from the judicial point of view. The dependability of the two methods is to be studied in relation to the justice delivery system. A highlight of the chronological study of cases along with the changes in the laws with the aid of presumptions will address the questions of necessity of a method according to the facts and situations. Address is required in this respect whether the legal and scientific forces converge somewhere pushing the traditional identification of paternity towards a fundamental change.

Keywords: cases, evidence, legal, scientific

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research and transfers of big data are not confined to a particular jurisdiction, but there is a lack of clarity regarding the legal requirements for importing and exporting such data. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

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Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Richard J. Sobelsohn

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Green Building and Sustainable Development help fight climate change, and protects the ozone, animal habitats, air quality, and ground water. The myriad of reasons to go Green has multiplied to the point that a developer that is building a ground-up or renovating/retrofitting a property has a plethora of choices to get to the green goal post. Sustainability not affects the bottom line but satisfies corporate mandates (ESG), consumer demand, market requirements, and the many laws dictating green building practices. The good news is that there are many paths a property owner can take to become green. The bad news is that there are many paths a property owner can take to become green, and they need to choose which direction to take. Certification of a building used to be the highest achievement in the Green building world. Now there are so many variables and laws with which a property owner must comply, and the legal analysis has mushroomed. Operation and Maintenance have also become one of the most important functions for a prudent Green Building owner. So adding to the “development/retrofit” parties involved in the sustainable building legal world, we now need to include all those people who keep the building green, and there are a lot of them!

Keywords: green building, sustainable development, legal issues, greenwashing, green cleaning, compliance, ESQ

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Authors: Maria Pavlova

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In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

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Authors: Shih-Yu Lo

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Stereotypes exist in almost every society, affecting how people interact with each other. However, to our knowledge, the influence of stereotypes was rarely explored in the context of basic perceptual processes. This study aims to explore how the gender stereotype affects object recognition. Participants were presented with a series of scene pictures, followed by a target display with a man or a woman, holding a weapon or a non-weapon object. The task was to identify whether the object in the target display was a weapon or not. Although the gender of the object holder could not predict whether he or she held a weapon, and was irrelevant to the task goal, the participant nevertheless tended to identify the object as a weapon when the object holder was a man than a woman. The analysis based on the signal detection theory showed that the stereotype effect on object recognition mainly resulted from the participant’s bias to make a 'weapon' response when a man was in the scene instead of a woman in the scene. In addition, there was a trend that the participant’s sensitivity to differentiate a weapon from a non-threating object was higher when a woman was in the scene than a man was in the scene. The results of this study suggest that the irrelevant social cues implied in the visual scene can be very powerful that they can modulate the basic object recognition process.

Keywords: gender stereotype, object recognition, signal detection theory, weapon

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Authors: Umeda Junaydova

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Legal aid is a key element of access to justice. According to UN Principles and Guidelines on Access to Legal Aid in Criminal Justice Systems, state members bear the obligation to put in place accessible, effective, sustainable, and credible legal aid systems. Regarding this obligation, developing countries, such as Tajikistan, faced challenges in terms of financing this system. Thus, many developed nations have launched rule-of-law programs to support these states and ensure access to justice for all. Following independence from the Soviet Union, Tajikistan committed to introducing the rule of law and providing access to justice. This newly established country was weak, and the sudden outbreak of civil war aggravated the situation even more. The country needed external support and opened its door to attract foreign donors to assist it in its way to development. In 2015, Tajikistan, with the financial support of development partners, was able to establish a state-funded legal aid system that provides legal assistance to vulnerable and marginalized populations, including in criminal cases. In the beginning, almost the whole system was financed from donor funds; by that time, the contribution of the government gradually increased, and currently, it covers 80% of the total budget. All these governments' actions toward ensuring access to criminal legal aid for disadvantaged groups look promising; however, the reality is completely different. Currently, not all disadvantaged people are covered by these services, and their cases are most of the time considered without appropriate defense, which leads to violation of fundamental human rights. This research presents a comprehensive exploration of the interplay between donor assistance and the effectiveness of legal aid services in Tajikistan, with a specific focus on criminal cases involving vulnerable groups, such as women and children. In the context of Tajikistan, this study addresses a pressing concern: despite substantial financial support from international donors, state-funded legal aid services often fall short of meeting the needs of poor and vulnerable populations. The study delves into the underlying complexities of this issue and examines the structural, operational, and systemic challenges faced by legal aid providers, shedding light on the factors contributing to the ineffectiveness of legal aid services. Furthermore, it seeks to identify the root causes of these issues, revealing the barriers that hinder the delivery of adequate legal aid services. The research adopts a socio-legal methodology to ensure an appropriate combination of multiple methodologies. The findings of this research hold significant implications for both policymakers and practitioners, offering insights into the enhancement of legal aid services and access to justice for disadvantaged and marginalized populations in Tajikistan. By addressing these pressing questions, this study aims to fill the gap in legal literature and contribute to the development of a more equitable and efficient legal aid system that better serves the needs of the most vulnerable members of society.

Keywords: access to justice, legal aid, rule of law, rights for council

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Authors: Mina Youssef Makram Ibrahim

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Engineering identity contributes to the professional and academic sustainability of female engineers. Recognizability is an important factor that shapes an engineer's identity. People who are deprived of real recognition often fail to create a positive identity. This study draws on Hornet’s recognition theory to identify factors that influence female civil engineers' sense of recognition. Over the past decade, a survey was created and distributed to 330 graduate students in the Department of Civil, Civil and Environmental Engineering at Iowa State University. Survey items include demographics, perceptions of a civil engineer's identity, and factors that influence recognition of a civil engineer's identity, such as B. Opinions about society and family. Descriptive analysis of survey responses revealed that perceptions of civil engineering varied significantly. The definitions of civil engineering provided by participants included the terms structure, design and infrastructure. Almost half of the participants said the main reason for studying Civil Engineering was their interest in the subject, and the majority said they were proud to be a civil engineer. Many study participants reported that their parents viewed them as civil engineers. Institutional and operational treatment was also found to have a significant impact on the recognition of women civil engineers. Almost half of the participants reported feeling isolated or ignored at work because of their gender. This research highlights the importance of recognition in developing the identity of women engineers.

Keywords: civil service, hiring, merit, policing civil engineering, construction, surveying, mapping, pile civil service, Kazakhstan, modernization, a national model of civil service, civil service reforms, bureaucracy civil engineering, gender, identity, recognition

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Authors: Norbert Tribl

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European contemporary scientific public opinion considers the concept of constitutional identity as a highlighted issue. Some scholars interpret the matter as the manifestation of a conflict of Europe. Nevertheless, constitutional identity is a bridge between the Member States and the EU rather than a river that will wash away the achievements of the integration. In accordance with the opinion of the author, the main problem of constitutional identity in Europe is the undetermined nature: the exact concept of constitutional identity has not been defined until now. However, this should be the first step to understand and use identity as a legal institution. Having regard to this undetermined nature, the legal-theoretical examination of constitutional identity is the main purpose of this study. The concept of constitutional identity appears in the Anglo-Saxon legal systems by a different approach than in the supranational system of European Integration. While the interpretation of legal institutions in conformity with the constitution is understood under it, the European concept is applied when possible conflicts arise between the legal system of the European supranational space and certain provisions of the national constitutions of the member states. The European concept of constitutional identity intends to offer input in determining the nature of the relationship between the constitutional provisions of the member states and the legal acts of the EU integration. In the EU system of multilevel constitutionalism, a long-standing central debate on integration surrounds the conflict between EU legal acts and the constitutional provisions of the member states. In spite of the fact that the Court of Justice of the European Union stated in Costa v. E.N.E.L. that the member states cannot refer to the provisions of their respective national constitutions against the integration. Based on the experience of more than 50 years since the above decision, and also in light of the Treaty of Lisbon, we now can clearly see that EU law has itself identified an obligation for the EU to protect the fundamental constitutional features of the Member States under Article 4 (2) of Treaty on European Union, by respecting the national identities of member states. In other words, the European concept intends to offer input for the determination of the nature of the relationship between the constitutional provisions of the member states and the legal acts of the EU integration.

Keywords: constitutional identity, EU law, European Integration, supranationalism

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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Authors: Vesali Naseh Morteza, Najafi Mohammad Hosein

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The possibility of trading in-game items for real money provides a high economic capacity for online games and turns them into a business model. Nowadays, the market for in-game item purchases and microtransactions or micropayments has been growing increasingly. Since the market should be legal, lawyers and lawmakers around the world have expressed concerns over the legality of online gaming and in-game transactions. The issue is highlighted by the recent emergence of an in-game business model in the name of loot boxes. Similarities between loot boxes gaming and gambling features activities have started a legal debate as to whether loot boxes constitute a form of gambling or whether the game’s use of loot boxes should be considered gambling. Hence, based on the relationship between loot boxes purchasing and problem gambling, the paper investigates the legal effect of the newly emergent phenomenon of loot boxes on online games from the perspective of Iranian law.

Keywords: serious games, loot boxes, online gambling, in-game purchase, virtual items

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Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

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Authors: Malcolm Richardson, Gabriele Richardson

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This paper illustrates how historical problems can be studied successfully using GIS even in cases in which data, in the modern sense, is fragmentary. The overall problem under investigation is how early (1300-1500) English schools of Common Law moved from apprenticeship training in random individual London inns run in part by clerks of the royal chancery to become what is widely called 'the Third University of England,' a recognized system of independent but connected legal inns. This paper focuses on the preparatory legal inns, called the Inns of Chancery, rather than the senior (and still existing) Inns of Court. The immediate problem studied in this paper is how the junior legal inns were organized, staffed, and located from 1292 to about 1500, and what maps tell us about the role of the chancery clerks as managers of legal inns. The authors first uncovered the names of all chancery clerks of the period, most of them unrecorded in histories, from archival sources in the National Archives, Kew. Then they matched the names with London property leases. Using ArcGIS, the legal inns and their owners were plotted on a series of maps covering the period 1292 to 1500. The results show a distinct pattern of ownership of the legal inns and suggest a narrative that would help explain why the Inns of Chancery became serious centers of learning during the fifteenth century. In brief, lower-ranking chancery clerks, always looking for sources of income, discovered by 1370 that legal inns could be a source of income. Since chancery clerks were intimately involved with writs and other legal forms, and since the chancery itself had a long-standing training system, these clerks opened their own legal inns to train fledgling lawyers, estate managers, and scriveners. The maps clearly show growth patterns of ownership by the chancery clerks for both legal inns and other London properties in the areas of Holborn and The Strand between 1450 and 1417. However, the maps also show that a royal ordinance of 1417 forbidding chancery clerks to live with lawyers, law students, and other non-chancery personnel had an immediate effect, and properties in that area of London leased by chancery clerks simply stop after 1417. The long-term importance of the patterns shown in the maps is that while the presence of chancery clerks in the legal inns likely created a more coherent education system, their removal forced the legal profession, suddenly without a hostelry managerial class, to professionalize the inns and legal education themselves. Given the number and social status of members of the legal inns, the effect on English education was to free legal education from the limits of chancery clerk education (the clerks were not practicing common lawyers) and to enable it to become broader in theory and practice, in fact, a kind of 'finishing school' for the governing (if not noble) class.

Keywords: GIS, law, London, education

Procedia PDF Downloads 174

Authors: Leandro Moura da Silva

Abstract:

The international community has strived to create legal mechanisms to protect their biodiversity, but this can represent, sometimes, particularly in the case of regulatory regime on access to genetic resources, an excessive nationalism which transforms itself into a significant obstacle to scientific progress causing damages to the country and to local farmers. Although it has been poorly publicized in the media, the international legal system was marked, in 2014, by the entry into force of the Nagoya Protocol, which regulates the access and benefit sharing of genetic resources of the States Party to that legal instrument. However, it’s not reasonable to think of regulating access to genetic resources without reflecting on the links of this important subject with other related issues, such as family farming and agribusiness, food safety, food security, intellectual property rights (on seeds, genetic material, new plant varieties, etc.), environmental sustainability, biodiversity, and biosafety.

Keywords: international law, regulation on agriculture, agronomy techniques, sustainability, genetic resources and new crop varieties, CBD, Nagoya Protocol, ITPGRFA

Procedia PDF Downloads 501

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

Abstract:

Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

Procedia PDF Downloads 153

Authors: Hirokatsu Kawashima

Abstract:

One important element of teaching/learning listening is intensive listening such as listening for precise sounds, words, grammatical, and semantic units. Several classroom-based investigations have been conducted to explore the usefulness of auditory recognition of phonological, grammatical and semantic errors in such a context. The current study reports the results of one such investigation, which targeted auditory recognition of phonological, grammatical, and semantic errors at the sentence level. 56 Japanese EFL learners participated in this investigation, in which their recognition performance of phonological, grammatical and semantic errors was measured on a 9-point scale by learners’ self-evaluation from the perspective of 1) two types of similar English sound (vowel and consonant minimal pair words), 2) two types of sentence word order (verb phrase-based and noun phrase-based word orders), and 3) two types of semantic consistency (verb-purpose and verb-place agreements), respectively, and their general listening proficiency was examined using standardized tests. A number of findings have been made about the interactive relationships between the three types of auditory error recognition and general listening proficiency. Analyses based on the OPLS (Orthogonal Projections to Latent Structure) regression model have disclosed, for example, that the three types of auditory error recognition are linked in a non-linear way: the highest explanatory power for general listening proficiency may be attained when quadratic interactions between auditory recognition of errors related to vowel minimal pair words and that of errors related to noun phrase-based word order are embraced (R2=.33, p=.01).

Keywords: auditory error recognition, intensive listening, interaction, investigation

Procedia PDF Downloads 513

Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

Abstract:

Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

Procedia PDF Downloads 116