Identification of surface water and groundwater relationship at Universiti Tun Hussein Onn Malaysia (UTHM) Campus

Descriptions of the surface water and groundwater relationships are required for enhanced water resource management. The increase in population and rapid development has boosted the demand and use of water supply each year in Parit Raja. Moreover, no further research related to relationships between both sources has been carried out in this flat topography area. Thus, the descriptions of surface water and groundwater relationships are required to enhance water resource management in UTHM campus in order to meet the future demands. The Schlumberger array was used for Electrical Resistivity Imaging (ERI) during data acquisition to identify potential shallow aquifers and suitable locations for boreholes which function as observation wells. Three new boreholes were installed and the ERI results showed that this area recorded low resistivity values less than 10 Ωm with potential groundwater at varying depths between 10 to 30 m. Meanwhile, in hydrochemical analysis the chemical properties of major cations (Na+, Mg2+, K+, Ca2+) and anions (Cl-, SO42-, NO3-) were analysed to characterise surface water and groundwater. The result showed that all surface water is characterized by Ca2+ - Mg2+- Cl- - SO42- types of fresh water, while the groundwater is characterized by Na-Cl type of saline water due to seawater intrusion which indicated that the interaction of surface water and groundwater were not occur in this study area and the recharge areas might be located outside this area. This result interpreted that the lakes and swale were remained in good quality whereas groundwater at this aquifer was seriously intruded by seawater. Even though, the isotopic composition for δ18O and δ2H values of surface water were relatively similar to that of groundwater samples in Station A and Station C as they varying between -4.32%o to -9.74%o for δ18O and from -33.86%o to -65.82%o for δ2H, these surface water samples had low salinity (Cl- 3000 mg/l). This result could be explained by effects of evaporation and seawater intrusion on these groundwater samples rather than interaction with surface water. Thus, the relationships of surface water and groundwater might not occur in UTHM campus and the recharge areas might be located outside this area

Multiparty Dynamics and Failure Modes for Machine Learning and Artificial Intelligence

An important challenge for safety in machine learning and artificial intelligence systems is a~set of related failures involving specification gaming, reward hacking, fragility to distributional shifts, and Goodhart's or Campbell's law. This paper presents additional failure modes for interactions within multi-agent systems that are closely related. These multi-agent failure modes are more complex, more problematic, and less well understood than the single-agent case, and are also already occurring, largely unnoticed. After motivating the discussion with examples from poker-playing artificial intelligence (AI), the paper explains why these failure modes are in some senses unavoidable. Following this, the paper categorizes failure modes, provides definitions, and cites examples for each of the modes: accidental steering, coordination failures, adversarial misalignment, input spoofing and filtering, and goal co-option or direct hacking. The paper then discusses how extant literature on multi-agent AI fails to address these failure modes, and identifies work which may be useful for the mitigation of these failure modes.Comment: 12 Pages, This version re-submitted to Big Data and Cognitive Computing, Special Issue "Artificial Superintelligence: Coordination & Strategy

Corporate Governance, Innovative Enterprise, and Economic Development

corporate governance, innovative enterprise, economic development